Review Reports

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The paper presents a comprehensive survey on network simulators and load balancing strategies in the context of smart cities, 6G, cloud infrastructures, and agentic AI.

1. The paper does not propose a new framework, methodology, or algorithm. Its contribution is largely descriptive and classificatory, rather than analytical or constructive.
2. The depth of comparison (e.g., performance trade-offs, scalability, implementation feasibility in large-scale simulations) remains limited.
3. Since the title mentions “Agentic AI,” the paper should provide more substance on how AI-driven coordination or federated intelligence could practically be integrated into simulation environments.

Author Response

Reviewer #1

We thank the reviewer for the valuable insights, which we hope have helped to structure the paper more effectively, add further analysis and contributions, and clarify some of the paper’s key points. For clarity purposes, we submit the paper version with change tracking disabled, while attaching the full tracking of the provided changes as Author's Notes File.

 

• Reviewer Point 1. The paper does not propose a new framework, methodology, or algorithm. Its contribution is largely descriptive and classificatory, rather than analytical or constructive.
• Reviewer Point 3. Since the title mentions “Agentic AI,” the paper should provide more substance on how AI-driven coordination or federated intelligence could practically be integrated into simulation environments.

Response: We appreciate the reviewer's constructive remark. We expanded our discussion for ResQ №2 (Section 5.2) to provide a general framework that describes the desiderata for an ideal simulator, completely describes our scenario of interest, and offers a diagrammatic representation of its functioning (Figure 2). This is a general remark on the feasibility of implementing such a scenario. We also noted the limitations of current simulators and discussed the possibility of either extending them to match the desiderata above or incorporating them as specific components within this framework.

In this regard, we maintained a specific focus on how this general framework should incorporate Agentic AI, as well as discussing its implementation in our latest version of SimulatorOrchestrator and its presentation in our forthcoming paper [40] (Section 2.3.3), marking the first attempt to realise this specific architecture.

 

 

• Reviewer Point 2. The depth of comparison (e.g., performance trade-offs, scalability, implementation feasibility in large-scale simulations) remains limited.

Response: Within the last paragraph of Section 5.2, we also discussed on the feasibility of either extending existing simulators to support this architecture, as well as considered the technical challenges required for some of them to be integrated in this general framework, by assuming that this entire architecture is implemented in Python as our current solution [40].

As different simulators focus on different scenarios, it is impossible to reconcile their analyses in a single scalability benchmark, as they focus on different technologies, different parts of the scenario depicted in Figure 1, and different levels of abstraction. These considerations were summarised in Tables 2 and 4. On the other hand, we mitigated this aspect by adding further analysis of which resources each simulator can track in ResQ №2, which is now discussed in Section 5.4 and summarised in Table 5.

Notwithstanding the former, we address the completeness of each simulator with respect to the scenario from Figure 1 in Table 2, as well as discussing the overarching support for load balancing techniques in Table 3. 

Adding further analysis to the paper will come at the detriment of the paper's accessibility, which is already 38 pages long and considers four research questions discussed in Section 5.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The paper surveys the current state of network simulators, including cloud simulators, osmotic simulators and cellular network simulators including those modelling current 5G cellular networks, but also future 6G based communications. The following comments are provided to help improve the overall quality of the manuscript.

1. The abstract is overly long and descriptive, without clearly highlighting the unique contribution or innovation of this paper.
2. While the paper reviews a large number of simulators, the text often reads like a product manual or technical brochure. The authors should make the discussion more analytical, comparing strengths and weaknesses in relation to the stated research questions rather than listing features. The following can be reviewed: a: Coordinated operation of multi-energy microgrids considering green hydrogen and congestion management via a safe policy learning approach, Partitional Decoupling Method for Fast Calculation of Energy Flow in a Large-Scale Heat and Electricity Integrated Energy System
3. The manuscript relies almost entirely on text. For clarity, comparative tables summarizing simulator capabilities and diagrams illustrating the proposed federated framework are needed.
4. The contribution claims (Section 1.1) remain vague. The authors should clearly differentiate their work from prior surveys on IoT and 6G simulators, specifying what new insights or taxonomies this paper provides.
5. Several sections contain long descriptive passages. The structure would benefit from more synthesis at the end of each subsection, highlighting key takeaways rather than leaving the reader with raw descriptions.
6. The review lacks a systematic evaluation framework. Instead of only narrative descriptions, the authors could design clear evaluation criteria (e.g., scalability, IoT support, 6G readiness, interoperability) and score or rate the simulators against them.
7. Since the paper emphasizes smart city infrastructure, the absence of a conceptual architecture figure showing how different simulators and load-balancing strategies integrate is a major weakness.

Comments on the Quality of English Language

good

Author Response

Reviewer #2

We thank the reviewer for the valuable insights, which we hope have helped to structure the paper more effectively, add further analysis and contributions, and clarify some of the paper’s key points. For clarity purposes, we submit the paper version with change tracking disabled, while attaching the full tracking of the provided changes as Author's Notes File.

 

• Reviewer Point 1: The abstract is overly long and descriptive, without clearly highlighting the unique contribution or innovation of this paper.

Response: We have now revised the abstract to encompass the reviewer’s observations.

• Reviewer Point 2: While the paper reviews a large number of simulators, the text often reads like a product manual or technical brochure. The authors should make the discussion more analytical, comparing strengths and weaknesses in relation to the stated research questions rather than listing features. The following can be reviewed: a: Coordinated operation of multi-energy microgrids considering green hydrogen and congestion management via a safe policy learning approach, Partitional Decoupling Method for Fast Calculation of Energy Flow in a Large-Scale Heat and Electricity Integrated Energy System

Response: we challenged this issue by shortening the description of each paper, while clearly separating the Overview, Pros, and Cons for each surveyed approach as separate paragraphs. 

Despite the relevant contribution made by these suggested papers, these fall out of the scope of our current survey, which mainly focus on urban mobility scenarios and Smart Cities. We added these considerations at the end of Section 1.1

• Reviewer Point 3: The manuscript relies almost entirely on text. For clarity, comparative tables summarizing simulator capabilities and diagrams illustrating the proposed federated framework are needed.

Response: We thank the reviewer for this constructive comment. We have now added Tables 1-3 and 5 (Table 4 was previously the sole table in the previous version of the manuscript) and Figures 1 and 2 to summarise our written findings more effectively.

• Reviewer Point 4: The contribution claims (Section 1.1) [ndr. now Section 1.3] remain vague. The authors should clearly differentiate their work from prior surveys on IoT and 6G simulators, specifying what new insights or taxonomies this paper provides

Response: We appreciate the reviewer's observation. We have now added a dedicated section, Section 1.2, clearly highlighting the shortcomings of the previous surveys while emphasising the novel contributions made by the present paper.

• Reviewer Point 5: Several sections contain long descriptive passages. The structure would benefit from more synthesis at the end of each subsection, highlighting key takeaways rather than leaving the reader with raw descriptions.

Response: To avoid burdening the reader with extensive remarks, we preferred to add summarising tables as per Reviewer point 3 and refine our introduction to the section, rather than adding further conclusions at the end of each section. On the other hand, we have expanded our previous Discussion (Section 5) to better discuss the evaluation of each Research Question presented by this paper.

 

• Reviewer Point 6: The review lacks a systematic evaluation framework. Instead of only narrative descriptions, the authors could design clear evaluation criteria (e.g., scalability, IoT support, 6G readiness, interoperability) and score or rate the simulators against them.

Response: We thank the reviewer for this remark, as it enables us to highlight the paper's novelty and position more effectively, thereby differentiating it from other surveys. We kindly remind the reviewer that CF mMIMO and Satellite support from Table 4 remark the specific domain of interest of 6G architectures with respect to our Use Case Scenario of interest, as well as discussing 6G technologies in Section 3. 

As mentioned in a previous comparison with other surveys, we did not focus specifically on the different IoT devives, as this was already considered as part of our previous work (Section 1.2.1). Thus, we focussed more on the simulation of the underlying technology which such IoT nodes are communicating against (Table 2) as well as the possibility of modelling them as Digital Twins/Agetntic AI nodes. By adding a discussion of the desired general framework in Section 5.s. and Figure 2, we argue that the structure of each IoT device can be thorougly generalised into an Agentic AI level plus orchestrator, governing the behaviour of the previous elements. Then, each Network Simulator will model the communication started by the agent towards the nearest Edge/AP. As this architecture could be then arbitrarily extended to support different type of simulators modelling different networks, the responsability of the modelling of the IoT communication framework is deferred to each underlying simulator. The connected discussion section also discusses the potential interoperaboility of each simulator within the context of being integrated in this general framework.

 

Concerning the support for 6G technologies, we provide a break-down of its potential constituents from Section 3 in Table 2.

 

Last, we added ResQ 4 to specifically address which resource utilizations are tracked by each surveyed simulator.

 

• Reviewer Point 7: Since the paper emphasizes smart city infrastructure, the absence of a conceptual architecture figure showing how different simulators and load-balancing strategies integrate is a major weakness.

Response: Please refer to the reply to Reviewer point 6 for the description of the general framework (Figure 2). Regarding the potential of each load-balancing strategy to fully support each communication phase as described in Figure 1, we have added Table 3 to explicitly address which of these phases can actually be supported by the surveyed algorithms.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

This manuscript surveys the current state of network simulators, including cloud simulators, osmotic simulators and cellular network simulators including those modelling current 5G cellular networks, but also future 6G based communications. The following issues are present in the manuscript:
1. It is recommended that the authors provide an overall framework diagram or summary table to allow readers to quickly grasp the scope of the survey.
2. Resource consumption is also an important direction; it is suggested that the authors include a survey and analysis of resource consumption aspects.
3. The manuscript is mainly based on simulations; it is suggested to include real-world applications to help readers gain a more intuitive understanding.
4. The manuscript contains numerous references, but their formatting is inconsistent; it is recommended to standardize them.

Author Response

Reviewer #3

We thank the reviewer for the valuable insights, which we hope have helped to structure the paper more effectively, add further analysis and contributions, and clarify some of the paper’s key points. For clarity purposes, we submit the paper version with change tracking disabled, while attaching the full tracking of the provided changes as Author's Notes File.

 

• Reviewer Point 1: It is recommended that the authors provide an overall framework diagram or summary table to allow readers to quickly grasp the scope of the survey.

Response: We thank the reviewer for bringing this to our attention. We have added Figure 1 to visually describe our Use Case Scenario of interest, as well as providing an activity diagram (Figure 2) that shows the desired behaviour of an overall simulator orchestrator, which bridges together all the desired components. Table 4 provides a summary of the ability of the addressed simulators to answer the first three research questions.

• Reviewer Point 2: Resource consumption is also an important direction; it is suggested that the authors include a survey and analysis of resource consumption aspects.

Response: We thank the reviewer for this insightful comment. We now added this as an additional research question (ResQ 4). Our findings are described in Section 5.4 and summarised in Table 5.

• Reviewer Point 3: The manuscript is mainly based on simulations; it is suggested to include real-world applications to help readers gain a more intuitive understanding.

Response: To better contextualise our survey on our specific use case scenario of interest, we revised the manuscript's title as well as adding Section 1.1. to contextualise our analysis and evaluation.

• Reviewer Point 4: The manuscript contains numerous references, but their formatting is inconsistent; it is recommended to standardise them.

Response: To the best of our abilities, we carefully revised the references and tried our best to format them according to the MDPI specifications.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

I have no more comments.

Reviewer 3 Report

Comments and Suggestions for Authors

The authors have well addressed all my concerns in the revision. The manuscript is acceptable for publication in its present form.