In:
International Journal of Electrical and Computer Engineering (IJECE), Institute of Advanced Engineering and Science, Vol. 8, No. 6 ( 2018-12-01), p. 4755-
Abstract:
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.
Type of Medium:
Online Resource
ISSN:
2088-8708
,
2088-8708
DOI:
10.11591/ijece.v8i6.pp4755-4762
Language:
Unknown
Publisher:
Institute of Advanced Engineering and Science
Publication Date:
2018
detail.hit.zdb_id:
2667127-X
