Abstract:
Sensors nodes with far distance from the Base Station tends to lose energy faster
compare to those closer to it. Power consumption at such sensor nodes can be
classified into four categories: communication, sensing, inactive listening, and data
processing. Considering these four categories, communication (transmission and
reception of data) prove to be a dominant feature in determining the rate of power
consumption. Several routing protocols have been developed for energy drainage in
communication. It has however been established that energy conservation is one of
the key solutions to challenges posed by resource constrained wireless sensor
networks (WSNs). Recent works are therefore on energy efficient protocols being
applied on specific challenges. This research proposes a novel energy optimization
algorithm called I-HEED (Intelligent Hybrid Energy Efficient Distributed) clustering
which is an hybrid of HEED and Monkey Search Algorithm. This algorithm utilizes
the optimized energy distribution method among sensor nodes in HEED protocol and
optimization strategy in Monkey Search Algorithm to select the best cluster head. To
ensure that the cluster head has enough capacity to transmit collaborative information
from other sensor nodes to the base station. The result analysis shows that the I-HEED
algorithm out performs LEACH (Low Energy Adaptive Clustering Hierarchy), DEEC
(Distributed Energy Efficient Clustering) and HEED algorithm in terms of alive
nodes, dead nodes and packet sent to the base station which are major determinant of
energy optimization in WSN. The developed I-HEED algorithm performed 330%
better than DEEC, 315 % better than HEED and 50% better than LEACH. I-HEED
algorithm for WSNs provide energy efficient solution within resource constrained
environments
