An Approach to an Energy Efficient Mechanism Using Mutated Bat Algorithm in Wireless Sensor Network

Maharajan, M. S. and Abirami, T. (2020) An Approach to an Energy Efficient Mechanism Using Mutated Bat Algorithm in Wireless Sensor Network. In: Recent Developments in Engineering Research Vol. 8. B P International, pp. 54-65. ISBN Recent Developments in Engineering Research Vol. 8

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Abstract

Today, the Wireless Sensor Network (WSN) is emerging to be a very promising technology to be
employed in the future. There were different protocols in energy-efficient routing that were designed
and further developed for the WSNs for the purpose of supporting data delivery given to their
respective destinations. The different techniques of clustering are perused widely by different
researchers for increasing their objectives of scalability and also their lifetime. There have been many
protocols used for the creation of a hierarchical structure to reduce the cost of the path at the time of
making any communication to the base station. This work increases an energy lifetime and the
stability of the network in an efficient manner within the protocols of clustering for which several
protocols were suggested. Discussion is made on the Bat Algorithm (BA), the Bat algorithm along with
mutation and the Genetic Algorithm (GA). This BAT algorithm had search abilities with various
applications to solve problems in engineering. There was viability for the mutated BAT algorithms
observed in various tasks that were proven and were shown by the empirical outcomes thus making
the proposed scheme to perform better in comparison with all schemes. At number of nodes 300, an
average packet delivery ratio of mutated BAT is increased by 15.72% and by 4.72% than GA and BAT
respectively. At number of nodes 1200, an average packet delivery ratio of mutated BAT is increased
by 25.79% and by 4.45% than GA and BAT respectively. At number of nodes 1800, an average
packet delivery ratio of mutated BAT is increased by 23.61% and by 4.14% than GA and BAT
respectively.

Item Type: Book Section
Subjects: STM Repository > Engineering
Depositing User: Managing Editor
Date Deposited: 11 Dec 2023 04:17
Last Modified: 11 Dec 2023 04:17
URI: http://classical.goforpromo.com/id/eprint/4691

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