Buffer Occupancy-Based Congestion Control Protocol for Wireless Multimedia Sensor Networks

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This paper presented a novel congestion control protocol, named Buffer Occupancy Based Congestion Control (BOCC), designed for Wireless Multimedia Sensor Networks (WMSNs). It aimed to address congestion issues that lead to buffer overflow and degraded Quality of Service (QoS). The paper could be improved based on the following comments.

-- Specific quantitative improvements (e.g., percentage reduction in packet loss or delay) should be included in the abstract to provide a clearer picture of the protocol's effectiveness.

-- Discuss the gap in existing research that BOCC addresses in the introduction.

-- Expand the literature review to include more recent studies on congestion control protocols including the following ones: RoboFiSense: attention-based robotic arm activity recognition with WiFi sensing; Fuzing multiple erroneous sensors to estimate travel time; Developing an eco-driving strategy in a hybrid traffic network using reinforcement learning.

-- I was wondering why the Raspberry Pi was chosen as the platform.

-- I was wondering how the performance of BOCC translates into real-world applications.

-- The conclusion should succinctly summarize the key findings and their significance without introducing new information.

-- Study how BOCC can be combined with Internet of Things (IoT) frameworks, considering the increasing number of connected devices.

 

-- Study the potential of machine learning for adaptive congestion control in WMSNs, enabling dynamic adjustments based on traffic patterns.

Comments on the Quality of English Language

The paper needs minor English editing.

Author Response

Dear Reviewer,

We are very grateful to you for giving us an opportunity to revise our manuscript. We appreciate you and the respected reviewers for their constructive comments and suggestions on our manuscript entitled “Buffer Occupancy Based Congestion Control (BOCC) for Wireless Multimedia Sensor Networks (WMSNs)”. Based on these comments and suggestions, we have made careful modifications on the original manuscript. The comments of reviewers are in italic, while our response in plain text. The modified texts in the manuscript are in red font to highlight the changes made for quick review. We are very grateful to the reviewer for their time and valuable comments. The comments are very helpful to further enhance our manuscript.

 

 

 

 

Point-by-point response

 

This paper presented a novel congestion control protocol, named Buffer Occupancy Based Congestion Control (BOCC), designed for Wireless Multimedia Sensor Networks (WMSNs). It aimed to address congestion issues that lead to buffer overflow and degraded Quality of Service (QoS). The paper could be improved based on the following comments.

Response

We would like to express our gratitude to the reviewer for the insightful feedback on our manuscript titled "Buffer Occupancy Based Congestion Control Protocol for Wireless Multimedia Sensor Network." Your suggestions are invaluable in refining our work, and we have addressed each point as follows:

1. Specific quantitative improvements (e.g., percentage reduction in packet loss or delay) should be included in the abstract to provide a clearer picture of the protocol's effectiveness

Response: 

 

Thank you for your valuable feedback. We have revised the abstract to include specific quantitative improvements related to the performance of the Buffer Occupancy Based Congestion Control (BOCC) protocol. The updated abstract now highlights Experimental results based on raspberry pi sensor nodes show that the BOCC protocol achieves up to 16% reduction in packet loss and up to 23% reduction in average end-to-end delay compared to state of art congestion control algorithms. compared to traditional congestion control mechanisms. We believe that these additions provide a clearer picture of the protocol's effectiveness and its impact on maintaining Quality of Service (QoS) in Wireless Multimedia Sensor Networks (WMSNs).

 

2. Discuss the gap in existing research that BOCC addresses in the introduction.

 

Response

Thank you for your insightful comment regarding the identification of research gaps in the introduction. We have revised the introduction to explicitly discuss the gaps in existing research that the Buffer Occupancy Based Congestion Control (BOCC) protocol addresses.

In the revised section, we added the following two paragraphs:

1. {Existing congestion control protocols for Wireless Multimedia Sensor Networks (WMSNs) primarily focus on either traffic-based or resource-based mechanisms, with some hybrid approaches attempting to balance both. However, these protocols often face limitations in high-density networks where buffer overflow and packet loss compromise Quality of Service (QoS) due to insufficient prioritization of critical data types and ineffective congestion detection. Traditional traffic-based methods are reactive, adjusting rates post-congestion, while resource-based methods can over-utilize network resources, impacting longevity. Hybrid methods partially address these concerns but lack robust prioritization mechanisms for multimedia data, which is essential for applications requiring real-time video and image transmission.
2. The BOCC protocol addresses these gaps by introducing a proactive congestion control method based on buffer occupancy metrics, which efficiently manages data transmission rates before severe congestion occurs. Unlike existing protocols, BOCC prioritizes high-priority I-frame packets over P-frame packets, ensuring essential multimedia data reaches its destination even under congested conditions. This strategy optimizes packet delivery by discarding lower-priority packets selectively, minimizing packet loss without exhausting network resources. Additionally, the use of convex optimization and Sequential Quadratic Programming (SQP) enables BOCC to dynamically adapt to network changes, enhancing packet delivery rates and reducing delays compared to traditional approaches. Above all, the key objectives achieved in this paper are listed below.

By addressing these points, we aim to clarify how the BOCC protocol fills these gaps and contributes to the field of congestion control in WMSNs

 

 

3. Expand the literature review to include more recent studies on congestion control protocols including the following ones: RoboFiSense: attention-based robotic arm activity recognition with WiFi sensing; Fuzing multiple erroneous sensors to estimate travel time; Developing an eco-driving strategy in a hybrid traffic network using reinforcement learning.

Response:

Response to Reviewer Comment 3:

Thank you for your valuable feedback regarding the expansion of the literature review. We have revised the literature review section to include the suggested recent studies related to congestion control protocols.

The following updates have been made:

1. RoboFiSense: We have added a discussion of "RoboFiSense," highlighting its innovative approach to activity recognition using WiFi sensing technology. This study underscores the potential for congestion control in scenarios where data from multiple sources, such as robotic arms, must be efficiently managed to maintain quality of service.
2. Fuzing Multiple Erroneous Sensors: The paper on fusing multiple erroneous sensors for travel time estimation has been incorporated to illustrate methods that can enhance data reliability and accuracy in congestion control scenarios. This research demonstrates techniques that can be leveraged to improve the robustness of congestion control protocols, including BOCC.
3. Eco-Driving Strategy Using Reinforcement Learning: We have included the study on developing eco-driving strategies in hybrid traffic networks using reinforcement learning, emphasizing its relevance to congestion management in WMSNs. The adaptive mechanisms discussed in this study can provide insights into how BOCC can be optimized for better performance in real-time applications.

The revised literature review highlighted in red color now reflects a broader scope of current research in congestion control and provides a stronger context for the development of the BOCC protocol.

We appreciate your suggestion to enhance the literature review, which has significantly improved the depth and relevance of our discussion.

 

4. I was wondering why the Raspberry Pi was chosen as the platform.

Response:

Thank you for your inquiry regarding the selection of Raspberry Pi as the platform for implementing the Buffer Occupancy Based Congestion Control (BOCC) protocol.

We chose Raspberry Pi for several reasons:

1. Cost-Effectiveness: Raspberry Pi is a low-cost computing platform, making it accessible for research and development purposes. This affordability allows for widespread experimentation and testing without substantial financial constraints.
2. Versatility: The Raspberry Pi supports various programming languages and development environments, making it adaptable for different applications. This versatility is particularly beneficial for implementing and testing the BOCC protocol in diverse scenarios.
3. Community Support: The extensive community support surrounding Raspberry Pi provides a wealth of resources, tutorials, and libraries that facilitate development. This support aids in troubleshooting and accelerates the implementation process.
4. Real-World Application: Raspberry Pi is widely used in educational and research settings for prototyping Internet of Things (IoT) applications. By using this platform, we aim to demonstrate the feasibility of BOCC in practical applications, paving the way for its potential deployment in real-world Wireless Multimedia Sensor Networks (WMSNs).
5. Performance Evaluation: The Raspberry Pi's performance capabilities, particularly in handling data transmission and processing tasks, align well with the requirements of our protocol. It allows us to effectively evaluate the performance improvements offered by BOCC under realistic operating conditions.

We appreciate your question, as it underscores the importance of platform choice in evaluating the effectiveness of the proposed protocol.

 

5. I was wondering how the performance of BOCC translates into real-world applications

Response to Reviewer

Thank you for your inquiry regarding the translation of the Buffer Occupancy Based Congestion Control (BOCC) protocol's performance into real-world applications.

The effectiveness of BOCC is particularly relevant in several practical scenarios, as outlined below:

1. Real-Time Video Streaming: In applications such as video surveillance or remote monitoring in smart cities, BOCC can significantly enhance the quality of service by effectively managing congestion, thereby reducing packet loss and latency. This ensures smoother video transmission and a better user experience.
2. Internet of Things (IoT) Integration: As IoT continues to expand, the ability of BOCC to scale with increasing device density becomes vital. By efficiently managing network traffic in WMSNs that comprise numerous interconnected devices, BOCC can support applications ranging from smart homes to connected vehicles, ensuring reliable data transmission and improved user experiences.

In summary, the performance improvements achieved through BOCC in managing congestion directly correlate with enhanced reliability and quality of service across various real-world applications, making it a valuable protocol for diverse operational contexts.

6. The conclusion should succinctly summarize the key findings and their significance without introducing new information.

Response

Thank you for your valuable feedback regarding the conclusion of our paper. We acknowledge the importance of providing a succinct summary of key findings without introducing new information. In the revised version, we have restructured the conclusion to clearly highlight the main outcomes of our research on the Buffer Occupancy Based Congestion Control (BOCC) protocol, emphasizing its significance in improving congestion management in Wireless Multimedia Sensor Networks (WMSNs).

Specifically, we have focused on the following points:

1. Summary of Key Findings: The revised conclusion now clearly articulates the main results of our experiments, including the effectiveness of BOCC in reducing packet loss and latency, and its potential impact on Quality of Service (QoS).
2. Significance of Findings: We have elaborated on the implications of these findings for real-world applications, illustrating how BOCC addresses congestion issues and enhances the performance of WMSNs in various scenarios.
3. Clear and Concise Language: The language used in the conclusion has been revised to ensure clarity and conciseness, avoiding any introduction of new information.

The updated conclusion is highlighted in red color in the paper that is given below:

The BOCC protocol effectively mitigates congestion in WMSNs by leveraging buffer occupancy metrics and change rates to adjust data transmission dynamically. With a feedback-based rate controller that prioritizes high-priority packets, BOCC ensures efficient video stream transmission even under congested conditions. Experimental results in a multi-hop, tree-topology WMSN environment with Raspberry Pi nodes demonstrate significant improvements in packet loss reduction and rate control over existing protocols. Further, optimization through convex programming and Sequential Quadratic Programming (SQP) enhances BOCC’s performance, with convex optimization providing faster convergence. Future work will explore BOCC’s adaptability to more diverse topologies and its integration with machine learning techniques to enhance congestion prediction and rate control. These advancements will further solidify BOCC as a scalable, efficient solution for dynamic WMSN environments.

 

We believe these adjustments enhance the clarity and impact of the conclusion, aligning it more closely with academic standards for summarizing research findings.

7. Study how BOCC can be combined with Internet of Things (IoT) frameworks, considering the increasing number of connected devices.

Response

Thank you for your insightful suggestion regarding the potential integration of the Buffer Occupancy Based Congestion Control (BOCC) protocol with Internet of Things (IoT) frameworks. We appreciate the relevance of this topic given the increasing number of connected devices in various applications.

In the revised manuscript, we have included a dedicated discussion on how BOCC can be effectively combined with IoT frameworks. Key points of this discussion are as follows:

1. Scalability: We outline how BOCC’s congestion control mechanisms can be adapted to manage the growing scale of IoT devices, focusing on its ability to dynamically allocate bandwidth and resources based on real-time traffic demands.
2. Interoperability: The discussion emphasizes the potential for BOCC to work seamlessly within diverse IoT ecosystems, facilitating communication between heterogeneous devices and ensuring that QoS is maintained across varying network conditions.
3. Application Scenarios: We present potential real-world application scenarios where BOCC could enhance IoT frameworks, such as smart cities, healthcare monitoring systems, and industrial automation. This section highlights how BOCC can improve data transmission efficiency and reliability in these contexts.
4. Future Work: We also suggest avenues for future research, including the exploration of adaptive algorithms that leverage machine learning techniques to optimize congestion control in IoT environments.

We believe that this addition not only addresses your comment but also enriches the manuscript by highlighting the broader implications of our research in the context of IoT.

 

8. Study the potential of machine learning for adaptive congestion control in WMSNs, enabling dynamic adjustments based on traffic patterns.

Response

Thank you for your valuable suggestion regarding the exploration of machine learning techniques for adaptive congestion control in Wireless Multimedia Sensor Networks (WMSNs). We recognize the importance of integrating advanced methodologies to enhance the performance of congestion control protocols.

In the revised manuscript, we have included a section dedicated to this topic. Key points discussed are as follows:

1. Overview of Machine Learning Applications: We provide an overview of how machine learning can be utilized for adaptive congestion control, focusing on the ability of algorithms to learn from historical traffic patterns and dynamically adjust the parameters of the Buffer Occupancy Based Congestion Control (BOCC) protocol.
2. Dynamic Traffic Adaptation: We discuss specific machine learning techniques, such as reinforcement learning and supervised learning, that can be employed to predict congestion scenarios based on real-time data. This would allow BOCC to proactively adjust its control strategies to optimize performance.
3. Potential Benefits: We highlight the potential benefits of incorporating machine learning, including improved responsiveness to fluctuating traffic loads, enhanced QoS, and reduced latency in data transmission.
4. Future Research Directions: Additionally, we outline potential research directions for integrating machine learning with BOCC, including the development of hybrid models that combine traditional control methods with machine learning approaches to achieve more robust congestion management.

We believe that this addition not only addresses your comment but also strengthens the manuscript by illustrating the forward-looking aspect of our research.

 

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

The presented article deals with the interesting topic of Buffer Occupancy Based Congestion Control Protocol for Wireless Multimedia Sensor Network. The work has scientific potential and additionally contains the results of the verification of the capabilities of the presented algorithm on a real device. However, the work contains a number of stylistic and methodological shortcomings, where the presentation of the work performed is very poor, difficult for the reader to follow and confusing. The resulting presentation of Algorithms 1 and 2 is not described in any more detail in the text and it is not explained that what was described in the given chapter is summarized in Algorithm 1 or 2. The work does not contain anything like that and it is purely up to the reader to orient himself, which I also find it inappropriate. All images are in raster format and in most places unnecessarily large, so they take up unnecessary space and provide almost no information. The graphs are also raster, and for some it is impossible to read what is written on the axes of the graph. Furthermore, the authors often refer to these images, but they are often under a completely different section, which makes it very difficult to understand and follow the entire text of the work. Figures 6, 7, 8 and 9 look like Excel clippings to me, which is completely inappropriate. For the NoBOCC member, you can see the highlighting below. Furthermore, there are a large number of abbreviations in the text, which are defined once with an uppercase letter in the text, then with a lowercase letter and are repeatedly stated in parentheses. This is very confusing and I recommend that the authors make a table describing all the abbreviations. It would greatly improve orientation and clarity. I perceive the way of referring to equations and pictures as another shortcoming, when sometimes they are with upper or lower case letters. If it is from, it should always be capitalized. Likewise, punctuation after equations (dot (.) and commas (,) is missing in most places).

But in order not to criticize, I find the overall content of the work interesting with scientific potential. The introductory section provides a nicely written intro to the topic. I believe that after the overall adjustment of the presentation, it could be a potentially interesting article. To increase the readability, clarity and overall presentation of the work, I suggest the following points to the authors:

1) Rework all images into vector format. And adjust their size to make sense. Text in images should be as large as the surrounding text.

2) Include a list of all abbreviations in the introductory chapter, for example in the form of a table.

3) Add keywords, the standard is about 10 keywords.

4) Unify abbreviations and list them only once and do not introduce them again in the text. Also, sometimes the first letters of words are capitalized and sometimes they are capitalized, why? Unite it and have it big everywhere.

5) In some places, the text contains unusual words that make it difficult to read (for example, stipulated). I would personally use more familiar synonyms for better readability.

6) Do not use not abbreviations in the text, i.e. rewrite doesn't to does not. Abbreviations are not used in scientific text.

7) Always move images below the place where there is the first reference to them.

8) The content of the article at the end of the first chapter does not correspond to the actual content. This should be fixed.

9) References to equations and figures should be capitalized.References to equations and figures should be capitalized.

10) Some of the images could be greatly reduced, especially the diagrams, Figure 2 over the entire page or Figure 5 do not make sense. Similarly, Pictures 1 and 4 could be done better.

11) The beginning of a new section should not be immediately followed by another subsection, but at least some text. For example, these are Sections 3 and 3.1 or 4 and 4.1.

12) Figures 3 and 4 are completely missing a reference in the text and are not explained as such. So why are they there in the first place?

13) The new sentence on line 188 begins with a lowercase letter.

14) On line 249, the end of the sentence is missing, there should probably be a colon (:).

15) Punctuation after equations is missing almost everywhere. If the sentence before it is preceded by a dot (:), then if the sentence continues after it, there must be a comma (,) after it, and if not, then a dot (.).

16) In Subsection 3.1 there is item 3. Packet Priority and Transmission Rate, here the index i=1,2,3,4 is introduced, but members 3 and 4 are not explained or used. Why?

17) If there are multiple brackets in the equations, the ones on the edge should be larger than the rest. For example, use \big in Latex.

18) Add description of Algorithm 1 and 2 and explain. Also, both algorithms have a slightly different writing style. Why? Personally, I would make them the same.

19) Rework the entire structure of the article, there are pictures in places where they don't make sense, there are empty spaces in the text and so on. The entire article needs to be reformatted so that it appears more coherent and clear.

20) On lines 366 and 373, the text begins with a mathematical symbol. This is not appropriate and it is better to start the sentence with for example "Parameter x..." or "Variable Y...".

21) On line 364 there is defined as and it is terminated by a dot (.), but it is followed by an equation, so there should be a colon (:).

22) On line 479 there is a reference to Figure 4.10. It is not clear what is meant by this and what it is supposed to refer to.

23) The upper limits of the sums m and p are not explained in Equation (22).

24) I don't understand chapter 4.4.2 where there are 3 lines of text and inserted Algorithm 2 without explanation.

25) In Equation 32, it is written that j does not belong to W_k, but why is that so? There is no explanation.

26) Abbreviations i.e. and similarly should be written in italics.

27) On line 418, a space is missing before W_0.

28) Rework examples and always give graphs for relevant examples. The current form is confusing and very difficult to understand.

29) Make your own chapter for Future Works and leave only a summary and evaluation of the entire article in the Conclusion.

 

Comments on the Quality of English Language

There are typographical errors throughout the article, and in places punctuation is missing or sentences end in the wrong way. I would also replace some of the terms used with more common synonyms to improve readability. Mathematical expressions also lack punctuation. That is why I recommend "Moderate editing of English language required".

Author Response

Dear Reviewer,

We are very grateful to you for giving us an opportunity to revise our manuscript. We appreciate you and the respected reviewers for their constructive comments and suggestions on our manuscript entitled “Buffer Occupancy Based Congestion Control (BOCC) for Wireless Multimedia Sensor Networks (WMSNs)”. Based on these comments and suggestions, we have made careful modifications on the original manuscript. The comments of reviewers are in italic, while our response in plain text. The modified texts in the manuscript are in red font to highlight the changes made for quick review. We are very grateful to the reviewer for their time and valuable comments. The comments are very helpful to further enhance our manuscript.

 

 

 

 

Point-by-point response

 

The presented article deals with the interesting topic of Buffer Occupancy Based Congestion Control Protocol for Wireless Multimedia Sensor Network. The work has scientific potential and additionally contains the results of the verification of the capabilities of the presented algorithm on a real device. However, the work contains a number of stylistic and methodological shortcomings, where the presentation of the work performed is very poor, difficult for the reader to follow and confusing. The resulting presentation of Algorithms 1 and 2 is not described in any more detail in the text and it is not explained that what was described in the given chapter is summarized in Algorithm 1 or 2. The work does not contain anything like that and it is purely up to the reader to orient himself, which I also find it inappropriate. All images are in raster format and in most places unnecessarily large, so they take up unnecessary space and provide almost no information. The graphs are also raster, and for some it is impossible to read what is written on the axes of the graph. Furthermore, the authors often refer to these images, but they are often under a completely different section, which makes it very difficult to understand and follow the entire text of the work. Figures 6, 7, 8 and 9 look like Excel clippings to me, which is completely inappropriate. For the NoBOCC member, you can see the highlighting below. Furthermore, there are a large number of abbreviations in the text, which are defined once with an uppercase letter in the text, then with a lowercase letter and are repeatedly stated in parentheses. This is very confusing and I recommend that the authors make a table describing all the abbreviations. It would greatly improve orientation and clarity. I perceive the way of referring to equations and pictures as another shortcoming, when sometimes they are with upper or lower case letters. If it is from, it should always be capitalized. Likewise, punctuation after equations (dot (.) and commas (,) is missing in most places).

But in order not to criticize, I find the overall content of the work interesting with scientific potential. The introductory section provides a nicely written intro to the topic. I believe that after the overall adjustment of the presentation, it could be a potentially interesting article. To increase the readability, clarity and overall presentation of the work, I suggest the following points to the authors:

Response:

We would like to thank the reviewer for his thorough evaluation of our manuscript titled "Buffer Occupancy Based Congestion Control Protocol for Wireless Multimedia Sensor Network." We appreciate the positive feedback regarding the scientific potential of our work and the introductory section. Below, we address the specific points raised by the reviewer and outline the changes made to improve the clarity, readability, and overall presentation of our article.

1) Rework all images into vector format. And adjust their size to make sense. Text in images should be as large as the surrounding text.

Response:

Thank you for your valuable feedback. I have addressed your concerns as follows:

1. Vector Format Conversion: All images in the manuscript have been converted to vector format, ensuring high quality and scalability. This enhances their clarity and precision, especially when zoomed in or resized.
2. Adjusted Image Size: The sizes of the images have been adjusted to fit the layout appropriately. This ensures that they complement the content without disrupting the flow of the text.
3. Consistent Text Size: The text within the images has been resized to match the font size of the surrounding manuscript text. This ensures uniformity and readability throughout the document.

We appreciate your detailed suggestions and hope that these changes enhance the overall quality of the paper.

 

2) Include a list of all abbreviations in the introductory chapter, for example in the form of a table.

Thank you for the suggestion. We have added a comprehensive list of all abbreviations used in the manuscript. This list is now included in the introductory chapter, presented in the form of a table for clarity and easy reference.

Abbreviation	Definition
WMSN	Wireless Multimedia Sensor Network
BOCC	Buffer Occupancy-Based Congestion Control
QoS	Quality of Service
PSNR	Peak Signal-to-Noise Ratio
SQP	Sequential Quadratic Programming
CMOS	Complementary Metal-Oxide Semiconductor
MEMS	Micro Electro-Mechanical Systems
PPI	Priority Packet Index
ECODA	Enhanced Congestion Detection and Avoidance
TARA	Topology-Aware Resource Adaptation
TMR	Time Delay-Based Multipath Routing
HRTC	Hybrid Resource and Traffic Control
HTAP	Hierarchical Tree Alternative Path
SLEB	Secure Load-Balanced Scheme
DHSSRP	Dynamic Hop Selection Static Routing Protocol
HOCA	Healthcare Aware Optimized Congestion Avoidance
CADA	Congestion-Aware Data Acquisition
ESRT	Event-to-Sink Reliable Transport
AWF	Adaptive Weight Firefly
NACK	Negative Acknowledgment

 

 

3) Add keywords, the standard is about 10 keywords.

Response:

Thank you for your suggestion. I have now added 10 relevant keywords to the manuscript, ensuring they reflect the core concepts and topics of the paper.

Following is the updated Keyword list.

Congestion control; Wireless multimedia sensor networks; wireless sensor networks; video transmission; IoT; Buffer Occupancy; QoS; Optimization; Sequential Quadratic Programming; Convex Optimization;

 

4) Unify abbreviations and list them only once and do not introduce them again in the text. Also, sometimes the first letters of words are capitalized and sometimes they are capitalized, why? Unite it and have it big everywhere.

Response:
Thank you for pointing this out. I have revised the manuscript as follows:

1. Unified Abbreviations: All abbreviations have been introduced only once at their first occurrence. Thereafter, the abbreviations are used consistently throughout the text without being reintroduced.
2. Standardized Capitalization: We have reviewed and corrected any inconsistencies in the capitalization of terms. Now, all terms, including abbreviations, follow a consistent format, with the appropriate capitalization applied uniformly across the manuscript.

 

5) In some places, the text contains unusual words that make it difficult to read (for example, stipulated). I would personally use more familiar synonyms for better readability.

Response

Thank you for your valuable feedback. I have carefully reviewed the manuscript and replaced less familiar or complex terms with simpler and more widely understood synonyms. This adjustment should enhance the overall readability of the paper without compromising its technical precision.

6) Do not use not abbreviations in the text, i.e. rewrite doesn't to does not. Abbreviations are not used in scientific text.

Response:
Thank you for your observation. I have revised the manuscript to remove all contractions and replaced them with their full forms (e.g., "doesn't" changed to "does not"). This ensures that the text adheres to formal scientific writing standards.

7) Always move images below the place where there is the first reference to them.

Response:
Thank you for your suggestion. I have repositioned all images in the manuscript to ensure they appear immediately after their first mention in the text. This adjustment improves the logical flow and makes it easier for readers to follow the discussion and the corresponding figures.

8) The content of the article at the end of the first chapter does not correspond to the actual content. This should be fixed.

Response:
Thank you for bringing this to my attention. I have carefully revised the summary at the end of the first chapter to ensure it accurately reflects the actual content of the manuscript. The updated section now provides a clear and concise overview of the material covered in the subsequent chapters, maintaining consistency with the overall structure of the paper.

9) References to equations and figures should be capitalized. References to equations and figures should be capitalized.

Response:
Thank you for your suggestion. I have reviewed and revised the manuscript to ensure that all references to equations and figures are now capitalized (e.g., "Equation 1" and "Figure 2"). This adjustment maintains consistency with the standard formatting conventions.

10) Some of the images could be greatly reduced, especially the diagrams, Figure 2 over the entire page or Figure 5 do not make sense. Similarly, Pictures 1 and 4 could be done better.

Response:
Thank you for your feedback. I have revised the manuscript as follows:

1. Image Size Adjustments: The sizes of Figures 2 and 5 have been reduced to fit the content better without taking up unnecessary space. This makes the layout more concise and readable.
2. Improved Quality: Pictures 1 and 4 have been enhanced to improve clarity and presentation. These revisions ensure that the diagrams and images are both visually appealing and functionally appropriate for the context.

 

11) The beginning of a new section should not be immediately followed by another subsection, but at least some text. For example, these are Sections 3 and 3.1 or 4 and 4.1.

Response:
Thank you for your observation. I have revised the manuscript to ensure that each new section is followed by some introductory text before proceeding to the subsections. This improves the flow of the paper and provides context for the reader. For example, I have added brief explanations or transitions between Sections 3 and 3.1, as well as between Sections 4 and 4.1.

 

12) Figures 3 and 4 are completely missing a reference in the text and are not explained as such. So why are they there in the first place?

Response:
Thank you for bringing this to my attention. I have reviewed the manuscript and made the following changes:

1. Incorporated References: I have added references to Figures 3 and 4 in the text, explaining their relevance and significance to the discussion. This clarification provides context for the reader and integrates these figures into the overall narrative of the paper.
2. Provided Explanations: I have included brief explanations of what Figures 3 and 4 depict and their importance to the research. This ensures that their inclusion is justified and enhances the reader's understanding.

 

13) The new sentence on line 188 begins with a lowercase letter.

 

Response:
Thank you for your careful review. I have corrected the formatting issue on line 188 by ensuring that the new sentence begins with an uppercase letter. This correction improves the grammatical accuracy of the manuscript.

14) On line 249, the end of the sentence is missing, there should probably be a colon (:).

Response:
Thank you for pointing out this oversight. I have reviewed line 249 and added a colon to complete the sentence appropriately. This correction clarifies the intended meaning and enhances the grammatical structure of the manuscript.

15) Punctuation after equations is missing almost everywhere. If the sentence before it is preceded by a dot (:), then if the sentence continues after it, there must be a comma (,) after it, and if not, then a dot (.).

Response:
Thank you for your observation regarding punctuation after equations. I have thoroughly reviewed the manuscript and made the following adjustments:

1. Corrected Punctuation: I have ensured that all equations are followed by appropriate punctuation. Specifically, I added commas after equations when the preceding sentence continues, and periods when the equation ends the sentence.
2. Consistent Formatting: This correction provides clarity and maintains a consistent style throughout the manuscript, adhering to proper grammatical standards.

16) In Subsection 3.1 there is item 3. Packet Priority and Transmission Rate, here the index i=1,2,3,4 is introduced, but members 3 and 4 are not explained or used. Why?

Response:
Thank you for your careful review of Subsection 3.1. an identifying the typo mistake. The i ∈ {1,2}.

 

17) If there are multiple brackets in the equations, the ones on the edge should be larger than the rest. For example, use \big in Latex.

Response:
Thank you for your insightful feedback. I have revised the equations in the manuscript to ensure that any multiple brackets are formatted correctly. Specifically, I have utilized the \big command in LaTeX to enlarge the outer brackets, enhancing the clarity and readability of the equations.

 

18) Add description of Algorithm 1 and 2 and explain. Also, both algorithms have a slightly different writing style. Why? Personally, I would make them the same.

Response:
Thank you for your valuable feedback. I have made the following revisions to address your comments:

1. Added Descriptions: I have included detailed descriptions for both Algorithm 1 and Algorithm 2, explaining their purpose, functionality, and significance in the context of the manuscript. This additional information provides clarity for the reader and enhances the understanding of the algorithms.
2. Unified Writing Style: I have reviewed both algorithms and standardized their writing style to ensure consistency throughout the manuscript. This includes harmonizing the terminology, formatting, and overall presentation of the algorithms.

 

19) Rework the entire structure of the article, there are pictures in places where they don't make sense, there are empty spaces in the text and so on. The entire article needs to be reformatted so that it appears more coherent and clear.

Response:
Thank you for your constructive feedback. I appreciate your suggestions regarding the article's structure. I have undertaken a thorough revision of the manuscript with the following changes:

1. Reorganized Structure: I have restructured the article to improve the logical flow and coherence of the content. This includes rearranging sections and subsections to ensure that ideas build upon each other effectively.
2. Improved Placement of Figures: I have reviewed the placement of all figures and images, ensuring that they are located in contextually appropriate sections and provide clear support for the surrounding text.
3. Addressed Empty Spaces: I have eliminated unnecessary empty spaces in the text to enhance readability and create a more professional presentation.
4. General Reformatting: Overall formatting has been standardized to ensure consistency in style, font, headings, and spacing throughout the manuscript.

 

 

20) On lines 366 and 373, the text begins with a mathematical symbol. This is not appropriate and it is better to start the sentence with for example "Parameter x..." or "Variable Y...".

Response:
Thank you for your observation regarding the beginning of the sentences on lines 366 and 373. I have revised these lines to ensure that they begin with descriptive phrases rather than mathematical symbols. Specifically, I have rephrased the sentences to start with "Parameter x..." and "Variable y...", which improves clarity and maintains a formal tone.

21) On line 364 there is defined as and it is terminated by a dot (.), but it is followed by an equation, so there should be a colon (:).

Response:
Thank you for pointing out this punctuation error. I have corrected the sentence on line 364 by replacing the period with a colon. This adjustment ensures that the statement correctly introduces the following equation and adheres to proper grammatical conventions.

 

22) On line 479 there is a reference to Figure 4.10. It is not clear what is meant by this and what it is supposed to refer to.

Response:
Thank you for your feedback regarding the reference to Figure 4.10. It was the typo mistake and actual is Figure 8. I have revised the text on line 479 to provide clearer context and explanation for the figure. Specifically, I have added a brief description of what Figure 8. illustrates and how it relates to the surrounding content. This enhancement improves clarity for the reader and ensures that the reference is meaningful.

 

23) The upper limits of the sums m and p are not explained in Equation (22).

Response:
Thank you for highlighting this oversight. I have added an explanation for the upper limits of the sums mmm and ppp in Equation (22). This additional information clarifies their significance and provides context for their use in the equation, ensuring that the reader understands their roles within the mathematical formulation.

In Equation (22) of the Sequential Quadratic Programming (SQP) method, the upper limits m and p represent the number of equality and inequality constraints, respectively:

• m is the number of equality constraints ci(x)=0
• p is the number of inequality constraints gj(x)≤0.

These indices help define how many constraints are considered in the optimization problem, which is essential for ensuring that both types of constraints are accounted for in each iteration of the SQP method.

24) I don't understand chapter 4.4.2 where there are 3 lines of text and inserted Algorithm 2 without explanation.

Response:
Thank you for your feedback regarding Chapter 4.4.2. I appreciate your concern about the lack of context surrounding Algorithm 2. I have revised this section by adding a more comprehensive explanation that outlines the purpose and relevance of Algorithm 2 in relation to the preceding content. This added context will help clarify its application and significance for the reader.

“The Active-Set Method iteratively identifies and solves a sequence of equality-constrained subproblems by adjusting the set of active constraints. This approach ensures that each iteration considers only the constraints actively influencing the current solution. Convergence occurs when the optimal solution meets the Karush-Kuhn-Tucker (KKT) conditions, ensuring that both the objective function and constraints are satisfied”.

 

25) In Equation 32, it is written that j does not belong to W_k, but why is that so? There is no explanation.

Response:
In Equation (32), it is specified that j∉Wk ​ because the Active-Set Method only considers inequality constraints that are not currently part of the working set WkW_kWk​ when determining the step length.

Here's the reasoning:

1. Active Set: At each iteration k, the working set Wk ​ contains the constraints that are currently "active" or binding at the current solution (i.e., they are either equality constraints or inequality constraints that are satisfied exactly, meaning they lie on the boundary of feasibility).
2. Step Length and Non-Active Constraints: When computing the step length αk, the algorithm checks which inequality constraints (not currently in Wk) would become active if the step length were increased. This ensures the next iterate remains feasible.
3. Avoiding Violations: The term j∉W ensures that we only consider constraints not already in Wk to prevent the step from violating any of these "inactive" inequalities. When a step size would violate a new inequality constraint, that constraint is added to the working set in the next iteration.

 

26) Abbreviations i.e. and similarly should be written in italics.

Response:
Thank you for your suggestion regarding the formatting of abbreviations. I have revised the manuscript to ensure that "i.e." and "similarly" are written in italics wherever they appear. This change enhances the visual consistency of the text and adheres to proper formatting standards.

27) On line 418, a space is missing before W_0.

Response:
Thank you for your attention to detail. I have corrected the formatting issue on line 418 by adding the necessary space before W₀​. This adjustment improves the overall readability of the text.

28) Rework examples and always give graphs for relevant examples. The current form is confusing and very difficult to understand.

Response:
Thank you for your constructive feedback regarding the examples in the manuscript. I have undertaken the following revisions:

1. Reworked Examples: I have revised the examples to enhance clarity and coherence, ensuring that they are presented in a more logical and understandable format.
2. Added Graphs: For each relevant example, I have included graphs that visually represent the concepts being discussed. These graphical representations aim to clarify the data and make the examples easier to comprehend.

 

29) Make your own chapter for Future Works and leave only a summary and evaluation of the entire article in the Conclusion.

 

Response:
Thank you for your suggestion to improve the structure of the manuscript. I have made the following revisions:

Thank you for your valuable feedback. We have carefully considered your suggestion to create a separate Future Works section. In the current manuscript, we have included the future directions within the Conclusion section to maintain the flow of the document. We believe this approach provides a cohesive summary while highlighting potential areas for further research.

 

 

 

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

1. The explanations for Figures 1 and 2 are implicit, and both figures appear to contain only minimal informative content. Specifically, Figure 2 illustrates a tree-based topology to highlight extreme congestion scenarios caused by bottlenecks. In contrast, Figure 1 is intended to represent the general scenario for wireless multimedia sensor networks. However, the topologies depicted in the two figures do not align, making the motivations and considered scenarios unclear. It would be beneficial to combine the two figures into one cohesive illustration, with explicit explanations of the scenarios under consideration.

2. While the authors categorize the congestion control algorithms into three approaches, the related works are merely listed without offering any insights from the authors themselves. A discussion of the advantages and disadvantages of each approach, as well as the relationship between the categorized algorithms and the proposed method, would add value to the analysis.

3. The reviewer has a minor question. B(t) and Bprev(t) are defined as the buffer occupancy at time t and at the previous time slot, t - Δt, respectively. The reviewer is curious about why Bprev(t) is used instead of B(t - Δt). Additionally, what does the index n in Sn(t) represent?

4. The normal state is described as the condition when the buffer occupancy is lower than in the slow state. The reviewer has concerns about whether the definition is correctly described as intended by the authors.

5. According to the current representation of congestion levels, it appears that the congestion level is determined at each time slot. In the reviewer’s view, this approach may result in instability when frequent changes in buffer states occur, such as transitioning from the normal state at t=1, to the slow state at t=2, and to the urgent state at t=3, and so on. This fluctuating environment could impose significant overhead on congestion control mechanisms. Has the use of averaging techniques been considered by the authors to stabilize performance?

6. Related to the previous question, how is the predefined threshold rate of change determined?

7. Packet priority levels Pi are defined for i ∈ {1, 2, 3, 4}, where P1 and P2 correspond to the priority levels of I-frames and P-frames, respectively. What do P3 and P4 represent?

8. The feedback mechanism requires more explicit clarification, as the current description is ambiguous. According to equation (3), the unit of feedback F(t) should be a data rate, and the function f( ) is intended to adjust the data rate based on the buffer occupancy of the parent node. However, these definitions are unclear, and the authors should provide further clarification. Additionally, the described model suggests that each node has a single parent node, as illustrated in Figure 2. The authors should clarify the considered scenario and its relevance to real-world applications.

9. The optimization problem described in equations (5), (6), and (7) requires further explanation. It seems to be formulated for a single i regarding a single frame type. It is also designed for a single transmission. What is the controllable parameter in this context? Why is the objective function designed as it is in equation (5)?

10. The optimization problem appears overly simplified and lacks sufficient detail. As a result, the reviewer has significant concerns regarding the rationale behind the proposed solutions and their corresponding results.

 

Author Response

Dear Reviewer,

We are very grateful to you for giving us an opportunity to revise our manuscript. We appreciate you and the respected reviewers for their constructive comments and suggestions on our manuscript entitled “Buffer Occupancy Based Congestion Control (BOCC) for Wireless Multimedia Sensor Networks (WMSNs)”. Based on these comments and suggestions, we have made careful modifications on the original manuscript. The comments of reviewers are in italic, while our response in plain text. The modified texts in the manuscript are in red font to highlight the changes made for quick review. We are very grateful to the reviewer for their time and valuable comments. The comments are very helpful to further enhance our manuscript.

 

 

Point-by-point response

 

We appreciate your insightful feedback regarding the figures presented in our manuscript. In response to your comments, we have decided to delete Figure 1 and retain only Figure 2.

Figure 2 has been refined to better illustrate the tree-based topology that highlights extreme congestion scenarios caused by bottlenecks in wireless multimedia sensor networks. We have ensured that the figure now includes explicit explanations of the scenarios under consideration, providing clearer context and enhancing the overall informative content.

By focusing solely on Figure 2, we aim to present a more coherent and focused depiction of the congestion issues relevant to our study. We believe this change strengthens the clarity of our findings and improves the overall quality of the manuscript.

Response:

 

2. While the authors categorize the congestion control algorithms into three approaches, the related works are merely listed without offering any insights from the authors themselves. A discussion of the advantages and disadvantages of each approach, as well as the relationship between the categorized algorithms and the proposed method, would add value to the analysis.

 

Response:

Thank you for the insightful suggestion. To address this, we have expanded the related works section to provide a comparative discussion of the advantages and disadvantages of each congestion control approach. Additionally, we have clarified how these approaches relate to our proposed BOCC protocol, allowing readers to better understand the positioning and contributions of our method within the existing landscape.

“Traffic-based congestion control protocols, such as the adaptive weight firefly (AWF) algorithm, effectively manage congestion by dynamically adjusting transmission rates in response to congestion signals. These approaches are advantageous in networks with predictable traffic loads, as they offer efficient and straightforward adjustments. However, their primary limitation lies in their sensitivity to fluctuating network loads, which can lead to unpredictable delays and packet losses—issues particularly prominent in multimedia sensor networks where data is bursty and bandwidth demands are high. Some traffic-based protocols may also introduce additional delay and complexity through frequent feedback adjustments. While the BOCC protocol similarly adjusts transmission rates in response to network conditions, it employs buffer occupancy and buffer occupancy change rate as proactive indicators. This approach allows BOCC to detect and respond to congestion more swiftly, avoiding excessive rate changes and maintaining better Quality of Service (QoS) for multimedia data transmission.

Resource-based congestion control protocols, on the other hand, excel in scenarios requiring high reliability and minimal delay by leveraging alternative paths or idle network resources to balance data flow. Hierarchical protocols, such as the HTAP algorithm, achieve effective load balancing by dispersing traffic, which helps in reducing congestion. However, these approaches can be resource-intensive, often requiring additional paths or nodes, which can lead to increased energy consumption and overhead. Furthermore, in dynamic WMSNs with limited nodes, creating alternative paths may be challenging, making these protocols less feasible. The BOCC protocol, by contrast, relies on feedback-based rate control rather than alternative routing, conserving energy in multi-hop networks. By adjusting rates based on buffer levels, BOCC avoids the need for complex routing changes, making it both energy-efficient and simpler to implement.

Hybrid congestion control protocols integrate traffic and resource management techniques to provide adaptive solutions tailored to network requirements. For instance, the healthcare-aware HOCA protocol optimizes data transmission by adjusting rates based on data sensitivity, which is highly suitable for WMSNs prioritizing specific data types such as video. However, these protocols often come with high computational overhead due to the need for both traffic and resource awareness, which can add significant complexity. Additionally, managing the balance between traffic and resource adjustments can introduce trade-offs between latency and throughput, potentially affecting performance in high-load scenarios. While BOCC shares some hybrid characteristics by incorporating adaptive traffic control based on congestion indicators, it avoids the extensive resource manipulation seen in hybrid approaches. BOCC’s design focuses on energy efficiency, high video quality, and prioritization of I-frames without the complexities of multi-resource management, making it particularly well-suited for the demands of WMSNs.”

3. The reviewer has a minor question. B(t) and Bprev(t) are defined as the buffer occupancy at time t and at the previous time slot, t - Δt, respectively. The reviewer is curious about why Bprev(t) is used instead of B(t - Δt). Additionally, what does the index n in Sn(t) represent?

 

Response

Thank you for the insightful questions The description of the notation is also available in section 3.2 highlighted in red color. I will clarify both points as follows:

Use of B_prev(t) instead of B(t−Δt): In our notation, B_prev(t) is used to denote the buffer occupancy from the prior time slot. Conceptually, B_prev(t) and B(t−Δt) represent the same value—the buffer occupancy at the previous time step. The choice of B_prev(t) over B(t−Δt) was primarily for notational simplicity and consistency, allowing us to maintain a clear differentiation between the current buffer occupancy and the previous occupancy within the same time frame. This notation also emphasizes that the previous occupancy value is a parameter influencing the current state B(t), aligning well with the stepwise approach in our congestion control model.

The Index n in Sn(t): The index n in Sn(t) specifies the node within the network to which the transmission rate S(t) belongs. In wireless multimedia sensor networks (WMSNs), each sensor node typically has its own buffer and transmission characteristics. By indexing the transmission rate with n, we can track and control the transmission rate of each individual node, allowing for node-specific adjustments to better manage congestion across the network as a whole. This granularity in indexing also facilitates the BOCC protocol’s ability to make independent rate adjustments for each node based on localized buffer occupancy and feedback.

 

 

4. The normal state is described as the condition when the buffer occupancy is lower than in the slow state. The reviewer has concerns about whether the definition is correctly described as intended by the authors.

 

Thank you for highlighting this concern. We recognize the importance of precisely defining the states to ensure clarity.

In the BOCC protocol, the normal state is defined based on both buffer occupancy and the rate of change in buffer occupancy. Specifically, the normal state occurs when the buffer occupancy B(t)B(t)B(t) is within a lower range and does not indicate impending congestion. This is formally described as:

• Normal State: 0≤B(t)≤B₁ and δ(t)≤ρ, where B₁ is a predefined threshold indicating low buffer occupancy, and δ(t) is the rate of change in buffer occupancy. The threshold ρ represents a rate of change boundary, beyond which buffer occupancy increases more rapidly, signaling a transition toward congestion.

In contrast, the slow state begins when buffer occupancy surpasses the B1B_1B1​ threshold, and the rate of change δ(t) exceeds ρ, indicating that the buffer is filling at a faster rate and may soon experience congestion if corrective actions are not taken.

Thus, the normal state does not merely signify "lower than slow state" occupancy; rather, it denotes a specific operational range where both occupancy and its change rate are low, allowing smooth network performance. This distinction ensures that each state in the BOCC protocol is triggered based on buffer usage and the dynamics of occupancy growth, aligning with our intended definition and operational objectives.

 

5. According to the current representation of congestion levels, it appears that the congestion level is determined at each time slot. In the reviewer’s view, this approach may result in instability when frequent changes in buffer states occur, such as transitioning from the normal state at t=1, to the slow state at t=2, and to the urgent state at t=3, and so on. This fluctuating environment could impose significant overhead on congestion control mechanisms. Has the use of averaging techniques been considered by the authors to stabilize performance?

Thank you for this insightful observation. We appreciate the reviewer’s concern regarding potential fluctuations in buffer states, which could indeed lead to instability and increased overhead in the congestion control mechanism.

To address this, we acknowledge that abrupt state transitions can lead to frequent adjustments in the data transmission rate, potentially overloading the network control mechanism and reducing system stability. To mitigate this, we have considered incorporating averaging techniques for buffer occupancy over a short moving window. By doing so, we aim to smooth out transient fluctuations and prevent rapid oscillations between congestion states.

Specifically, an exponential moving average (EMA) or a simple moving average (SMA) could be applied to buffer occupancy values over recent time slots. This approach would involve calculating an averaged buffer occupancy B_avg(t) as follows:

B_avg​(t)=α⋅B(t)+(1−α)⋅B_avg​(t−1)

where α is a smoothing factor (typically between 0.1 and 0.3), chosen based on network dynamics. B_avg(t) would then be used in place of instantaneous B(t) for determining congestion states. This effectively filters out short-term fluctuations, ensuring that congestion control responses are triggered by sustained changes rather than momentary spikes.

The use of averaging would stabilize the BOCC protocol, reduce the frequency of congestion notifications, and minimize unnecessary rate adjustments. This approach enhances system robustness by providing a smoother congestion response, aligning with our goal of maintaining consistent QoS while efficiently managing network resources.

 

6. Related to the previous question, how is the predefined threshold rate of change determined?

 

The predefined threshold rate of change, denoted as ρ, is a critical parameter in the BOCC protocol as it determines when the buffer occupancy growth rate signals a transition between congestion states. Setting an effective ρ value is essential to balance responsiveness with stability.

To determine ρ, we consider both empirical analysis and network requirements. This process typically involves the following steps:

1. Empirical Calibration: During the initial protocol testing phase, ρ is calibrated by analyzing network simulations under various traffic conditions. These simulations help to observe typical rates of buffer occupancy growth during normal and congested states. By analyzing buffer behavior across different traffic loads, an optimal threshold range for ρ can be identified.
2. QoS and Latency Requirements: The value of ρ is also influenced by the specific QoS and latency requirements of the WMSN application. For applications sensitive to delays or packet losses, a lower ρ may be chosen to trigger congestion control more aggressively. Conversely, applications that can tolerate minor delays may use a higher ρ to prevent unnecessary rate adjustments in response to transient changes in buffer occupancy.
3. Adaptation through Feedback: Additionally, we propose an adaptive approach where ρ can be dynamically adjusted based on network feedback. If the network experiences frequent but unnecessary congestion triggers, ρ can be increased incrementally. Similarly, if congestion frequently escalates without timely intervention, ρ can be decreased to improve responsiveness.

 

 

7. Packet priority levels Pi are defined for i ∈ {1, 2, 3, 4}, where P1 and P2 correspond to the priority levels of I-frames and P-frames, respectively. What do P3 and P4 represent?

Thank you for identifying the typo mistake. It is actually i ∈ {1, 2}. It is corrected in the manuscript.

8. The feedback mechanism requires more explicit clarification, as the current description is ambiguous. According to equation (3), the unit of feedback F(t) should be a data rate, and the function f( ) is intended to adjust the data rate based on the buffer occupancy of the parent node. However, these definitions are unclear, and the authors should provide further clarification. Additionally, the described model suggests that each node has a single parent node, as illustrated in Figure 2. The authors should clarify the considered scenario and its relevance to real-world applications.

 

 

Thank you for these observations. We agree that providing additional clarification on the feedback mechanism, including the function f(⋅), the units involved, and the network model, will improve the reader’s understanding.

1. Clarification of the Feedback Mechanism and Function f(⋅): In the BOCC protocol, each node adjusts its transmission rate Sn(t) based on the feedback F(t), which reflects the buffer occupancy status of its parent node. The primary aim of f(⋅) is to convert the parent node's buffer occupancy into a suitable feedback value that can modulate the child node's data transmission rate. We define f(B_parent(t)) as a function that maps the parent node’s buffer occupancy B_parent(t) to a value between 0 and 1, indicating the level of congestion experienced by the parent node.
   • Unit of Feedback F(t): Since F(t) is used to adjust the transmission rate, its unit is effectively a multiplier rather than a direct rate. This multiplier is applied to the normal transmission rate S_n(t), reducing it in proportion to the parent node’s buffer occupancy. The adjusted transmission rate is given by:

S_n​(t)=S_n​(t)⋅(1−F(t))

where F(t)=f(B_parent(t)) and f(B_parent(t)) represents the level of congestion at the parent node. A high B_parent(t) will result in a higher F(t), which in turn reduces S_n(t) to prevent further congestion.

 

Definition and Role of f(⋅): The function f(⋅)can be defined as a piecewise linear or sigmoid function that increases with B_parent(t). This function might look as follows:

Here, B_low and B_high are predefined thresholds indicating buffer levels where congestion control should begin (for moderate buffer occupancy) and where it should be maximized (at high buffer occupancy), respectively. This mapping allows for a gradual adjustment of Sn(t) based on how full the parent node’s buffer is.

Single-Parent Node Model and Real-World Applicability: The BOCC protocol assumes a tree-like structure, where each node communicates with a single designated parent node, as illustrated in Figure 1. This model is relevant in applications with hierarchical or cluster-based WMSNs, such as surveillance or environmental monitoring, where sensor nodes report data to a central sink or gateway via intermediate parent nodes. In many real-world WMSNs, especially in multi-hop networks, data flows up a tree-like structure to reduce redundancy and energy use, making the single-parent assumption both practical and efficient.

By clearly defining f(⋅)f(\cdot)f(⋅) and the feedback mechanism, we aim to enhance the protocol’s clarity and show how BOCC’s congestion control adapts to real-world WMSN topologies that rely on hierarchical data flows.

 

 

 

9. The optimization problem described in equations (5), (6), and (7) requires further explanation. It seems to be formulated for a single i regarding a single frame type. It is also designed for a single transmission. What is the controllable parameter in this context? Why is the objective function designed as it is in equation (5)?

Thank you for highlighting this important point. The optimization problem presented in equations (5), (6), and (7) is indeed intended to control congestion at each node by optimizing the data transmission rate, specifically for high-priority packets, to maintain video quality. Let us clarify the problem formulation and its components in more detail:

1. Optimization Context and Controllable Parameter: The primary controllable parameter in this context is the transmission rate S_n(t) for each node n at a given time t. This transmission rate is adjusted based on real-time feedback from congestion levels at the node itself and from its parent node. By controlling S_n(t), the BOCC protocol can prioritize high-quality video frames (I-frames) while managing congestion to avoid buffer overflow and packet loss.
2. Objective Function in Equation (5): Equation (5) is designed to minimize a combination of the packet drop probability P_drop(t) and the rate of change of buffer occupancy δ(t). The rationale for this design is as follows:
   • Minimizing Packet Drop Probability: P_drop(t) represents the likelihood of packets being discarded due to buffer overflow. Minimizing P_drop(t) is essential for maintaining high-quality multimedia transmission, as packet drops, particularly for I-frames, can degrade video quality significantly. The weight P_i ​ in the term P_drop(t) reflects the priority of each packet, emphasizing high-priority frames in the optimization.
   • Minimizing Buffer Occupancy Change Rate: The term λ⋅δ(t) in the objective function penalizes rapid increases in buffer occupancy, which are indicative of potential congestion. By including this term, the optimization process encourages a steady flow of data rather than abrupt surges, thus stabilizing the buffer and preventing sudden congestion events.

Together, these two components aim to balance the quality of service (QoS) for multimedia transmission with network stability. The weights P_i ​ and λ allow the network to prioritize packet delivery and video quality while controlling buffer fluctuations.

3. Scope of Optimization Problem (Single Frame and Transmission): The formulation in equations (5), (6), and (7) is initially presented for a single node n and a single time slot ttt as a baseline, focusing on controlling one high-priority frame type, typically an I-frame, which has the most significant impact on video quality. In a practical implementation, this single transmission model serves as a foundation for continuous adjustment of S_n(t) over multiple frames and time slots, adapting dynamically as network conditions change.

For a broader application, this single-instance formulation can be expanded to handle multiple nodes and frame types by applying the optimization iteratively for each time slot and adjusting S_n(t) for each node based on its local congestion feedback.

4. Justification of Constraints in Equations (6) and (7):
   • Transmission Rate Constraint 0≤S_n(t)≤S_normal: This constraint ensures that the transmission rate stays within a feasible range, bounded by a normal transmission rate S_normal ​, preventing the rate from either dropping to zero or excessively increasing.
   • Buffer Capacity Constraint 0≤B(t)≤B_max: This constraint maintains buffer occupancy within capacity limits, avoiding overflow. By keeping B(t)≤B_max, the optimization process ensures that packets are not dropped due to excessive buffering.

 

10. The optimization problem appears overly simplified and lacks sufficient detail. As a result, the reviewer has significant concerns regarding the rationale behind the proposed solutions and their corresponding results.

We appreciate the reviewer's feedback and would like to provide a more detailed rationale for our optimization model, demonstrating its suitability for the BOCC protocol's objectives.

1. Rationale for the Optimization Model: Our model is purposefully designed to address congestion in Wireless Multimedia Sensor Networks (WMSNs) by optimizing two core parameters: the packet drop probability and the buffer occupancy change rate. These two components are critical in WMSNs where QoS requirements are high, especially in applications with real-time video and multimedia streaming.
   • Packet Drop Probability P_drop(t): This parameter captures the likelihood of packet loss due to buffer overflow, which directly affects video quality. By minimizing P_drop(t), the model prioritizes high-quality multimedia transmission, particularly for I-frame packets, which are crucial in maintaining overall video clarity and integrity.
   • Buffer Occupancy Change Rate δ(t): This term minimizes abrupt increases in buffer occupancy, which are early indicators of potential congestion. The buffer occupancy change rate directly impacts network stability; hence, by controlling δ(t), the model prevents rapid, destabilizing congestion triggers. This inclusion is essential for reducing jitter and maintaining smooth video playback across the network.

Together, these two parameters provide a balanced approach that directly targets the critical QoS aspects of packet delivery and network stability in a manner suitable for WMSNs.

2. Suitability and Design of the Objective Function: Our objective function in Equation (5) is a weighted combination of P_drop(t). The weights P_i and λ are carefully selected to reflect the priority of packet types (e.g., high-priority I-frames) and the network’s tolerance for changes in buffer occupancy. By using a simple, interpretable objective, we ensure computational efficiency, which is essential for real-time network adjustments in WMSNs. This design choice intentionally keeps the optimization lightweight, allowing it to be implemented in resource-constrained sensor nodes without overwhelming computational demands.
3. Validation of the Model through Experimental Results: The optimization model and its results were rigorously validated through empirical testing, as described in our experimental results section. Using a multi-node test bed of Raspberry Pi nodes, we evaluated BOCC’s performance across various metrics, including:
   • Packet Delivery Ratio for I-frame and P-frame packets, showing that BOCC maintains a higher delivery ratio for critical packets compared to other protocols.
   • End-to-End Delay: Our results demonstrate that the BOCC protocol minimizes delay effectively, especially under higher data rates, outperforming alternative protocols.
   • Peak Signal-to-Noise Ratio (PSNR): This metric, which reflects video quality, validates that BOCC’s prioritization of I-frame packets yields superior video quality, supporting the protocol’s effectiveness in QoS maintenance.
   • Buffer Occupancy Trends: The experimental results confirm that BOCC’s control over buffer occupancy is consistent with our optimization objectives, demonstrating stability in buffer levels without abrupt changes, aligning with the goal of minimizing δ(t).

These results show that the proposed model successfully achieves congestion mitigation and quality preservation, supporting the accuracy and relevance of the chosen optimization formulation.

4. Conclusion on Model Adequacy: The simplicity of the optimization model is intentional, designed to achieve efficient congestion control without unnecessary computational complexity. The experimental results validate that our model captures the necessary dynamics to support QoS in WMSNs. Therefore, we contend that the chosen optimization model is both theoretically sound and practically validated.

 

Author Response File: Author Response.docx

Reviewer 4 Report

Comments and Suggestions for Authors

 

In the manuscript entitled “Buffer Occupancy Based Congestion Control Protocol for Wireless Multimedia Sensor Networks”, the authors focused on the issues caused by congestion in WMSN. They proposed protocol to overcome this problem. They used a raspberry-pi sensor node in their setup and claimed that their proposed protocol outperforms the existing algorithms. The work and results are promising and I would like to congratulate the authors for their effort. The authors need to consider the following point.

1.     Add numerical results in Abstract and conclusion.

2.     Use full text for all abbreviations when used first time. Full text of abbreviations are in the references but it is still recommended to use full text once in the manuscript. For example ECODA. 

3.     Some text is bold for example “topology of WMSNs is depicted in figure 1.”

4.     “Introduction” section is long. Some paragraphs from this section can be moved to “Related work” section.

5.     Size of figure 2, which occupies whole page, can be reduced. Similarly, the size of figure 3 can also be reduced.

 

Comments on the Quality of English Language

The quality of English is good and only minor editing is required. 

Author Response

Dear Reviewer,

We are very grateful to you for giving us an opportunity to revise our manuscript. We appreciate you and the respected reviewers for their constructive comments and suggestions on our manuscript entitled “Buffer Occupancy Based Congestion Control (BOCC) for Wireless Multimedia Sensor Networks (WMSNs)”. Based on these comments and suggestions, we have made careful modifications on the original manuscript. The comments of reviewers are in italic, while our response in plain text. The modified texts in the manuscript are in red font to highlight the changes made for quick review. We are very grateful to the reviewer for their time and valuable comments. The comments are very helpful to further enhance our manuscript.

 

 

Point-by-point response

 

In the manuscript entitled “Buffer Occupancy Based Congestion Control Protocol for Wireless Multimedia Sensor Networks”, the authors focused on the issues caused by congestion in WMSN. They proposed protocol to overcome this problem. They used a raspberry-pi sensor node in their setup and claimed that their proposed protocol outperforms the existing algorithms. The work and results are promising and I would like to congratulate the authors for their effort. The authors need to consider the following point.

 

Response

 

We would like to sincerely thank you for your positive feedback on our manuscript, "Buffer Occupancy Based Congestion Control Protocol for Wireless Multimedia Sensor Networks." We appreciate your recognition of our efforts to address congestion issues in Wireless Multimedia Sensor Networks (WMSNs) and the promising results derived from our protocol, implemented using Raspberry Pi sensor nodes.

We are committed to enhancing our manuscript based on your suggestions. However, it appears that the specific points requiring our attention were not fully articulated in your comment. We would greatly appreciate it if you could provide further details regarding the specific aspects you believe we should consider.

1. Add numerical results in Abstract and conclusion.

 

Thank you for your valuable suggestion to include numerical results in the Abstract and Conclusion of our manuscript. We agree that presenting specific numerical results in these sections will enhance the clarity and impact of our findings.

We have revised the abstract and conclusion sections to include specific numerical results from our experiments. Thank you for the suggestion.

 

2. Use full text for all abbreviations when used first time. Full text of abbreviations are in the references but it is still recommended to use full text once in the manuscript. For example ECODA. 

 

Response to Reviewer Comment:

Thank you for your constructive feedback regarding the use of full text for abbreviations in our manuscript. We agree that it is important to provide clarity to readers by defining abbreviations when they are first introduced.

A table is added that includes all acronyms used in the document and their definitions

3. Some text is bold for example “topology of WMSNs is depicted in figure 1.”

 

Response to Reviewer Comment:

Thank you for your observation regarding the use of bold text in the manuscript. We appreciate your attention to detail in ensuring consistency and clarity in the presentation. We corrected the formatting issues in the manuscript.

 

4. “Introduction” section is long. Some paragraphs from this section can be moved to “Related work” section.

Response to Reviewer Comment:

Thank you for your insightful feedback regarding the length of the "Introduction" section. We appreciate your suggestions for improving the manuscript’s structure. Unnecessary details are removed from the manuscript and the updated text is highlighted in the manuscript.

 

 

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors have satisfactorily addressed all concerns that were previously raised. So, I recommend acceptance of the manuscript for publication.

Author Response

The authors have satisfactorily addressed all concerns that were previously raised. So, I recommend acceptance of the manuscript for publication.

Response:

Thank you for your positive feedback and recommendation for acceptance. We appreciate the time and effort you invested in reviewing our manuscript and addressing all concerns. We are grateful for your constructive feedback, which has helped us improve the quality of our work.

Reviewer 2 Report

Comments and Suggestions for Authors

I thank the authors for their response and response to my comments. Much of it has been removed and improved. The presentation quality and clarity have improved. Unfortunately, some still persisted, for example, missing punctuation after mathematical equations, images are still not in vector format and are unnecessarily large. In the answer, authors state that they eliminated this deficiency, but it did not happen. Please use e.g. .pdf or .eps format for all charts. I ask the authors to correct these shortcomings as well:

1) Correct the punctuation after all equations as I pointed out last time.

2) Number only the equations to which there is a reference in the text.

3) If the reference is to Figure 1 or Equation (1), it should be capitalized.

4) Figure 1 is not in vector format and is unnecessarily large. His information could be summarized in a much smaller picture.

5) Figure 2 is not in vector format and is unnecessarily large. His information could be summarized in a much smaller picture.

6) Figure 3 is not in vector format and is unnecessarily large. His information could be summarized in a much smaller picture. In addition, the arrows sometimes extend into the blocks.

7) Figure 4 is not in vector format and is unnecessarily large. His information could be summarized in a much smaller picture.

8) Figures 5,6,7,8 are not in vector format and are unnecessarily large. His information could be summarized in a much smaller picture. In addition, this is probably a screenshot, because there is a red underline at the top, which is quite inappropriate.

9) Figures 9,10,11,12 are not in vector format and are unnecessarily large. His information could be summarized in a much smaller picture.

10) Figures 13,14,15,16 are not in vector format and are unnecessarily large. His information could be summarized in a much smaller picture.

11) I also recommend using Matlab rendering with box on and grid on for better clarity and easier orientation in the graph.

12) Resize all images so that there is no white space in the text, as on page 22.

13) On page 12, the overlapping numbering of lines 11,12 and 13 in the description of the algorithm appears.

14) On page 16, the overlapping numbering of lines 7 - 20 in the description of the algorithm appears. Line 20 has an unreadable number.

Comments on the Quality of English Language

The English language is mostly fine and I haven't encountered any problems except capital letters for references and punctuation after math equations.

Author Response

Dear Reviewer,

We are very grateful to you for giving us an opportunity to revise our manuscript. We appreciate you for your constructive comments and suggestions on our manuscript entitled “Buffer Occupancy Based Congestion Control (BOCC) for Wireless Multimedia Sensor Networks (WMSNs)”. Based on these comments and suggestions, we have made careful modifications on the original manuscript. The comments of reviewers are in italic and bold, while our response in plain text. The modified texts in the manuscript are in red font to highlight the changes made for quick review. We are very grateful to the reviewer for their time and valuable comments. The comments are very helpful to further enhance our manuscript.

 

Comments

I thank the authors for their response and response to my comments. Much of it has been removed and improved. The presentation quality and clarity have improved. Unfortunately, some still persisted, for example, missing punctuation after mathematical equations, images are still not in vector format and are unnecessarily large. In the answer, authors state that they eliminated this deficiency, but it did not happen. Please use e.g. .pdf or .eps format for all charts. I ask the authors to correct these shortcomings as well:

• Correct the punctuation after all equations as I pointed out last time.

() Punctuation after equations is missing almost everywhere. If the sentence before it is preceded by a dot (:), then if the sentence continues after it, there must be a comma (,) after it, and if not, then a dot (.))

Thank you for the feedback. I have reviewed and corrected all the noted issues.

 

2) Number only the equations to which there is a reference in the text.

 

Thank you for the suggestion. I’ve updated the document so that only equations referenced in the text are numbered.

 

3) If the reference is to Figure 1 or Equation (1), it should be capitalized.

 

"Thank you for the guidance. I’ve ensured that references to figures and equations are now capitalized as suggested.

4) Figure 1 is not in vector format and is unnecessarily large. His information could be summarized in a much smaller picture.

Thank you for pointing this out. I’ve resized and optimized Figure 1 to a smaller, more concise format to improve clarity and file size.

 

5) Figure 2 is not in vector format and is unnecessarily large. His information could be summarized in a much smaller picture.

Thank you for pointing this out. I’ve resized and optimized Figure 2 to a smaller, more concise format to improve clarity and file size.

 

 

6) Figure 3 is not in vector format and is unnecessarily large. His information could be summarized in a much smaller picture. In addition, the arrows sometimes extend into the blocks.

Thank you for pointing this out. I’ve resized and optimized Figure 3 to a smaller, more concise format to improve clarity and file size.

 

7) Figure 4 is not in vector format and is unnecessarily large. His information could be summarized in a much smaller picture.

 

Thank you for pointing this out. I’ve resized and optimized Figure 4 to a smaller, more concise format to improve clarity and file size.

 

 

8) Figures 5,6,7,8 are not in vector format and are unnecessarily large. His information could be summarized in a much smaller picture. In addition, this is probably a screenshot, because there is a red underline at the top, which is quite inappropriate.

Thank you for pointing this out. I’ve resized and optimized Figure 5,6,7,8 to a smaller, more concise pdf format to improve clarity and file size.

 

 

9) Figures 9,10,11,12 are not in vector format and are unnecessarily large. His information could be summarized in a much smaller picture.

Thank you for pointing this out. I’ve resized and optimized Figures 9,10,11, and 12 to a smaller, single more concise vector format to improve clarity and file size.

 

10) Figures 13,14,15,16 are not in vector format and are unnecessarily large. His information could be summarized in a much smaller picture.

Thank you for pointing this out. I’ve resized and optimized Figures 13,14, and 15, 16 to a a single smaller, more concise vector format to improve clarity and file size.

 

11) I also recommend using Matlab rendering with box on and grid on for better clarity and easier orientation in the graph.

Thankyou for the valuable suggestion, i have used the MATLAB 2018 to generate eps vector files for the figures 9-16

12) Resize all images so that there is no white space in the text, as on page 22.

Thank you for pointing this out. I’ve resized and optimized all Figures

13) On page 12, the overlapping numbering of lines 11,12 and 13 in the description of the algorithm appears.

Thank you for pointing this out. Algorithm is updated.

 

14) On page 16, the overlapping numbering of lines 7 - 20 in the description of the algorithm appears. Line 20 has an unreadable number.

Thank you for pointing this out. Algorithm is updated.

 

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

Although the authors have provided additional details in the response file, the actual modifications in the manuscript appear to require further refinement.

* Regarding previous comment 5, while the authors mention they considered using averaging techniques for buffer occupancy over a short moving window, the revised manuscript lacks clear context or details reflecting this incorporation.

* Concerning previous comment 6, although the authors have provided additional details on the predefined threshold value, 𝜌, it remains unclear how this value is specifically defined or determined in the revised manuscript.

* For previous comment 8, it is challenging to locate any modifications made in response to this comment within the revised manuscript.

* Similarly, for previous comment 9 and 10, it is difficult to identify any corresponding changes or clarifications in the revised manuscript.

 

Author Response

Dear Reviewer,

We are very grateful to you for giving us an opportunity to revise our manuscript. We appreciate you and the respected reviewers for their constructive comments and suggestions on our manuscript entitled “Buffer Occupancy Based Congestion Control (BOCC) for Wireless Multimedia Sensor Networks (WMSNs)”. Based on these comments and suggestions, we have made careful modifications on the original manuscript. The comments of reviewers are in italic and bold, while our response in plain text. The modified texts in the manuscript are in red font to highlight the changes made for quick review. We are very grateful to the reviewer for their time and valuable comments. The comments are very helpful to further enhance our manuscript.

1. Although the authors have provided additional details in the response file, the actual modifications in the manuscript appear to require further refinement. Regarding previous comment 5, while the authors mention they considered using averaging techniques for buffer occupancy over a short moving window, the revised manuscript lacks clear context or details reflecting this incorporation.

Response:

Thank you for the insightful suggestion. To address this, we have expanded the section 3.2 Problem Formulation for Buffer Occupancy-Based Congestion Control (BOCC) Algorithm item no. 1 “Buffer Occupancy”. The updated text is highlighted in red colour.

 

2. Concerning previous comment 6, although the authors have provided additional details on the predefined threshold value, ?, it remains unclear how this value is specifically defined or determined in the revised manuscript.

Response:

Thank you for the insightful suggestion. To address this, we have expanded the section 3.2 Problem Formulation for Buffer Occupancy-Based Congestion Control (BOCC) Algorithm item no. 2 “Congestion levels”. The updated text is highlighted in red colour.

 

3. For previous comment 8, it is challenging to locate any modifications made in response to this comment within the revised manuscript.

Response:

Thank you for the insightful suggestion. To address this, we have expanded the section 3.2 Problem Formulation for Buffer Occupancy-Based Congestion Control (BOCC) Algorithm item no. 4 “Feedback Mechanisms”. The updated text is highlighted in red colour.

 

4. Similarly, for previous comment 9 and 10, it is difficult to identify any corresponding changes or clarifications in the revised manuscript.

 

Response:

Thank you for the insightful suggestion. To address this, we have expanded the section 3.2 Problem Formulation for Buffer Occupancy-Based Congestion Control (BOCC) Algorithm. The updated text is appended right after the item 6. Overall optimization problem. The updated text is highlighted in red colour.

 

Author Response File: Author Response.docx

Round 3

Reviewer 2 Report

Comments and Suggestions for Authors

The authors addressed all my comments. Thanks to this, the quality of the presentation and the overall format of the article increased considerably. I hereby thank the authors for devoting additional time to their works. I have no further comments.

Reviewer 3 Report

Comments and Suggestions for Authors

The authors have carefully responded to the reviewer's comments.