Fuzzy‐based techniques for clustering in wireless sensor networks (WSNs): Recent advances, challenges, and future directions
Sandeep Verma, Sakshi Bhatia, Sherali Zeadally, Satnam Kaur
Abstract
Summary A wireless sensor network (WSN) is a network of tiny sensors deployed to collect data. These sensors are powered with batteries that have limited power. Recharging and/or replacement of these batteries, however, are not always feasible. Over the past few years, WSN applications are being deployed in diverse fields such as military, manufacturing, healthcare, agriculture, and so on. With the ever‐increasing applications of WSNs, improving the energy efficiency of the WSNs still remains to be a challenge. Applying fuzzy logic to the problem of clustering exploits the uncertainty associated with the factors that affect the lifetime of these sensors and enables the development of models that would improve their performance in real‐world applications. We present a comprehensive review of various fuzzy‐based techniques for clustering in WSNs whose main goal is to optimize energy usage in WSNs while simultaneously improving their overall performance.