Open AccessGenetic Algorithms for Localization in WSN
Author(s) -
Gondhi Navabharat Reddy,
A M Navya,
D. Kiran Kumar,
Sruthi Setlam,
Natasha Saude
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.e2533.039520
Subject(s) - firefly algorithm , bat algorithm , wireless sensor network , computer science , heuristic , node (physics) , algorithm , firefly protocol , artificial intelligence , computer network , engineering , biology , particle swarm optimization , zoology , structural engineering
In wireless sensor networks, localization is a way to track the exact location of sensor nodes. Occasionally node localization may not be accurate due to the absence or limitation of anchor nodes. To reduce the mean localization error, soft computing techniques such as BAT and bacterial foraging driven bat algorithm (BDBA) are utilized in literature. For better localization with reduced error, in this paper, firefly driven bat algorithm (FDBA) is proposed, which combines the heuristic of firefly and BAT algorithms. Our proposed FDBA algorithm provides better localization in terms of error of 60% and 40 % less error as compared to BAT and BDBA algorithm, respectively.