Comprehensive Evaluation of Energy Efficiency Based on TOPSIS for Protocols of Collaborative Wireless Sensor Networks

Li, Jian; Zhou, Jianzhong; Zhang, Yongchuan

doi:10.1155/2015/640736

Cited by 2 publications

(3 citation statements)

References 17 publications

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“…OCER and Extended OCER, by considering different parameters. In [17], researchers put forward a new neutrosophic‐based decision‐making technique with multiple‐parameter similarity combined with weight. In [18], a TDMA‐based routing protocol is given for improving the performance in terms of energy in WBAN.…”

Section: Related Workmentioning

confidence: 99%

AHP–neutrosophic decision model for selection of relay node in wireless body area network

Bilandi¹,

Verma²,

Dhir³

2020

CAAI trans. intell. technol.

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The medical health systems empowered by wireless body area networks (WBANs) are becoming a reliable technology with unmatched facilities for personalised health monitoring and managing real‐time health issues. A WBAN is primarily composed of a miniature, and smart devices called sensors that are worn in, on, or around the human body. In recent years, research has been mainly centred towards the reduction of the energy consumption and stability of the network. The selection of the relay node is one of the foremost issues for balancing the energy consumption in WBAN. To overcome this issue, the authors propose a hybrid analytic hierarchy process–neutrosophic method for making the decision of the relay node selection, in which the analytic hierarchy process (AHP) technique calculates the weights for different criteria and forwards them to the neutrosophic technique which finds out the best alternative solution or choice which is closest to the ideal solution. A detailed analysis is carried out on multi‐criteria decision‐making techniques by comparing the proposed AHP–neutrosophic and AHP techniques taking into account various criteria and alternatives. The experimental outcomes of this research indicate a significant reduction in terms of energy consumption and enhanced overall network‐stability.

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Section: Related Workmentioning

confidence: 99%

AHP–neutrosophic decision model for selection of relay node in wireless body area network

Bilandi¹,

Verma²,

Dhir³

2020

CAAI trans. intell. technol.

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“…The most suitable alternative should be closest to the positive ideal solution and the farthest from the negative ideal solution. At present, with the deepening realization about TOPSIS, some extended TOPSIS techniques have been used widely for MADM problems to overcome the vagueness in the judgments made by the assessors [11][12][13][14][15][16][17][18][19][20][21]. In order to overcome the problem of index weight calculation, AHP is the main auxiliary method of TOPSIS, and fuzzy sets are introduced together to facilitate the quantification of the two pairs of indicators [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

“…So the ANP is the development and supplement of AHP. In addition, the method of comprehensive evaluation, principal component analysis, and other methods are all important methods to calculate weights, which are applied in TOPSIS [21][22][23]. On the other hand, the optimal or worst value for every attribute should be selected, and a quantitative measure method should be constructed to compare with each other.…”

Section: Introductionmentioning

confidence: 99%

A Novel TOPSIS Method Based on Improved Grey Relational Analysis for Multiattribute Decision‐Making Problem

Wei-guo

2019

Mathematical Problems in Engineering

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Multiattribute decision-making (MADM) problem is difficult to assess because of the large number of attribute indices and the diversity of data distribution. Based on the understanding of data dispersion degree, a new grey TOPSIS method for MADM is studied. The main idea of this paper is to redefine the grey relational analysis through the dispersion of data distribution and redesign the TOPSIS by using the improved grey relational analysis. As a classical multiattribute decision analysis method, traditional TOPSIS does not consider the data distribution of the degree of dispersion and aggregation when it is compared with the optimal and worst alternative solutions. In view of the limitations of traditional TOPSIS, this paper has made two major improvements to TOPSIS. Firstly, the new grey relational analysis is applied to evaluate the grey positive relational degree between each alternative and the optimal solution and compute the grey negative relational degree between each alternative and the worst solution. Secondly, the weights of every attribute index about the optimal and worst solutions are put forward based upon the distance standard deviation and the average distance. Finally, the comprehensive grey TOPSIS is utilized to analyze the ranking of weapon selection problem. The numerical results verify the feasibility of the improved grey relational analysis and also highlight the practicability of the grey comprehensive TOPSIS.

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Comprehensive Evaluation of Energy Efficiency Based on TOPSIS for Protocols of Collaborative Wireless Sensor Networks

Cited by 2 publications

References 17 publications

AHP–neutrosophic decision model for selection of relay node in wireless body area network

AHP–neutrosophic decision model for selection of relay node in wireless body area network

A Novel TOPSIS Method Based on Improved Grey Relational Analysis for Multiattribute Decision‐Making Problem

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