Optimal Base Station Location for Network Lifetime Maximization in Wireless Sensor Network
Round 1
Reviewer 1 Report
The paper proposes a base station location problem for a multi-hop clustering sensor network to conserve energy consumption for network lifetime maximization in WSN. The paper does not merit publication in its current form. My comments are summarized as follows
- In Abstract it is mentioned that: “Implementing an evolutionary algorithm for this optimization problem simplifies the problem with improved computational efficiency.” What computational tools are used to map the complexity of algorithm.
- What is meant by Optimal base station location. What method have you chosen to prove that the objective function that is defined finds global solution as per your solution. Proof of optimality is necessary for the claim. Also, the authors mention in Line 113 as “show that a good optimal location”. Can you please elaborate further on good and bad optimal locations.
- Authors are advised to refer to any good journal paper and see how equations shall be written. Most equations are not aligned e.g., (7)-(9), and the symbols e.g. summation are not as per standard.
- The paper needs extensive proof reading and improvement in organization and style. Only few issues are pointed out among many
- wireless sensor network technology (WSN) change to wireless sensor network (WSN) technology. Also some acronyms are defined with capital letters while others with small letters. Need better consistency.
- Line 31: Missing space in reference, “monitoring environment[1,2],”
- AoI not defined at first use.
- Line 86: why ‘E’ is capital in , “Efficient energy-saving”
- Line 93: consider changing “table 1.” To Table 1.
- Line 102: “Tamandani and Bokhari [16]”, however that paper seems to have third author as well. Also same issue in other place e.g., “Li and Dong [27]”
- Consider rewriting , “Shah [28] the authors proposed an algorithm for the optimum position”.
- 3.1 needs to be continuous and possibly supported using a flowchart.
- Mathematically symbols are not consistent. e.g., equation (1), and definitions on line 174 are not same.
Author Response
Dear Reviewer,
Please see the attachment
Author Response File: 
Author Response.pdf
Reviewer 2 Report
The paper is generally well written and structured.
Justify your recommendation with concrete evidence and specific examples.
Describe the Novelty of the work.
Illustrate and discuss why the Crossover elitist conservation genetic algorithm is preferred in this Work?
Author Response
Dear Reviewer,
Please see the attachment
Author Response File: Author Response.pdf
Reviewer 3 Report
ELECTRONICS
The authors propose an optimization approach to base location task to maximize lifetime of the system.
In the introduction, at first, the authors define a wireless sensor network and presnet some challenges connected with it. In the remaining part of the introduction, they list various approaches to the topic of optimal placement of both nodes and sensors, identifying in a single sentence pros of their approach.
The latter is found to be insufficient, and the authors are encouraged to give some clear statements, using say bullet list, concerning novelty and contribution topics, to make the readers aware of the value of the paper.
Sections 2.1 and 2.2 do not have a common background story and it is hard to the reader, to identify the connection between optimizing base station locations using P-medians and other approaches, with a huge hop to GAs, without identifying the obvious drawback of the first ones.
In the formal definition of the optimization problem in (7) and below, the authors should add ARGUMENTS (decision variables' symbols) below MAX, to allow the readers to understand the complicated nature of the problem, and their support to use GAs instead of convex programming techniques.
It is advantageous that the authors compare their results with other algorithms, as it sheds some light on their performance. Could you make a larger simulation campaign, though, just to present mean values with plus minus 1 sd to see which method is more, say, repeatible?
Author Response
Dear Reviewer,
Please see the attachment
Author Response File: Author Response.pdf
Reviewer 4 Report
I found the article to be interesting, insightful and notably well written. This research paper contributes to the literature by using an improved algorithm based on the Crossover Elitist Conservation Genetic Algorithm to optimize the base station location . I think the authors have tried to put their findings into context, however the algorithm used are old (but improved) , a new metaheuristics algorithms for better results is required.
Author Response
Dear Reviewer,
Please see the attachment
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
While the authors have put in an effort to improve the paper, still the paper does not merit publication. Most of my concerns are still not addressed.
Technically, I see that you are somehow equating good, and best (optimal) solutions. If the algorithms yield good results among the compared solutions, then write the paper accordingly. However, if the solution is best(optimal), prove the convexity mathematically.
Writing of the paper makes the paper very rudimentary. e.g. inconsistency in writing: Abstract, “The increased demand for Wireless Sensor Networks in various applications ….. efficiency in wireless sensor networks”, also in Abstract, “This paper proposed an…” see the tense structure used for abstract. Equations are still not aligned e.g. (7)-(9). The paper needs to improve considerably in writing an organization aspect.
Author Response
Dear editor (Jeff Xu),
First, we express our deep appreciation to the Editor. Thank you for giving us the second revision opportunity. Second, we are very grateful to the reviewers for their comments. The reviewers are quite precise and dedicated so much to our MS. The comments are very professional and constructive, and they are important for the improvement of our MS quality. We are lucky to receive the reports from such experts. Now, we have made a major revision on our MS according to the comments. We hope our revision can make the reviewers satisfied, but if the reviewers still have questions about our work, we are happy to answer them and make further revisions to our MS.
Please see the attachment
Author Response File: Author Response.pdf
Reviewer 3 Report
Thank you for incorporanting the changes, and presenting a nice comparison between your and the other results. As far as the argument to the optimization task is considered, I meant to ask you to include the argument under MAX/MIN functions, in the style \max_{x} f(x), so that the readers can follow your ideas and identify that x is the actual decision variable. This is my only comment here, and that is why a minor revision is selected. Good luck with the review process.
Author Response
Dear editor (Jeff Xu),
First, we express our deep appreciation to the Editor. Thank you for giving us the second revision opportunity. Second, we are very grateful to the reviewers for their comments. The reviewers are quite precise and dedicated so much to our MS. The comments are very professional and constructive, and they are important for the improvement of our MS quality. We are lucky to receive the reports from such experts. Now, we have made a major revision on our MS according to the comments. We hope our revision can make the reviewers satisfied, but if the reviewers still have questions about our work, we are happy to answer them and make further revisions to our MS.
The following are the reviewer’s comments in italic type and our response in normal type.
Please see the attachment
Author Response File: Author Response.pdf
Round 3
Reviewer 1 Report
I am giving it an accept, but note that moderate English changes are still required.
This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.
