The Distributed HTAP Architecture for Real-Time Analysis and Updating of Point Cloud Data
Round 1
Reviewer 1 Report
In view of the situation that existing systems for point cloud data management often fail to ensure timely updates or point cloud data cannot be effectively refreshed, this manuscript proposes a distributed hybrid transactional/analytical processing (HTAP) architecture designed for efficient management and real-time processing of point cloud data. Finally, this manuscript provides a qualitative and quantitative evaluation of the processing architecture, and analyzes the evaluation results. The manuscript is logically clear, but there are still some details. The specific problems are as follows:
1. In Chapter 3, it is stated at the beginning that the operating algorithm of the data pipeline and the update process from collecting LiDAR data from vehicles to the final data will be described in Section 3.2. However, these contents are described in Sections 3.3 and 3.4.
2. In Figure 4, the second decision box does not have a corresponding error branch, and the subsequent textual does not clarify what happens when the difference does not exceed the threshold.
3. The meaning of "ref_id" is not explained in the paper.
4. There is no performance comparison of this architecture with other architectures.
In conclusion, the manuscript is innovated and interesting, it could be published with minor changes.
Author Response
Dear Reviewer,
We sincerely appreciate your thorough review of our paper and providing valuable suggestions for improvement. We have carefully reviewed your comments and made the necessary revisions accordingly. Detailed information about the modifications can be found in the "Response to Reviewer 1 Comments.docx" file.
Best regards, Author Juhyun Kim
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Thanks to the authors for their ultimate effort. There are a few points that need to be addressed. Here are the specific recommendations for improvement:
• The paper's title is too long. Ensure you shorten it by using more specific keywords that reflect your research topic.
• The main contribution of this research work is unclear. Summarize your contributions in bullet points to help readers understand them.
• I encourage the authors to include a simple figure below the introduction, providing background on using point cloud data in autonomous driving. This will help the reader understand the system architecture presented in Figure 1.
• In Figure 1, why was the system architecture divided into three parts?
• Some mentioned technologies, such as the Kafka broker server, need to be defined.
• What are the main differences between Worker Node-1, Worker Node-2, and Worker Node-3, as illustrated in Figure 2? They appear to have similar parameters.
• The authors should explain Figure 3 in more detail.
• Figure 8 contains four images: two on the top and two on the bottom. Could you explain them? How were these images generated?
• Figures 3, 10, 11, and 12 are fuzzy; please enhance their quality.
• The "Related Work" section is shallow and lacks sufficient information relevant to the research topic. Ensure you include more pertinent research.
• Figure 5 is not explained.
• Pseudocode should be presented as text, not as a figure (see Figure 6).
• What are the limitations of this research?
Author Response
Dear Reviewer,
We sincerely appreciate your thorough review of our paper and providing valuable suggestions for improvement. We have carefully reviewed your comments and made the necessary revisions accordingly. Detailed information about the modifications can be found in the "Response to Reviewer 2 Comments.docx" file.
Best regards, Author Juhyun Kim
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
1. More quantitative evaluation results should be provided to prove that the proposed archiechture can achieve real-time processing.
2. Performance comparisons should be made with related technologies.
Author Response
Dear Reviewr,
We sincerely appreciate your review.
We have carefully considered the feedback and made the necessary revisions accordingly.
Best regards,
Author
Author Response File: Author Response.pdf
Reviewer 2 Report
Thank you
Author Response
Thank you for your review
