Abstract

Many application fields initiate using wireless sensor network (WSN), and the evaluation for its performance becomes an important topic, which can help the decision‐maker to find the deficiency of the current WSN or seek the best WSN. There exist mixed multiple attributes in the WSN performance evaluation process, for example, some evaluation indicators can be expressed as interval numbers, while others can be expressed as linguistic variables, so it is necessary to explore the evaluation model based on mixed multiattribute decision‐making (MADM). Considering the specific evaluation purpose and requirements for different enterprises, this paper puts forward an indicator selection method and a subjective weighting method based on the rough set theory. After that, based on the transformation of mixed attributes into the unified intuitionistic fuzzy numbers (IFNs), an objective weighting method based on intuitionistic fuzzy entropy is proposed. Meanwhile, the combined weights of indicators are obtained by synthesizing the subjective and objective weights. Subsequently, in order to evaluate WSN performance objectively, an integrated comprehensive evaluation framework is proposed, which includes single evaluation, compatibility test, combination evaluation, and consistency test. The paper gives specific models and calculation steps in detail. Finally, it provides a case study to explain the application of the proposed indicator selection method and the evaluation models, which provide new ideas and references for WSN performance evaluation.

Highlights

  • wireless sensor network (WSN) is a combination of multiple sensor nodes, which play a role in real-time sensing, collecting, processing, and transmitting the sensing object information

  • How to establish a more scientific comprehensive evaluation model based on the mixed multiattribute decision-making (MADM) method? This study mainly focuses on the above two aspects, and its contributions are as follows: (1) A rough set method for WSN performance evaluation indicator selection is proposed, which can make full use of the experience of the field experts and provide relatively complete indicators that meet the needs of decision-makers

  • When all the values of attributes are uniformly transformed into intuitionistic fuzzy numbers (IFNs), WSN performance evaluation becomes an intuitionistic fuzzy MADM problem

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Summary

Introduction

WSN is a combination of multiple sensor nodes, which play a role in real-time sensing, collecting, processing, and transmitting the sensing object information. Based on the mixed MADM method, the establishment of a comprehensive evaluation model of WSN performance is more realistic, and the conclusion will be more scientific. Xu et al [53] proposed an approach that aggregates the heterogeneous information into IFNs by group evaluation in rating system and TOPSIS and applied intuitionistic weighted arithmetic mean operator for ranking the alternatives. This study mainly focuses on the above two aspects, and its contributions are as follows: (1) A rough set method for WSN performance evaluation indicator selection is proposed, which can make full use of the experience of the field experts and provide relatively complete indicators that meet the needs of decision-makers.

Indicator Selection Based on Rough Set
Indicator Weighting Based on Rough Set and Intuitionistic Fuzzy Entropy
Evaluation Model Based on Intuitionistic Fuzzy MADM
A Case Study
A2 A3 A4 A5
Conclusions
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