Road side unit deployment optimization for the reliability of internet of vehicles based on information transmission model

Jun Zhang; Guangtong Hu

doi:10.1371/journal.pone.0315716

Peer Review History

Original SubmissionSeptember 9, 2024
22 Oct 2024 Decision Letter - Agbotiname Lucky Imoize, Editor PONE-D-24-39904Road side unit deployment optimization for the reliability of Internet of Vehicles based on information transmission modelPLOS ONE Dear Dr. Hu, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. ACADEMIC EDITOR: Major revision Please submit your revised manuscript by Dec 06 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. 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Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows: "This study is supported by grants from the National Social Science Foundation of China (grant number 20BGL001), which is required to be unique." Please include your amended statements within your cover letter; we will change the online submission form on your behalf. Additional Editor Comments: The authors should revise the paper based on the reviewers comments. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Partly Reviewer #2: Yes ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: No Reviewer #2: Yes ****** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: No ****** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ****** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: The presentation of the NNSGA-II algorithm focuses on optimizing RSU (Road Side Unit) deployment within the Internet of Vehicles (IoV) information transmission model. The exploration of various Levels of Service (LoS) reveals their effects on IoV reliability and RSU costs, culminating in a proposed bi-objective optimization framework. Here are my concerns and suggestions to the authors: 1. The presence of formatting issues with some equations detracts from the clarity of mathematical reasoning. 2. The description of the NNSGA-II algorithm could be enhanced by adding flowcharts or pseudocode for better understanding. 3. A need exists for more detailed examples and visualizations to illustrate the algorithm's practical applications, with current examples lacking robustness. 4. The model's adaptability to different road network types and limitations observed during simulations requires clarification. 5. The rationale behind selecting specific parameter values for mutation and crossover probabilities needs further explanation, alongside any sensitivity analysis conducted. 6. This paper develops a bi-objective optimization model utilizing the NNSGA-II algorithm for improved RSU deployment strategies in IoV systems. The effective comparison of the proposed model with benchmark methods highlights notable advantages in specific scenarios. The need for improvements in mathematical clarity, inclusion of visual aids, and detailed examples is crucial. Insights into parameter selection and model adaptability to various road types are encouraged. With these enhancements, the work is positioned to yield significant insights into practical applications in smart transportation systems. 7. The necessity exists for a detailed simulation comparison to elucidate the proposed model's performance. Further exploration of the model's algorithms is essential for bolstering claims of efficiency. 8. Expanding evaluation breadth to encompass various scenarios enhances robustness. 9. Increasing figure size is crucial for improved interpretation of key data and trends. 10. The adaptation of the model to distinct environmental scenarios warrants exploration. 11. Conducting a thorough cost-benefit analysis is critical for understanding economic impacts. An additional explanations or examples of the applied NSGA-II algorithm could help non-expert readers understand its implementation and significance. 12. While numerical results are mentioned, consider providing more details about the test scenarios, conditions, and parameters used in the simulations to enhance reproducibility and understanding of the results. Reviewer #2: This paper explores optimizing Road-Side Unit (RSU) deployment for Internet of Vehicles (IoV) based on different Line of Sight (LoS) conditions and IoV penetration rates. It aims to minimize the cost of RSU deployment while ensuring IoV reliability through a bi-objective optimization model. The reliability is measured by the proportion of online transmission distance below a certain threshold. The modified NSGA-II algorithm, with adjustments to crossover and mutation probabilities, is used to improve solution efficiency. Experimental results show the proposed model performs better in RSU-dominated scenarios and that NNSGA-II is more efficient than traditional algorithms by 10.01%. 1. Introduction should cover the background of the area, problem motivation, importance of problem, methodology used, results analysis and concluding remarks in a short note. 2. The authors should include a section for literature survey (Section II- Related work). 3. Authors should very clearly state how does your work advances the state of the art. At the end of Section II, the authors should give a brief summary of related work to show the difference and improvement of this work. Maybe including a table summarizing the related work could help identifying gaps that your work fills. 4. I suggest to keep a table at the end of section II. 5. Section II may be divided into subsections like conventional methods, cooperative methods, non-cooperative methods, online/offline methods and their merits and demerits. 6. The simplicity of Figure 1 is noted, and it is suggested that more details be incorporated to depict the communication between CVs, and RSUs. This addition would provide greater clarity to the reader regarding the entire system model. 7. This submission lacks a comprehensive discussion of pertinent works, notably omitting references to key sources such as a. "Contact duration-aware cooperative cache placement using genetic algorithm for mobile edge networks." Computer Networks 193 (2021): 108062. b. Service Caching and User Association in Cache Enabled Multi-UAV Assisted MEN for Latency-Sensitive Applications.” Computers and Electrical Engineering (Elsevier) (2024) ****** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: Yes: Ebrahim E. Elsayed Reviewer #2: No ******** [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. 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Revision 1
5 Nov 2024 Author Response Capital University of Economic and Business Beijing, China charles3000@cueb.edu.cn November 2, 2024 Dear Editors We thank the reviewers for their generous comments on the manuscript and have edited the manuscript to address their concerns. We add a section about Related work, focusing on the contributions of related literature and improvements of our model. Additionally, we provide more detailed descriptions of the model content and include figures of results. Furthermore, we add the description of the model's performance in different traffic scenarios. We believe that the manuscript is now suitable for publication in PLOS One. Dr. Guangtong Hu Ph.D. Candidate in Capital University of Economic and Business On behalf of all authors. Reviewer 1 (Ebrahim E. Elsayed) 1. The presence of formatting issues with some equations detracts from the clarity of mathematical reasoning. Answer: Thank you for your reminder. We check all the formulas and revise the format of Equations (15) and (16). 2. The description of the NNSGA-II algorithm could be enhanced by adding flowcharts or pseudocode for better understanding. Answer: We add a description of the flowchart for the NNSGA-II algorithm in Figure 3. 3. A need exists for more detailed examples and visualizations to illustrate the algorithm's practical applications, with current examples lacking robustness. Answer: We add visual results (Fig 5) and detailed descriptions to illustrate the practical application of the model and algorithm. 4. The model's adaptability to different road network types and limitations observed during simulations requires clarification. Answer: We add the model's adaptability to different types of road networks in Section 5.2 and discuss the limitations observed during the simulation process in the Conclusion. 5. The rationale behind selecting specific parameter values for mutation and crossover probabilities needs further explanation, alongside any sensitivity analysis conducted. Answer: In our study, the selection of specific mutation and crossover probability parameters is based on extensive experimental data. We conduct a wide-ranging sensitivity analysis to verify the model's sensitivity to different parameter values. Figure 9 illustrates the sensitivity analysis of mutation and crossover probabilities. 6. This paper develops a bi-objective optimization model utilizing the NNSGA-II algorithm for improved RSU deployment strategies in IoV systems. The effective comparison of the proposed model with benchmark methods highlights notable advantages in specific scenarios. The need for improvements in mathematical clarity, inclusion of visual aids, and detailed examples is crucial. Insights into parameter selection and model adaptability to various road types are encouraged. With these enhancements, the work is positioned to yield significant insights into practical applications in smart transportation systems. Answer: We have addressed the reviewer's comments by improving mathematical clarity, adding visual aids and detailed examples, and providing insights into parameter selection and model adaptability to various road types. These enhancements significantly strengthen the practical applicability and robustness of our work. 7. The necessity exists for a detailed simulation comparison to elucidate the proposed model's performance. Further exploration of the model's algorithms is essential for bolstering claims of efficiency. Answer: We demonstrate the performance of the proposed model in different traffic scenarios compared to other models in Section 5.2, showcase the superior performance of the proposed algorithm through comparisons in Section 5.3, and present the results of sensitivity analysis for various parameters in Section 5.4. 8. Expanding evaluation breadth to encompass various scenarios enhances robustness. Answer: We compare six different traffic states, ranging from smooth to extremely congested, in Section 5.2. 9. Increasing figure size is crucial for improved interpretation of key data and trends. Answer: Thank you for your reminder. We increase the size of all figures. 10. The adaptation of the model to distinct environmental scenarios warrants exploration. Answer: We compare six different traffic states, ranging from smooth to extremely congested, in Section 5.2. 11. Conducting a thorough cost-benefit analysis is critical for understanding economic impacts. An additional explanations or examples of the applied NSGA-II algorithm could help non-expert readers understand its implementation and significance. Answer: We add a discussion on the cost-benefit analysis and socioeconomic impacts of RSU deployment optimization in the introduction section. In Section 4, we provide additional descriptions and explanations of the NNSGA-II algorithm. 12. While numerical results are mentioned, consider providing more details about the test scenarios, conditions, and parameters used in the simulations to enhance reproducibility and understanding of the results. Answer: We add details about the test scenarios, conditions, and parameters used in the simulations in Section 5.1. Reviewer 2 (Anonymous) 1. Introduction should cover the background of the area, problem motivation, importance of problem, methodology used, results analysis and concluding remarks in a short note. Answer: We add the results analysis and conclusions in the introduction section. 2. The authors should include a section for literature survey (Section II- Related work). Answer: Thank you for your reminder. We add the Section II - Related work. 3. Authors should very clearly state how does your work advances the state of the art. At the end of Section II, the authors should give a brief summary of related work to show the difference and improvement of this work. Maybe including a table summarizing the related work could help identifying gaps that your work fills. Answer: We summarize the related work and describe the improvements of our work at the end of Section 2. Additionally, we add a table to highlight the limitations of related work and our solutions. 4. I suggest to keep a table at the end of section II. Answer: In Section 2, we add a table to highlight the limitations of related work and our solutions. 5. Section II may be divided into subsections like conventional methods, cooperative methods, non-cooperative methods, online/offline methods and their merits and demerits. Answer: We categorize the related literature into four different types: Integer Programming, Heuristic Algorithms, Mathematical Modeling and Optimization Algorithms, Hybrid Management Strategies. 6. The simplicity of Figure 1 is noted, and it is suggested that more details be incorporated to depict the communication between CVs, and RSUs. This addition would provide greater clarity to the reader regarding the entire system model. Answer: Thank you for your reminder. We re-draw Figure 1, and adding more details. 7. This submission lacks a comprehensive discussion of pertinent works, notably omitting references to key sources such as: a. "Contact duration-aware cooperative cache placement using genetic algorithm for mobile edge networks." Computer Networks 193 (2021): 108062. b. Service Caching and User Association in Cache Enabled Multi-UAV Assisted MEN for Latency-Sensitive Applications.” Computers and Electrical Engineering (Elsevier) (2024) Answer: We conduct a thorough review of the literature and include citations in Section 5. Attachments Attachment Submitted filename: Response Letter.docx https://doi.org/10.1371/journal.pone.0315716.r002
1 Dec 2024 Decision Letter - Agbotiname Lucky Imoize, Editor Road side unit deployment optimization for the reliability of Internet of Vehicles based on information transmission model PONE-D-24-39904R1 Dear Dr. Hu, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Agbotiname Lucky Imoize Academic Editor PLOS ONE Additional Editor Comments (optional): The authors have revised the paper accordingly. Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: (No Response) ******** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: (No Response) ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: (No Response) ****** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: (No Response) ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: (No Response) ****** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: The paper has been suitably revised. I recommend acceptance. I am happy with the responses and edits of the manuscript, and they address all of my concerns. ****** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: Yes: Ebrahim E. Elsayed ******** https://doi.org/10.1371/journal.pone.0315716.r003
Formally Accepted
8 Dec 2024 Acceptance Letter - Agbotiname Lucky Imoize, Editor PONE-D-24-39904R1 PLOS ONE Dear Dr. Hu, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps. Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. If we can help with anything else, please email us at customercare@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Mr. Agbotiname Lucky Imoize Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0315716.r004

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