Performance Evaluation of Two Fuzzy-Based Cluster Head Selection Systems for Wireless Sensor Networks
Author(s) -
Junpei Anno,
Leonard Barolli,
Arjan Durresi,
Fatos Xhafa,
Akio Kôyama
Publication year - 2008
Publication title -
mobile information systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.346
H-Index - 34
eISSN - 1875-905X
pISSN - 1574-017X
DOI - 10.1155/2008/876212
Subject(s) - computer science , wireless sensor network , cluster (spacecraft) , fuzzy logic , selection (genetic algorithm) , distributed computing , computer network , artificial intelligence
Sensor networks supported by recent technological advances in low power wireless communications along with silicon integration of various functionalities are emerging as a critically important computer class that enable novel and low cost applications. There are many fundamental problems that sensor networks research will have to address in order to ensure a reasonable degree of cost and system quality. Cluster formation and cluster head selection are important problems in sensor network applications and can drastically affect the network's communication energy dissipation. However, selecting of the cluster head is not easy in different environments which may have different characteristics. In this paper, in order to deal with this problem, we propose two fuzzy-based systems for cluster head selection in sensor networks. We call these systems: FCHS System1 and FCHS System2. We evaluate the proposed systems by simulations and have shown that FCHS System2 make a good selection of the cluster head compared with FCHS System1 and another previous system
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