A Study of MANET Routing Protocols in Heterogeneous Networks: A Review and Performance Comparison

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The article investigates an interesting topic and aims to provide evidence from a context where the topic is of relevance. The need for this investigation is extended in the introduction section and the gap in the literature is clear. 

The main objective of this paper is to review and compare the performance of four selected MANET routing protocols in a heterogeneous Mobile Ad hoc Networks setting. 

The literature review section is well elaborated and sets the ground for the investigation.

Three research questions were formulated:

Research Question 1: How do the routing protocols (AODV, OLSR, BATMAN, DYMO) affect MANET performance in a heterogeneous environment?

Research Question 2: What impact do heterogeneous nodes have on the quality of service (QoS) parameters in MANET routing protocols?

Research Question 3: How can the findings from the performance comparison of MANET routing protocols in heterogeneous environments inform the development of next-generation wireless networks?

We recommend that each figure and table have a source.

Four MANET routing protocols have been selected for this article:

AODV  - Ad-hoc On-demand Distance Vector

OLSR - Optimized Link State Routing (OLSR)

BATMAN - Better Approach to Mobile Ad-hoc Networking

DYMO - Dynamic MANET On-demand.

Parameter settings for simulations remain the same across all four routing protocols.

All results presented in this paper are obtained with 95% confidence interval and ≤ 5% statistical errors and the model is validated on how it reacts to its inputs and the model’s output behaviors.

The following methods were used to validate the simulation model: Animation, Parameter variability and sensitivity analysis and Face validity

Although 3 research questions were issued, the article does not specify their degree of validity. We recommend taking this aspect into account.

 

We also recommend extending the conclusions section.

 

Comments on the Quality of English Language

Overall, the article is well-written. Yet, authors should pay attention to few syntax errors and possible typos found across the manuscript. There is a need to correct grammatical errors and to convey information in an easy understandable and explicit way. This will enhance the readability of their work

Author Response

Please see attached pdf Response to Reviewer 1

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

1. Connect the Dots to Real-World Impact
The study’s findings feel a bit siloed in simulations. Take a moment to explore how these results could shape real-world systems. For example, if DYMO excels in mixed-device networks, could this be a game-changer for disaster recovery teams relying on ad-hoc communication during emergencies? Or how might it stabilize data flow in military field operations where devices vary widely? Grounding the results in tangible applications will help readers see the bigger picture.

2. Own the Limitations
Every study has boundaries, and being upfront about them builds trust. Right now, the paper doesn’t address questions like: Would DYMO hold up in a network of 1,000+ nodes? How might real-world interference (like urban Wi-Fi congestion) skew the results compared to OMNeT++ simulations? A dedicated “Limitations” section could tackle these gaps head-on. For instance, if your tests used 10 mobile phones and 5 laptops, what happens if we triple those numbers? Acknowledging these constraints doesn’t weaken the work—it shows depth.

3. Explain the “Why” Behind the Data
The results section has strong data, but readers need more storytelling. When DYMO outperforms OLSR in latency (Figure 3), why does that happen? Is it DYMO’s hybrid approach cutting down route discovery time? Or maybe its adaptability to erratic mobility patterns? Connecting these dots helps readers grasp the mechanics behind the metrics.

4. Defend Your Toolbox Choices
You used OMNeT++ for simulations, but why not NS-3 or QualNet? A sentence or two comparing these tools—like OMNeT++’s modular design being better suited for visualizing heterogeneous networks—would silence skeptics who might question the methodology.

5. Polish the Visuals
Some figures and tables feel like puzzles without answers. For example, a throughput graph could use annotations like “20% improvement here” or a trend line to highlight where DYMO pulls ahead. Captions should also summarize key takeaways, like “Figure 5: DYMO maintains stable throughput even as node mobility increases, unlike AODV.”

6. Tighten the Terminology
Small inconsistencies, like switching between “BATMAN” and “Batman,” can trip up readers. Stick to one format and double-check that all acronyms (e.g., AODV) are defined upfront.

7. Simplify the Language
A few sections get bogged down by overly technical phrasing. For example:

• Original: “The simulation results for DYMO illustrate that it achieves superior performance with respect to delay and throughput…”

• Revised: “DYMO outperforms other protocols in delay and throughput, making it ideal for networks where devices move unpredictably.”

8. Stress-Test Scalability
The paper hints at DYMO’s strengths but doesn’t ask: What happens in a massive network? Could this protocol handle a smart city’s IoT sprawl, or would it buckle under 500+ nodes? Addressing scalability—even briefly—would reassure readers eyeing large-scale deployments.

9. Link to Prior Research
How do your findings stack up against earlier studies? If AODV’s throughput here is lower than in past work, is it because of your unique node mix or simulation setup? These comparisons add context and show where your work fits in the broader field.

10. Chart a Path Forward
The conclusion could spark excitement by pointing to specific next steps. For example:

• Could machine learning fine-tune DYMO’s routing decisions in real time?

• How would these protocols perform in a 5G-integrated MANET?

• What new vulnerabilities might arise in IoT deployments, and how can they be mitigated?

Author Response

Please see attached pdf Response to Reviewer 2

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

Research Motivation and Definition of Research Questions

Although the paper highlights the significance of Mobile Ad Hoc Networks (MANETs) in heterogeneous network environments, the articulation of the research problem is somewhat vague and lacks a strong theoretical foundation. While the study outlines three research questions, including the impact of different routing protocols on MANET performance, it does not clearly explain their academic contributions or how they address existing research gaps. Furthermore, although the author mentions challenges in heterogeneous networks, the paper lacks an in-depth discussion on why these challenges remain unresolved in current studies, which weakens the research motivation.

Literature Review Insufficiently Reflects Recent Research Developments

The literature review classifies various MANET routing protocols (such as AODV, OLSR, BATMAN, and DYMO) and discusses issues in heterogeneous networks. However, the cited literature is fragmented and lacks a systematic analysis. Additionally, some references are outdated, with certain sources published before 2010, potentially failing to reflect recent technological advancements. The paper should incorporate more studies published after 2020 to ensure a comprehensive and up-to-date research foundation.

Simulation Environment and Parameter Settings Lack Realism

The study utilizes OMNeT++ for simulations, modeling scenarios with fixed PDAs, low-mobility laptops, and highly mobile smartphone nodes. However, the simulation scale is limited to only 12 nodes and does not account for other critical variables affecting MANET performance, such as interference, varying network load conditions, or node density changes. Additionally, the transmission power range (2-5mW) is somewhat unrealistic compared to actual wireless environments, which may result in significant discrepancies between the research findings and real-world applications.

Data Analysis and Result Discussion Lack Depth

 

The study evaluates the performance of various MANET routing protocols using metrics such as delay, throughput, and packet delivery ratio (PDR). However, the data analysis remains superficial, often merely describing which protocol achieves higher throughput without exploring the underlying reasons for the observed results. Moreover, the study does not employ statistical tests (e.g., ANOVA or t-tests) to verify the significance of the findings, thereby undermining the credibility of the results. A more in-depth analysis should be conducted, examining the strengths and weaknesses of various protocols in heterogeneous environments, such as assessing how node mobility patterns influence performance or proposing ways to enhance specific protocols.

Comments on the Quality of English Language

no comments

Author Response

Please see attached pdf Response to Reviewer 3

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

This submission sheds some light on the selection of a protocol for heterogeneous MANETs. The results indicate that a more recent reactive protocol, DYMO, is preferable in that regard compared to three other routing protocols.  The paper is well-structured and the review of Section 2 makes some well-made general remarks about the different references cited. However, the number of nodes simulated is limited and consequently one lacks the effect of varying densities in the node distribution. There are other technical details of the simulations that are missing. There are also various weaknesses of presentation. However, no doubt these downsides can be addressed

 

Comments:

1. The authors mention on several occasions that some protocols take time to settle down. However, the authors should confirm that they have run the simulation engine for sufficient time at the start of a simulation in order to allow the random number generator itself to style down.  It is well-known that simulation results at the start of a simulation may not be reliable if the random-number generator has not stabilised and consequently these results should be stabilised.

2. The authors have only  used a random waypoint  mobility model, which in the past has been frequently used, but nowadays one would hope that a more realistic mobility model was used. Therefore, the authors should consider simulating some results with at least one other mobility model to allow readers to see any changes that result. Random waypoint is a point of comparison but does not help to determine realistic behaviour of mobile node movements.

3. In Section 5, on “end-to-end delay” an author remarks “I believe this to be because it was further away from the gateway and couldn’t communicate with the gateway until it moved into range.”  This remark illustrates the problem arising from using only a relatively few nodes in that a single node can disproportionately affect the results. Therefore it is recommended that some results at least should be presented with a varying densities of nodes, including more nodes. A remark on how the initial placement of nodes occurred would also be helpful. For example, was it left to the simulator or did manual intervention occur ?.

4. The Packet Delivery Ratio (PDR) is defined strangely as “The PDR is the average time it takes for  a source to deliver packets across the network.” (page 19, line 572).

However, the number of bytes delivered, not the number of packets delivered, is shown across the four plots in Figs. 19 to 22. In fact, the UDP packet size is not given. Further the cause of packet loss is not determined: Is it buffer overflow or wireless loss? If the cause of loss is the latter, what wireless loss model is used? For example, was  it a simple model such as free space path loss or more complex (and realistic for mobile nodes) such as Rician and Rayleigh fading. If the cause was buffer overflow, what size were the buffers set to ?Therefore, the reader needs some detail on packet loss. The columns for PDR (Ratio) also seem to be missing in the PDF version.

5. In the PDR graphs, the vertical axis numbering should be made more sensible. For example, instead of 200000.0 200k is more professional.

Elsewhere, the numbering of the axes should be made more compact, where necessary. The units, according to SI standard units  of the vertical and horizontal axes should also be given, for example s for seconds.

 

6. The labels of the plots need to be made more compact. The labels at present are far too long. Though appropriate at the research report stage, they should be made more compact at the research paper stage.  

7. Figure 1 has two “Infrastructure-based Networks” boxes, whereas only one is required. Moreover, these two boxes are derived from an Infrastructure-less (Ad Hoc) Network box. It is not clear to this reviewer how the diagram’s classification is meant to work.

8. Page 2, l. 76 “While extensive research has been conducted on MANET routing protocols” This is an opportunity to reference/cite a textbook on this subject for the more general technical reader.

9. Where information in Sections 1 and 2 is repeated, such as the fact that OMNET++ is used and that MANET have certain beneficial features it is better to prune (remove) the repetitions to make the text easier to read.

Author Response

Please see attached pdf Response to Reviewer 4

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

This article critically examines and compares the performance of routing protocols in heterogeneous Mobile Ad Hoc Networks (Heterogeneous MANETs). However, various aspects of its academic structure and research design necessitate further refinement. Firstly, while the article reviews and compares four routing protocols—AODV, OLSR, BATMAN, and DYMO—the literature review is insufficiently detailed. Additionally, in examining the impact of heterogeneous nodes on Quality of Service (QoS) parameters, the research questions are overly broad and do not clearly delineate the specific performance of each protocol under varying network conditions.

Regarding the experimental design, although the study employs the OMNeT++ simulation environment, the parameter settings are overly simplistic and fail to adequately simulate real-world scenarios. Factors such as varying network topology densities or interference environments that could influence protocol performance are not adequately considered. Furthermore, the definition of heterogeneous nodes is rather rudimentary, as it overlooks critical factors such as energy consumption and hardware resource constraints, which may substantially affect the practical implementation of MANETs. In terms of data analysis, while the study presents comparisons of end-to-end delay, throughput, and packet delivery ratio, it lacks statistical significance testing, which undermines the generalizability of the findings. Additionally, the evaluation of the strengths and weaknesses of different protocols is relatively superficial, lacking a detailed analysis of failure cases or protocol performance degradation under extreme conditions.

In the conclusion section, while the article highlights DYMO’s advantages in heterogeneous environments, it does not provide clear recommendations for future research directions. This omission is particularly notable in terms of enhancing the applicability of MANETs in real-world scenarios, such as their integration with 5G or Internet of Things (IoT) technologies. Moreover, certain figures in the article lack detailed explanations, diminishing the clarity of result interpretation. Therefore, while this study offers some valuable insights, there remains room for improvement in research scope, depth of data analysis, and the generalizability of its conclusions.

Author Response

Please find attached round 2 response to reviewer pdf file

Author Response File: Author Response.pdf