Abstract
Node clustering and data aggregation are popular techniques to reduce energy consumption in large Wireless Sensor Networks (WSN). Cluster based routing is always a hot research area in wireless sensor networks. Classical LEACH protocol has many advantages in energy efficiency, data aggregation and so on. However, determining number of clusters present in a network is an important problem. Conventional clustering techniques generally assume this parameter to be user supplied. There exist very few techniques that can solve the problem of automatic detection of number of clusters satisfactorily. Some of these techniques rely on user supplied information, while others use cluster validity indices. In this paper, we proposed a rather simple method to identify the number of clusters that can give satisfactory results. Proposed method is compared with classical LEACH protocol and found to be giving better results.
Highlights
Node clustering and data aggregation are popular to reduce energy consumption in large Wireless Sensor Networks (WSN)
Clustering in WSN is the process of dividing the nodes of WSN into groups, where each group agrees on a central node, called the Cluster Head (CH), which is responsible for gathering the sensory data of all group members, aggregating it and sending to Base Station (BS)
We compare our proposed algorithm with LEACH based on three performance metrics: i) spread of the dead/alive nodes at each round; ii) Number of packets transmitted at FND(First-node dead), HND (Half nodes dead), AND (All Nodes Dead); iii) Cluster indices of Dunn’s, PBM and DB
Summary
Abstract—Node clustering and data aggregation are popular techniques to reduce energy consumption in large Wireless Sensor Networks (WSN). Classical LEACH protocol has many advantages in energy efficiency, data aggregation and so on. Conventional clustering techniques generally assume this parameter to be user supplied. There exist very few techniques that can solve the problem of automatic detection of number of clusters satisfactorily. Some of these techniques rely on user supplied information, while others use cluster validity indices. We proposed a rather simple method to identify the number of clusters that can give satisfactory results. Proposed method is compared with classical LEACH protocol and found to be giving better results
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