A Hybrid Artificial Bee Colony and Bacterial Foraging Algorithm for Optimized Clustering in Wireless Sensor Network
Bandi Rambabu1, A Venugopal Reddy2, Sengathir Janakiraman3

1Bandi Rambabu Associate Professor, CVR College of Engineering and Research Scholar, JNTUH Hyderabad
2Dr. A Venugopal Reddy, Professor, JNT University, Hyderabad
3Dr.J Sengathir Associate Professor, CVR College of Engineering, JNTUH Hyderabad

Manuscript received on 02 July 2019 | Revised Manuscript received on 09 July 2019 | Manuscript published on 30 August 2019 | PP: 2186-2190 | Volume-8 Issue-10, August 2019 | Retrieval Number: J93910881019/2019©BEIESP | DOI: 10.35940/ijitee.J9391.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The emerging ubiquitous nature of wireless sensor networks has made it suitable and applicable to a diversified number of vital applications that include environment surveillance, health monitoring using implantable sensors, weather forecasting and other plethora of contexts. The critical issues such as computation time, limited memory and energy are more common due to the tiny sized hundred and thousands of sensor nodes existing in the networks. In this context, the network lifetime completely depends on the potential use of available resources. The process of organizing closely located sensor nodes into clusters is convenient for effective management of cluster and improving the lifetime of the complete network. At this juncture, swarm intelligent and evolutionary algorithms the pertains to the problem of NP-complete is determined to achieve a superior optimal solution. In this paper, a Hybrid Artificial Bee Colony and Bacterial Foraging Algorithm-based Optimized Clustering (HABC-BFA-OC) is proposed for achieving enhanced network lifetime in sensor networks. In this proposed HABC-BFA-OC technique, the benefits of Bacterial Foraging Optimization is included for improving the local search potential of ABC algorithm in order to attain maximum exploitation and exploration over the parameters considered for cluster head selection. The simulation experiments of the proposed HABC-BFA-OC technique confirmed an enhanced network lifetime with minimized energy consumptions during its investigation with a different number of sensor nodes.
Keywords: Cluster Head Selection, (ABC)Artificial Bee Colony, (BFO)Bacterial Foraging Optimization, Network Lifetime, Exploitation, Exploration.
Scope of the Article: Energy Harvesting and Transfer for Wireless Sensor Networks