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Peer-Review Record

Redundancy Mitigation Mechanism for Collective Perception in Connected and Autonomous Vehicles

Future Internet 2023, 15(2), 41; https://doi.org/10.3390/fi15020041
by Wellington Lobato 1,*, Paulo Mendes 2, Denis Rosário 3, Eduardo Cerqueira 3 and Leandro A. Villas 1
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Future Internet 2023, 15(2), 41; https://doi.org/10.3390/fi15020041
Submission received: 20 December 2022 / Revised: 19 January 2023 / Accepted: 20 January 2023 / Published: 22 January 2023
(This article belongs to the Special Issue Future Intelligent Vehicular Networks toward 6G)

Round 1

Reviewer 1 Report

The authors are asked to elaborate on the metrics considerd by them in Section 4 with respect to metrics used in Section VI.C in https://ieeexplore.ieee.org/abstract/document/9762711, explain the differences and motivate the use of the former ones.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

The manuscript proposes a reliable redundancy mitigation mechanism for collective perception services to reduce the transmission of inefficient messages.

The manuscript is nicely written.

The following comments to be addressed:

adding some more recent work to section 2.1 and 2.4

https://ieeexplore.ieee.org/abstract/document/9910433

https://ieeexplore.ieee.org/abstract/document/9445064

 

At the end of line 381, would be great to add a numerical example to show how the algorithm operates.

 

In the simulation studies: Hoe the baseline is defined? What are the evaluation metrics? any comparison against the other similar works?

 

There are some inconsistencies in the format of references. For example, vol and issue are missing for some. 

Author Response

Please see the attachment.

 

Author Response File: Author Response.docx

Reviewer 3 Report

To reduce the transmission of inefficient messages, this paper proposes an effective mechanism for mitigating redundancy in collective perception services. Although this paper is very interesting, there are a few points that I would like to raise:

·         The authors tend to place excessive references within the text. It does not contribute to the content of the paper. It is sufficient to cite one or two references.

·         Are the regions based on the RSUs?

·         There is a need to elaborate on this sentence  "The authors’ results demonstrated a decrease in the overall burden of communication overhead while preserving the system’s information propagation dependability"

·         The literature review has been applied in sections 2.2., 2.3., and 2.4 in an inconsistent manner. The authors should assess the review in accordance with a consistent storyboard. Assessing each paper individually does not actually help the paper's flow or consistency.

·         It is necessary for the authors to explain why they selected the simulation parameters they did.

·         ITS requires real-time processing as one of its key requirements. Can this approach be applied to real-time processing?

·         False information can also adversely affect such a system, as mentioned in the open research challenges. Do the advantages of this system outweigh the challenges?

·         As this approach is very consuming, I expected to see one of the performance metrics discussed regarding latency or computation.

 

·         I believe that the efficiency of the results needs to be justified. I understand that the vehicle has to process more data to ensure the accuracy of the information; thus, I am not sure how the system enhanced the efficiency. It is important to emphasise this point. 

Author Response

Please see the attachment.

 

Author Response File: Author Response.docx

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