Simulated Annealing Application to Maximum Lifetime Coverage Problem in Wireless Sensor Networks

Antonina Tretyakova; Franciszek Seredynski

doi:10.29007/gl61

Download PDF Open PDF in browser

Simulated Annealing Application to Maximum Lifetime Coverage Problem in Wireless Sensor Networks

16 pages•Published: December 18, 2015

Antonina Tretyakova and Franciszek Seredynski

Abstract

Energy optimization problem in Wireless Sensor Networks (WSN) is a backbone of efficient performance of sensor network consisting of small devices with limited and non-recovering battery. WSN lifetime maximization problem under assumption of that the coverage is main task of the network is known as Maximal lifetime coverage problem (MLCP).
This problem belongs to a class of NP-hard problems. In this paper we propose a novel simulated annealing (SA) algorithm to solve MLCP. The proposed algorithm is studied for high dense WSN instances under different parameter setup.

Keyphrases: coverage control, coverage preserving protocols, energy optimization, maximum lifetime coverage problem, Wireless Sensor Networks

In: Georg Gottlob, Geoff Sutcliffe and Andrei Voronkov (editors). GCAI 2015. Global Conference on Artificial Intelligence, vol 36, pages 296--311

Links:	https://easychair.org/publications/paper/clDP
	https://doi.org/10.29007/gl61

BibTeX entry

@inproceedings{GCAI2015:Simulated_Annealing_Application_to,
  author    = {Antonina Tretyakova and Franciszek Seredynski},
  title     = {Simulated Annealing Application to Maximum Lifetime Coverage Problem in Wireless Sensor Networks},
  booktitle = {GCAI 2015. Global Conference on Artificial Intelligence},
  editor    = {Georg Gottlob and Geoff Sutcliffe and Andrei Voronkov},
  series    = {EPiC Series in Computing},
  volume    = {36},
  pages     = {296--311},
  year      = {2015},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {https://easychair.org/publications/paper/clDP},
  doi       = {10.29007/gl61}}

Download PDF Open PDF in browser