Presentation: MOFCA: Multi-Objective Fuzzy Clustering Algorithm for Wireless Sensor Networks
When: June 20, 2016, 10:00-11:00
Where: Zi 2024
Who: Alper Sert
This study introduces a new clustering approach which is not only
energy-efficient but also distribution-independent for Wireless Sensor Networks
(WSNs). Clustering is used as a means of efficient data gathering technique in
terms of energy consumption. In clustered networks, each node transmits acquired
data to a cluster-head which the nodes belong to. After a cluster-head collects
all the data from all member nodes, it transmits the data to the base station
(sink) either in a compressed or uncompressed manner. This data transmission
occurs via other cluster-heads in a multi-hop network environment. As a result
of this situation, cluster-heads close to the sink tend to die earlier because
of the heavy inter-cluster relay. This problem is named as the hotspots problem.
To solve this problem, some unequal clustering approaches have already been
introduced in the literature. Unequal clustering techniques generate clusters in
smaller sizes when approaching the sink in order to decrease intra-cluster
relay. In addition to the hotspots problem, the energy hole problem may also
occur because of the changes in the node deployment locations. Although a number
of previous studies have focused on energy-efficiency in clustering, to the best
of our knowledge, none considers both problems in uniformly and non-uniformly
distributed networks. Therefore, we propose a multi-objective solution for these
problems. In this study, we introduce a multi-objective fuzzy clustering
algorithm (MOFCA) that addresses both hotspots and energy hole problems in
stationary and evolving networks. Performance analysis and evaluations are done
with popular clustering algorithms and obtained experimental results show that
MOFCA outperforms the existing algorithms in the same set up in terms of
efficiency metrics, which are First Node Dies (FND), Half of the Nodes Alive
(HNA), and Total Remaining Energy (TRE) used for estimating the lifetime of the
WSNs and efficiency of protocols.