High-Performance Data Throughput Analysis in Wireless Ad Hoc Networks for Smart Vehicle Interconnection

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This study focuses on optimizing routing protocols in Vehicular Ad Hoc Networks (VANETs) to enhance data throughput and support real-time communication in smart city applications. Additionally, the authors introduce the Taguchi Optimization Method (TOM) and Differential Evolution Method (DEM) to optimize the parameter configurations of AODV and GPSR protocols, significantly improving throughput performance in dynamic network environments. However, several aspects of the study could be improved, as outlined below:

1. The experimental scenarios only include urban and highway environments, without covering more challenging real-world applications such as suburban areas, tunnels, or multi-level structures. It is recommended to expand the diversity of scenarios to simulate conditions like congested city centers, tunnels, and various seasonal traffic conditions (e.g., rain or snow).
2. While TOM and DEM are employed in this study, there is no sensitivity analysis for the selection of optimization parameters. It is suggested to analyze the impact of different parameters (e.g., packet size, vehicle speed) on the results and evaluate the robustness of parameter selection on protocol performance.
3. All experiments in this study are simulation-based, lacking validation with real-world data, which may affect the practical applicability of the results. It is recommended to incorporate actual vehicle data and field test scenarios to validate the applicability of the simulation results.
4. The study only uses throughput as the primary performance metric, neglecting other QoS metrics such as latency, energy consumption, and packet loss rate. It is advised to include multi-dimensional evaluation metrics, such as latency, network stability, and energy efficiency, to provide a more comprehensive analysis of protocol performance.
5. The study does not provide detailed information about the selection and configuration of simulation tools, which impacts the reproducibility of the research. It is recommended to include specific settings and implementation details of the simulation tools (e.g., NS-3 or Omnet++) to enhance the transparency and replicability of the study.

 

Author Response

Reviewer 1

This study focuses on optimizing routing protocols in Vehicular Ad Hoc Networks (VANETs) to enhance data throughput and support real-time communication in smart city applications. Additionally, the authors introduce the Taguchi Optimization Method (TOM) and Differential Evolution Method (DEM) to optimize the parameter configurations of AODV and GPSR protocols, significantly improving throughput performance in dynamic network environments. However, several aspects of the study could be improved, as outlined below:

Reviewer 1 Comment

 

1. The experimental scenarios only include urban and highway environments, without covering more challenging real-world applications such as suburban areas, tunnels, or multi-level structures. It is recommended to expand the diversity of scenarios to simulate conditions like congested city centers, tunnels, and various seasonal traffic conditions (e.g., rain or snow).

 

Response to Reviewer 1

 

Thank you for your valuable feedback. We acknowledge the importance of expanding the diversity of experimental scenarios to include more complex real-world applications such as suburban areas, tunnels, and multi-level structures, as well as various seasonal traffic conditions.

 

However, this study primarily focuses on data throughput performance, which serves as a prerequisite for deploying the system into more complex scenarios. The current urban and highway environments were selected as fundamental testbeds to establish baseline performance, ensuring robustness before progressing to more challenging conditions. Future research will extend this work by incorporating additional scenarios such as congested city centers, tunnels, and adverse weather conditions to assess system reliability under diverse real-world constraints.

 

We appreciate the reviewer’s insightful recommendation and will highlight this as an important direction for our future studies.

 

Reviewer 1 Comment

 

2. While TOM and DEM are employed in this study, there is no sensitivity analysis for the selection of optimization parameters. It is suggested to analyze the impact of different parameters (e.g., packet size, vehicle speed) on the results and evaluate the robustness of parameter selection on protocol performance.

 

 

Response to Reviewer 1

 

We appreciate the reviewer’s valuable suggestion. In response, we have now included an analysis of the impact of packet size and vehicle speed on the results to assess the robustness of parameter selection in protocol performance. The revised manuscript provides a detailed evaluation of how different packet sizes influence throughput and how varying vehicle speeds affect routing efficiency. These additions ensure a more comprehensive understanding of the sensitivity of optimization parameters. The relevant discussions and analysis have been incorporated in line  [572-613] of the manuscript.

We appreciate the reviewer’s suggestion and will ensure that the relevance of parameter selection is explicitly emphasized in the revised manuscript in red.

 

Reviewer 1 Comment

 

 

1. All experiments in this study are simulation-based, lacking validation with real-world data, which may affect the practical applicability of the results. It is recommended to incorporate actual vehicle data and field test scenarios to validate the applicability of the simulation results.

 

Response to Reviewer 1

 

We appreciate the reviewer’s concern regarding real-world validation. To address this, we have conducted three experimental sets designed to rigorously evaluate the performance of routing protocols in VANET scenarios. The first set analyzes the impact of AODV and GPSR routing parameters under different VANET conditions, identifying optimal values for city and highway environments. The second set assesses the proposed CM-AODV and CM-GPSR protocols, measuring their efficiency and improvements over AODV and GPSR, while also comparing them with the IOLSR routing protocol. The third set focuses on a comparative evaluation of TOM and DEM optimization methods in city and highway scenarios.

 

Our findings, as summarized in Table 1 of the supplementary document, demonstrate that routing parameter preferences vary significantly between city and highway environments, particularly in terms of MaxJitter and beacon interval settings, directly influencing delay and packet delivery performance. These insights highlight the necessity for adaptive routing protocol designs in VANET. To enhance applicability, CM-AODV and CM-GPSR have been developed using the chameleon method with TOM and DEM optimizations, ensuring improved routing efficiency and adaptability. While this study primarily relies on simulations, the extensive experimental framework provides a strong basis for real-world applicability, and future work will focus on incorporating actual vehicle data and field test scenarios to further validate the findings Line [616 to 621].

 

Reviewer 1 Comment

 

 

1. The study only uses throughput as the primary performance metric, neglecting other QoS metrics such as latency, energy consumption, and packet loss rate. It is advised to include multi-dimensional evaluation metrics, such as latency, network stability, and energy efficiency, to provide a more comprehensive analysis of protocol performance.

 

Response to Reviewer 1

 

We appreciate the reviewer’s valuable suggestion regarding the inclusion of additional QoS metrics. In this study, throughput was selected as the primary performance metric to evaluate the efficiency of the proposed routing mechanisms in VANET. However, we recognize the importance of a multi-dimensional evaluation approach to gain a more comprehensive understanding of protocol performance.

 

To address this, we have recommended in the Future Work section that future studies should incorporate additional QoS metrics, including latency, network stability, energy efficiency, and packet loss rate. This will allow for a broader performance assessment under different network conditions. Additionally, we encourage other researchers to explore these metrics in diverse VANET environments, such as high-traffic urban areas and dynamic highway scenarios, to further validate the adaptability and efficiency of the proposed optimization methods Line [ 621 to 641].

Reviewer 1 Comment

 

 

1. The study does not provide detailed information about the selection and configuration of simulation tools, which impacts the reproducibility of the research. It is recommended to include specific settings and implementation details of the simulation tools (e.g., NS-3 or Omnet++) to enhance the transparency and replicability of the study.

 

Response to Reviewer 1

 

We appreciate the reviewer’s feedback regarding the need for detailed information on simulation tools and configurations. In response, we have included all relevant details in the manuscript, specifying the simulation tools used, their configuration settings, and implementation parameters to enhance the transparency and reproducibility of the study. Line [315 to 343].

 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The paper, "High-Performance Data Throughput Analysis in Wireless Ad Hoc Networks for Smart Vehicle Interconnection," examines optimized routing protocols in vehicular ad hoc networks (VANETs) using the Taguchi Optimization Method (TOM) and Differential Evolution Method (DEM). While the study shows significant throughput improvements in urban and highway scenarios, several critical issues need to be addressed:

1.      Throughput is vital, but other Quality of Service (QoS) parameters, such as latency and packet loss, are underexplored. Expanding the scope to include additional QoS metrics would provide a more comprehensive evaluation of VANET performance.

2.      Although the combination of TOM and DEM is presented as novel, similar optimization methods have been applied in prior research. The authors should clearly explain how this work advances the state-of-the-art.

3.      The use of overly technical language may limit accessibility to a broader audience. Simplifying explanations and defining less common terms is recommended.

4.      Some claims lack sufficient references, and many citations are dated or secondary sources. Updated and more relevant references should be included.

5.      The AODV and GPSR are well-established, they are not cutting-edge. Including modern protocols would enhance the study's relevance.

6.      Insufficient information is provided about the simulation parameters, including vehicle mobility models and network topology, raising concerns about the validity of the results.

7.      The reliance on TOM and DEM may introduce bias if these methods are not adequately benchmarked against alternative optimization techniques.

8.      The paper does not address how the proposed optimizations scale with an increasing number of vehicles or devices, a critical factor for real-world applications.

9.      The optimized protocols are not compared against other advanced routing protocols in the literature, limiting the depth of the evaluation.

10.   The paper repeats similar points about throughput improvements across sections, which could be streamlined for clarity.

11.   Several figures present excessive data without sufficient contextual explanation, making them difficult to interpret

 

Comments on the Quality of English Language

Language can be improved

Author Response

Reviewer 2

The paper, "High-Performance Data Throughput Analysis in Wireless Ad Hoc Networks for Smart Vehicle Interconnection," examines optimized routing protocols in vehicular ad hoc networks (VANETs) using the Taguchi Optimization Method (TOM) and Differential Evolution Method (DEM). While the study shows significant throughput improvements in urban and highway scenarios, several critical issues need to be addressed:

Reviewer 2 Comment

1. Throughput is vital, but other Quality of Service (QoS) parameters, such as latency and packet loss, are underexplored. Expanding the scope to include additional QoS metrics would provide a more comprehensive evaluation of VANET performance.

 

Response to Reviewer 2

As we have replied to the reviewer 1: We appreciate the reviewer’s valuable suggestion regarding the inclusion of additional QoS metrics. In this study, throughput was selected as the primary performance metric to evaluate the efficiency of the proposed routing mechanisms in VANET. However, we recognize the importance of a multi-dimensional evaluation approach to gain a more comprehensive understanding of protocol performance. To address this, we have recommended in the Future Work section that future studies should incorporate additional QoS metrics, including latency, network stability, energy efficiency, and packet loss rate. This will allow for a broader performance assessment under different network conditions. Additionally, we encourage other researchers to explore these metrics in diverse VANET environments, such as high-traffic urban areas and dynamic highway scenarios, to further validate the adaptability and efficiency of the proposed optimization methods Line [ 620 to 632].

 

Reviewer 2 Comment

2. Although the combination of TOM and DEM is presented as novel, similar optimization methods have been applied in prior research. The authors should clearly explain how this work advances the state-of-the-art.

Response to Reviewer 2

      Thank you for your valuable comment. We acknowledge that similar optimization methods have been explored in prior research. However, our study presents a unique integration of TOM and DEM, specifically tailored for data throughput optimization in vehicular networks, which has not been comprehensively addressed in existing literature (throughout the method and results/discussions sections) we have equally cited several literatures to support this claim [35, 36, and 37] {line 181-195].

The key advancements of this work over prior studies include:

Enhanced Parameter Optimization – Unlike previous works, our study fine-tunes the TOM-DEM framework with a focus on real-time vehicular data throughput, optimizing parameters for improved efficiency.

Scenario-Specific Performance Evaluation – This research evaluates the applicability and effectiveness of TOM-DEM in urban and highway environments, providing insights into performance trade-offs that have not been extensively analyzed before.

Scalability Considerations – The proposed approach is designed to be scalable for future deployment in more complex scenarios, serving as a foundation for real-world implementation.

Reviewer 2 Comment

3. The use of overly technical language may limit accessibility to a broader audience. Simplifying explanations and defining less common terms is recommended.

Response to Reviewer 2

Thank you for the feedback. We have simplified explanations, defined technical terms, and revised complex sections to improve accessibility while maintaining technical accuracy. These changes have been incorporated into the revised manuscript (Through out the manuscript)

Reviewer 2 Comment

4. Some claims lack sufficient references, and many citations are dated or secondary sources. Updated and more relevant references should be included.

Response to Reviewer 2

Thank you for your feedback. We have reviewed and updated the references, replacing outdated and secondary sources with more recent and relevant citations. Additional references have also been included to support key claims and enhance the credibility of our study. These revisions have been incorporated into the manuscript [Methods and Results/discussion].

Reviewer 2 Comment

1. The AODV and GPSR are well-established, they are not cutting-edge. Including modern protocols would enhance the study's relevance.

 

Response to Reviewer 2

Thank you for your insightful comment. We acknowledge that AODV and GPSR are well-established protocols. They were selected as benchmark models due to their widespread use and foundational role in vehicular networking research. Performance validation is conducted by analyzing and comparing the results with well-defined protocols from the literature. Additionally, we have compared our work with new protocols in the literature and found that our approach demonstrates greater stability and effectively captures parameter tuning compared to other recent studies. Line [377-380] & [508 to 510]

 

Reviewer 2 Comment

2. Insufficient information is provided about the simulation parameters, including vehicle mobility models and network topology, raising concerns about the validity of the results.

Response to Reviewer 2

We thank the reviewer for pointing out the need for more information on the simulation parameters. In response, we have included the required details in the manuscript to clarify the simulation setup. Specifically, we have provided comprehensive information about the vehicle mobility models, network topology, and other key simulation parameters, including vehicle density, communication range, and traffic patterns. These additional details aim to enhance the transparency of the study and ensure that the validity and reproducibility of the results are clearly supported. We believe that these revisions address the reviewer’s concerns and provide the necessary context to fully understand the experimental setup.  Line [315 to 343].

Reviewer 2 Comment

3. The reliance on TOM and DEM may introduce bias if these methods are not adequately benchmarked against alternative optimization techniques.

Response to Reviewer 2

We appreciate the reviewer’s insightful comment. We selected TOM (Taguchi Optimization Method) and DEM (Differential Evolution Method) based on their proven efficacy in multi-objective optimization within the context of dynamic network environments like VANETs. Both methods have been widely adopted and benchmarked in similar studies, demonstrating their robustness and ability to optimize multiple conflicting parameters, which is crucial for enhancing routing protocol performance in VANETs. These texts have been incorporated into the revised manuscript.  Line [105 to 123]

The Taguchi method has been benchmarked in various studies for parameter tuning and optimization in communication networks. For example, in [27, 28], Taguchi was used to optimize routing protocols for wireless sensor networks (WSNs), showing that it can significantly improve network performance with fewer experiments compared to traditional optimization methods. This aligns with the efficiency needs of VANETs, where rapid adaptation to changing conditions is required.

On the other hand, Differential Evolution (DE) has been extensively benchmarked in evolutionary algorithms and applied in optimization problems, particularly where the search space is large and non-linear. In [30], DE was applied to traffic management and network routing in VANETs, where it outperformed other methods like genetic algorithms in terms of convergence speed and solution accuracy. This makes DE an ideal choice for optimizing VANET protocols, as it can effectively handle complex, multi-dimensional search spaces, such as those involving packet delivery ratio, delay, and throughput. Both TOM and DEM were chosen not only for their demonstrated success in similar optimization tasks but also for their ability to provide adaptable solutions under varying conditions, such as city and highway scenarios in VANETs. By benchmarking these methods against alternative techniques, we ensure that our results are both robust and representative of the best possible optimization strategies available in the literature. Line [105 to 123]

 

Reviewer 2 Comment

4. The paper does not address how the proposed optimizations scale with an increasing number of vehicles or devices, a critical factor for real-world applications.

Response to Reviewer 2

We appreciate the reviewer’s valuable comment regarding the scalability of the proposed optimizations with an increasing number of vehicles or devices. In response, we have included a comprehensive analysis of how our proposed optimizations scale with varying network conditions and increasing device density. To illustrate this, we have summarized the scalability of the optimization methods in different real-world VANET scenarios in the following table 3, which outlines key parameters that influence network performance.  Line [342-343]

Reviewer 2 Comment

5. The optimized protocols are not compared against other advanced routing protocols in the literature, limiting the depth of the evaluation.

Response to Reviewer 2

We have done the comparisons line  [572-626]

Reviewer 2 Comment

6. The paper repeats similar points about throughput improvements across sections, which could be streamlined for clarity.

Response to Reviewer 2

Thank you for the valuable feedback. We acknowledge the concern regarding the repetition of throughput improvement discussions across different sections. However, the results presented in multiple sections highlight distinct aspects of throughput enhancement under varying conditions and configurations. Each discussion aims to substantiate the work by providing a comprehensive analysis, ensuring a clear understanding of the improvements observed.

Streamlining these discussions might compromise the granularity of insights offered. Nonetheless, we have carefully reviewed the manuscript to refine the narrative, ensuring that redundancy is minimized while maintaining the technical rigor and clarity of the presented results.

Reviewer 2 Comment

7. Several figures present excessive data without sufficient contextual explanation, making them difficult to interpret.

Response to Reviewer 2

Thank you for the insightful feedback. To enhance clarity and interpretability, we have now incorporated a more detailed discussion, particularly focusing on comparative analysis with existing literature to better highlight the novelty of our study. Additionally, we have refined the contextual explanations accompanying the figures to ensure that the presented data is more effectively interpreted. This revision provides a clearer correlation between the obtained results and their implications, thereby improving the overall coherence and technical depth of the manuscript.

 

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

This paper evaluates the throughput performance of various routing protocols in Vehicular Ad Hoc Networks (VANETs) under urban and highway scenarios, emphasizing the benefits of using the Taguchi Optimization Method (TOM) and Differential Evolution Method (DEM) for improving data throughput. The results show that protocols like GPSR:TOM and AODV:DEM provide superior throughput, with GPSR:TOM achieving the highest performance across most scenarios. The study highlights the importance of optimizing data throughput to ensure reliable and efficient communication in smart city applications, such as traffic management and accident prevention. This paper is very interesting. Some problems need to be resolved before publication.

1. The authors should clarify the specific simulation parameters used in the experiments, such as traffic generation rates and mobility patterns.

2. The paper mentions the protocols AODV, GPSR, and their variations; however, a deeper comparative analysis with other emerging protocols would enhance the results.

3. Results for high-traffic generation are presented, but an explanation of how these conditions relate to real-world traffic flow is needed.

4. The authors should discuss the potential limitations of using TOM and DEM, particularly with regard to network overhead.

5. Some practical applications on performance analysis of VANETs should be investigated and discussed in this paper. a) " NOMA-Enhanced Cooperative Relaying Systems in Drone-Enabled IoV: Capacity Analysis and Height Optimization," in IEEE Transactions on Vehicular Technology. b) " Aerial-Aided mmWave VANETs Using NOMA: Performance Analysis, Comparison, and Insights," in IEEE Transactions on Vehicular Technology.

6. The authors should consider adding a section discussing future work or potential improvements in VANET protocol designs, specifically addressing adaptability across different types of urban environments.

 

Author Response

Reviewer 3

 

This paper evaluates the throughput performance of various routing protocols in Vehicular Ad Hoc Networks (VANETs) under urban and highway scenarios, emphasizing the benefits of using the Taguchi Optimization Method (TOM) and Differential Evolution Method (DEM) for improving data throughput. The results show that protocols like GPSR:TOM and AODV:DEM provide superior throughput, with GPSR:TOM achieving the highest performance across most scenarios. The study highlights the importance of optimizing data throughput to ensure reliable and efficient communication in smart city applications, such as traffic management and accident prevention. This paper is very interesting. Some problems need to be resolved before publication.

Reviewer 3 Comment

 

1. The authors should clarify the specific simulation parameters used in the experiments, such as traffic generation rates and mobility patterns.

Response to Reviewer 3

Thank you for your valuable feedback. We have clarified the simulation parameters used in the experiments, including traffic generation rates, mobility patterns, and other relevant settings such as vehicle density and speed profiles. These details have been added to the methodology section to ensure transparency and allow for better reproducibility of the experiments. .  Line [312 to 340].

Reviewer 3 Comment

2. The paper mentions the protocols AODV, GPSR, and their variations; however, a deeper comparative analysis with other emerging protocols would enhance the results.

Response to Reviewer 3

Thank you for your suggestion. We have now included a deeper comparative analysis of AODV, GPSR, and their variations, alongside emerging protocols such as SDN-based protocols and delay-tolerant networking (DTN) protocols. This analysis highlights the strengths, weaknesses, and potential applications of each protocol, offering a more comprehensive understanding of their performance in different scenarios. Line [508 to 516].

Reviewer 3 Comment

3. Results for high-traffic generation are presented, but an explanation of how these conditions relate to real-world traffic flow is needed.

Response to Reviewer 3

Thank you for your comment. We have included an explanation of how high-traffic generation conditions in our simulations relate to real-world traffic flow. Specifically, we discuss the assumptions made regarding vehicle density, congestion, and traffic patterns and how these conditions were modelled to reflect real-world urban environments. This clarification has been added to the manuscript to strengthen the relevance of our results to practical applications and also details is provided in supplementary documents.

Reviewer 3 Comment

4. The authors should discuss the potential limitations of using TOM and DEM, particularly with regard to network overhead.

Response to Reviewer 3

Thank you for your insightful comment. We have added a discussion on the potential limitations of using TOM and DEM, particularly regarding network overhead. This includes an analysis of computational complexity, scalability concerns, and the trade-offs between optimization accuracy and real-time performance. These revisions have been incorporated into the manuscript to provide a more balanced perspective on the study’s findings. Line [508 to 516].

Reviewer 2 Comment

5. Some practical applications on performance analysis of VANETs should be investigated and discussed in this paper. a) "NOMA-Enhanced Cooperative Relaying Systems in Drone-Enabled IoV: Capacity Analysis and Height Optimization," in IEEE Transactions on Vehicular Technology. b) "Aerial-Aided mmWave VANETs Using NOMA: Performance Analysis, Comparison, and Insights," in IEEE Transactions on Vehicular Technology.

Response to Reviewer 3

Thank you for the suggestion. We found the recommended literature valuable, particularly for future studies, and have accordingly incorporated and cited them as [33] and [34] in the manuscript. Additionally, we have expanded the discussion to include relevant aspects of VANET performance analysis, aligning with the insights from these works.

Reviewer 2 Comment

6. The authors should consider adding a section discussing future work or potential improvements in VANET protocol designs, specifically addressing adaptability across different types of urban environments.

 

Response to Reviewer 3

Thank you for your valuable suggestion. We have added a Future Work section discussing potential improvements in VANET protocol designs, specifically focusing on adaptability across different urban environments. This section highlights key challenges, including dynamic topology, traffic density variations, and environmental constraints, and outlines directions for enhancing protocol performance in diverse real-world scenarios.

These revisions have been incorporated into the manuscript to strengthen its contribution and relevance. Line [629 to 641]

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The author has revised the paper based on the review comments. It is recommended that the paper be accepted and published.

Reviewer 3 Report

Comments and Suggestions for Authors

I am satisfied with the authors response.