Efficient Method for Continuous IoT Data Stream Indexing in the Fog-Cloud Computing Level

Round 1

Reviewer 1 Report

Dear Authors, your manuscript is well structured however, following comments should be accommodated, prior to further processing of the article.

1)      Refer to whole article: Similarity of the article is higher i.e. 22%.

2)      Refer to author’s affiliation: Authors affiliation section need careful review and necessary corrections.

3)      Refer to abstract: No doubt IoT is very famous term however, authors must keep in mind that article is also read by beginners of the domain and novice readers. Therefore, it is highly recommended to describe all short forms at their first occurrence. Recheck and update all short forms / abbreviations accordingly.

4)      Refer to abstract: Abstract is poorly written and needs to be rewritten with more clarity and conciseness.

5)      Refer to Introduction: Referencing style is very poor. These are not properly managed.

6)      Refer to line # 54: Authors have state that …. IoT data stream and make rapid the similarity query search… Authors need to recheck and elaborate “similarity query search”?

7)      Refer to line # 57: authors have stated that … the fog layer is divided into three levels: clustering fog level, clusters processing fog levels and indexing fog level… Whereas, figure 1 does not indicate any levels in it. Synchronization of figure and text is required. Authors should describe where these three levels are shown (like is figure 2).   

8)      Refer to contribution: Authors have suggested applying Density-Based Spatial Clustering of Applications with Noise for clustering because it is the most suitable algorithm for grouping diverse IoT data into homogeneous and high density clusters. This algorithm was initially proposed in 1996. If authors have used already developed algorithm then where is their contribution? Authors need to clarify their contribution.

9)      Refer to figure 4 - 14: Figures size is a little bit smaller.

Good luck.

Dear Authors, your manuscript is well structured however, following comments should be accommodated, prior to further processing of the article.

1)      Refer to whole article: Similarity of the article is higher i.e. 22%.

2)      Refer to author’s affiliation: Authors affiliation section need careful review and necessary corrections.

3)      Refer to abstract: No doubt IoT is very famous term however, authors must keep in mind that article is also read by beginners of the domain and novice readers. Therefore, it is highly recommended to describe all short forms at their first occurrence. Recheck and update all short forms / abbreviations accordingly.

4)      Refer to abstract: Abstract is poorly written and needs to be rewritten with more clarity and conciseness.

5)      Refer to Introduction: Referencing style is very poor. These are not properly managed.

6)      Refer to line # 54: Authors have state that …. IoT data stream and make rapid the similarity query search… Authors need to recheck and elaborate “similarity query search”?

7)      Refer to line # 57: authors have stated that … the fog layer is divided into three levels: clustering fog level, clusters processing fog levels and indexing fog level… Whereas, figure 1 does not indicate any levels in it. Synchronization of figure and text is required. Authors should describe where these three levels are shown (like is figure 2).   

8)      Refer to contribution: Authors have suggested applying Density-Based Spatial Clustering of Applications with Noise for clustering because it is the most suitable algorithm for grouping diverse IoT data into homogeneous and high density clusters. This algorithm was initially proposed in 1996. If authors have used already developed algorithm then where is their contribution? Authors need to clarify their contribution.

9)      Refer to figure 4 - 14: Figures size is a little bit smaller.

Good luck.

Author Response

Please see attached the responses. Thank you

Author Response File: Author Response.pdf

Reviewer 2 Report

 

1.       First line in abstract should have ‘produce’ instead of ‘, produces’.

2.       Generally the term ‘spatio-temporal’ is used instead of ‘spatial-temporal’.

3.       Do the authors mean the same thing when the refer to the terms ‘fog-cloud level’ and ‘fog-cloud architecture’.  It is suggested that either the clear line of differentiation be drawn, or mentioned that the use in the manuscript is interchangeable, or best would be to use only one phrase consistently.  This will also improve the readability of the manuscript.  Notably, the phrase used in the title is used only one time in the entire manuscript!

4.       In order to prevent eye-strain and give manuscript a more professional look, it is recommended that only the same shades of colors be used for all graphs rather than keep on changing it for graphs from figure to figure.

5.       In order to maintain quality, it is recommended that the authors prefer citing only the duly reviewed, accepted, and published research work.  At least, the reference corresponding to the peer-reviewed published version of the arXiv paper should be included wherever possible.

6.       All the figures with graphical content need to have captions for ‘both’ axes in addition to the labels for the axes.

7.       It is recommended that the entire manuscript be thoroughly proofread, preferably by a native English speaker, for the correct usage of the English language in the manuscript.

8.       It is highly recommended that the authors present a ‘table’ of comparison of the proposed work with similar research works and state-of-the-art research studied as part of the literature review.  This will go a long way in emphasizing the research gaps and highlighting the specific contributions of the proposed work.  Irrespective of the presented discussion, this should be done in terms of contrast and comparison of approach as well as the contrast and comparison of the results.

9.       The corresponding long forms should accompany all the first usages of abbreviations (in abstract and the remaining manuscript).  At the same location, the words of the long form should be suitably written in Title Case.  Either the style of ‘long form followed by the abbreviation’ (preferably) or the ‘abbreviation followed by the long form’ should be consistently used throughout the manuscript.  After the abbreviation has been defined at the first instance, the subsequent text of the manuscript should not unnecessarily mention the abbreviation and long form again, and rather only the abbreviation should be used.

10.    How did the authors assured that the creation of data streams from data sets did not result in bias?  How were the data streams created?  Who all created it?  Notably these data streams have been, in turn, used for experimentation, proposing the results, and advocating the robustness of the proposal of the manuscript.

11.    The name of datasets need to be mentioned consistently throughout the manuscript, including figures, text as well as Table 2.

12.    The resolution of figures needs to be specifically improved.

13.    Consistency needed for usage of phrases ‘ieee access’, ‘Ieee Access’, and ‘IEEE Access’.

As above.

Author Response

Please see attached our responses. Thank you

Author Response File: Author Response.pdf

Reviewer 3 Report

As mentioned above "Did you detect inappropriate self-citations by authors?" there are many citations without coressponding DOI or URL. => Need to fullfil.

Author Response

Please see below our responses. Thank you

Response to Reviewer 3

Comments and Suggestions for Authors

 

• As mentioned above "Did you detect inappropriate self-citations by authors?" there are many citations without coressponding DOI or URL. => Need to fullfil.
• Thank you for your comment. In the manuscript, references were generated by BibTex.

Reviewer 4 Report

Major Comments:

1)Lack of Clarity and Organization: The paper lacks clarity and proper organization in some sections, making it difficult to follow the flow of information. It would greatly benefit from better structuring, with clear subsections and headings to guide the reader through the content. Additionally, the introduction should provide a more detailed overview of the indexing problem and the significance of the proposed methods.

2) Inadequate Explanation of Indexing Methods: The authors briefly mention the four proposed indexing methods but fail to provide sufficient details regarding their underlying principles and techniques. A more elaborate description of each method, along with relevant equations or algorithms, is necessary to help readers understand the key aspects of these approaches.

3) Lack of Comparative Analysis: While the authors compare the performance of different indexing methods in terms of various metrics, such as the number of indexes, comparisons, and energy consumption, the paper lacks a comprehensive comparative analysis. It would be helpful to include a clear evaluation framework that directly compares the strengths and weaknesses of each method. This would enhance the paper's contribution and assist readers in understanding the trade-offs between the proposed approaches.

4)  Based on the literature review, the current research work addresses some of the limitations, but not all of them.

·         Existing approaches for indexing IoT data: The current research proposes a fog-cloud computing architecture specifically designed for indexing continuous and heterogeneous data in IoT systems. This addresses the limitation of existing approaches not efficiently handling the dynamic nature and continuous growth of IoT data.

·         Wang et al.'s CR-index limitation: The current research does not directly address this limitation. It does not mention indexing data with higher dimensions or unique dimensions, so it may not provide a solution for this specific limitation.

·         Multi-attribute indexing limitation: The current research does not explicitly mention multi-attribute indexing. It focuses on clustering the data and indexing the resulting clusters. Therefore, it may not provide a direct solution for this limitation.

·         Doan et al.'s indexing model based on timestamps limitation: The current research does not directly address this limitation. It focuses on clustering and indexing based on DBSCAN, without explicitly mentioning the use of timestamps for indexing.

·         SeaCloudDM latency problem limitation: The current research proposes a fog-cloud computing architecture that can potentially address the latency problems faced by cloud-based methods like SeaCloudDM. However, it does not explicitly discuss or compare the latency issue, so its effectiveness in solving this limitation is unclear.

 

In summary, while the current research addresses some of the limitations mentioned, it does not directly tackle all of them. It focuses on proposing a fog-cloud computing architecture for indexing continuous and heterogeneous data in IoT systems, emphasizing clustering, and indexing based on DBSCAN.

 

Minor Comments:

 

1)      Dataset Description: The paper provides a brief description of the datasets used for experimental evaluation. However, it would be beneficial to include additional details, such as the size, dimensionality, and characteristics of the datasets. This information would enable readers to better understand the suitability of the proposed methods for different types of data streams.

2)      Figures and Tables: The paper includes several figures and tables to support the experimental results. However, some of the figures lack proper labels, making it challenging to interpret the presented data. Additionally, it would be helpful to provide captions that explain the significance of each figure and table.

3)      Grammar and Language: The paper contains numerous grammatical errors, typos, and awkward sentence constructions. A thorough proofreading and language editing should be undertaken to enhance the overall readability and clarity of the manuscript.

 

 

Conclusion: In conclusion, the paper addresses an important problem of the indexing of continuous and heterogeneous data. While the work has potential, there are several areas that require improvement, including clarity of presentation, detailed explanation of indexing methods, comprehensive comparative analysis, and addressing minor issues related to figures, tables, and grammar. Addressing these concerns will significantly strengthen the paper and make it more accessible and valuable to the readers.

The paper contains numerous grammatical errors, typos, and awkward sentence constructions. It requires thorough proofreading and language editing to improve the overall readability and clarity of the manuscript

Author Response

Please see attached our responses. Thank you

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Dear Authors,

I appreciate your efforts. My comments are satisfactorily addressed and I have no more comments.

Good luck.

Reviewer 2 Report

The suggestions of the previous review round have been well-executed by the authors.

None specifically.

Reviewer 4 Report

The authors have addressed the reviewer's comments very well and significantly improved the manuscript.