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Distributed fuzzy approach to unequal clustering and routing algorithm for wireless sensor networks
Author(s) -
Mazumdar Nabajyoti,
Om Hari
Publication year - 2018
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.3709
Subject(s) - computer science , wireless sensor network , cluster analysis , base station , energy consumption , computer network , efficient energy use , routing (electronic design automation) , distributed computing , relay , fuzzy logic , node (physics) , energy (signal processing) , routing protocol , destination sequenced distance vector routing , algorithm , dynamic source routing , engineering , mathematics , artificial intelligence , power (physics) , statistics , physics , structural engineering , quantum mechanics , electrical engineering
Summary Due to inherent issue of energy limitation in sensor nodes, the energy conservation is the primary concern for large‐scale wireless sensor networks. Cluster‐based routing has been found to be an effective mechanism to reduce the energy consumption of sensor nodes. In clustered wireless sensor networks, the network is divided into a set of clusters; each cluster has a coordinator, called cluster head (CH). Each node of a cluster transmits its collected information to its CH that in turn aggregates the received information and sends it to the base station directly or via other CHs. In multihop communication, the CHs closer to the base station are burdened with high relay load; as a result, their energy depletes much faster as compared with other CHs. This problem is termed as the hot spot problem. In this paper, a distributed fuzzy logic‐based unequal clustering approach and routing algorithm (DFCR) is proposed to solve this problem. Based on the cluster design, a multihop routing algorithm is also proposed, which is both energy efficient and energy balancing. The simulation results reinforce the efficiency of the proposed DFCR algorithm over the state‐of‐the‐art algorithms, ie, energy‐aware fuzzy approach to unequal clustering, energy‐aware distributed clustering, and energy‐aware routing algorithm, in terms of different performance parameters like energy efficiency and network lifetime.