Open AccessNovel Bacteria Foraging Optimization for Energy-efficient Communication in Wireless Sensor Network
Author(s) -
P Hemavathi,
A. N. Nandakumar
Publication year - 2018
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v8i6.pp4755-4762
Subject(s) - computer science , wireless sensor network , swarm intelligence , node (physics) , wireless , foraging , transmission (telecommunications) , residual , energy (signal processing) , distributed computing , particle swarm optimization , mathematical optimization , computer network , algorithm , telecommunications , mathematics , engineering , ecology , statistics , structural engineering , biology
Optimization techniques based on Swarm-intelligence has been reported to have significant benefits towards addressing communication issues in Wireless Sensor Network (WSN). We reviewed the most dominant swarm intelligence technique called as Bacteria Foraging Optimization (BFO) to find that there are very less significant model towards addressing the problems in WSN. Therefore, the proposed paper introduced a novel BFO algorithm which maintains a very good balance between the computational and communication demands of a sensor node unlike the conventional BFO algorithms. The significant contribution of the proposed study is to minimize the iterative steps and inclusion of minimization of both receiving / transmittance power in entire data aggregation process. The study outcome when compared with standard energy-efficient algorithm was found to offer superior network lifetime in terms of higher residual energy as well as data transmission performance.