Open AccessEnergy efficient clustering protocol based on K‐means (EECPK‐means)‐midpoint algorithm for enhanced network lifetime in wireless sensor network
Author(s) -
Ray Anindita,
De Debashis
Publication year - 2016
Publication title -
iet wireless sensor systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.433
H-Index - 27
eISSN - 2043-6394
pISSN - 2043-6386
DOI - 10.1049/iet-wss.2015.0087
Subject(s) - cluster analysis , wireless sensor network , base station , midpoint , computer science , algorithm , energy consumption , efficient energy use , centroid , protocol (science) , euclidean distance , energy (signal processing) , computer network , mathematics , engineering , statistics , electrical engineering , artificial intelligence , medicine , geometry , alternative medicine , pathology
Wireless sensor networks (WSNs) consist of an enormous number of tiny sensor nodes deployed in huge numbers which are able to sense, process and transmit environmental information to the base station (BS) for a variety of applications. Energy efficiency is one of the primary concerns for maintaining WSN in operation. In this study, an energy efficient clustering protocol based on K‐means algorithm named EECPK‐means has been proposed for WSN where midpoint algorithm is used to improve initial centroid selection procedure. The proposed approach produces balanced clusters to ultimately balance the load of cluster heads (CHs) and prolong the network lifetime. It considers residual energy as the parameter in addition to Euclidean distance used in basic K‐means algorithm for appropriate CH selection. Multi‐hop communication from CH nodes to BS takes place depending on their distances from BS. Simulation result shows that the proposed approach outperforms LEACH‐B, balanced parallel K‐means (BPK‐means), Park's approach and Mk‐means with respect to network lifetime and energy efficiency. Simulation result also demonstrates that the proposed approach can reduce the energy consumption at most 50% compared to LEACH‐B, 14% compared to BPK‐means protocol, 10% compared to Park's approach and 6% compared to Mk‐means.