{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T04:18:48Z","timestamp":1750306728176,"version":"3.41.0"},"reference-count":32,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2014,11,25]],"date-time":"2014-11-25T00:00:00Z","timestamp":1416873600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["SIGBED Rev."],"published-print":{"date-parts":[[2014,11,25]]},"abstract":"<jats:p>Wireless sensor network (WSN) consists of low size, power constrained nodes that sense the environment and communicate this information through wireless links. There are a number of research issues in WSN with energy efficiency being one of the prime issues for WSN applications. In clustering-based routing protocols, cluster head selection has significant effect on performance of the protocol, along with routing technique. Game theory as a mathematical notion, being able to analyze interactive decision situations, is applicable to a wide spectrum within WSN. It can assist in designing more efficient protocols. This article surveys the application of game theory in wireless sensor network protocols, specifically in the domain of communication protocols involving cluster formation i.e. clustering protocols in WSN and how it optimizes the functioning of these protocols.<\/jats:p>","DOI":"10.1145\/2692385.2692386","type":"journal-article","created":{"date-parts":[[2014,11,26]],"date-time":"2014-11-26T14:51:56Z","timestamp":1417013516000},"page":"8-18","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["A survey on wireless sensor network clustering protocols optimized via game theory"],"prefix":"10.1145","volume":"11","author":[{"given":"Surabhi","family":"Midha","sequence":"first","affiliation":[{"name":"Dr. B.R. 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