{"title":"Mobile wireless sensor networks coverage maximization by firefly algorithm","authors":"Eva Tuba, M. Tuba, M. Beko","doi":"10.1109/RADIOELEK.2017.7937592","DOIUrl":null,"url":null,"abstract":"Wireless sensor networks have many applications and accordingly represent an active research area. Coverage maximization of the area of interest by sensors that have limited sensing radius is an important hard optimization problem. Since sensors are initially often deployed randomly one way of solving maximal coverage problem is by using mobile sensors that move to optimal positions. Since power in sensor nodes is limited, minimization of the sensor nodes movement is secondary optimization goal. In this paper we propose use of recent swarm intelligence algorithm, firefly algorithm, for optimization of that hard multiobjective problem. We tested our approach on standard benchmark data and compared results with other techniques from literature. Our proposed approach was better considering all quality measures: coverage, energy consumption, robustness and convergence speed.","PeriodicalId":160577,"journal":{"name":"2017 27th International Conference Radioelektronika (RADIOELEKTRONIKA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 27th International Conference Radioelektronika (RADIOELEKTRONIKA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RADIOELEK.2017.7937592","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 29
Abstract
Wireless sensor networks have many applications and accordingly represent an active research area. Coverage maximization of the area of interest by sensors that have limited sensing radius is an important hard optimization problem. Since sensors are initially often deployed randomly one way of solving maximal coverage problem is by using mobile sensors that move to optimal positions. Since power in sensor nodes is limited, minimization of the sensor nodes movement is secondary optimization goal. In this paper we propose use of recent swarm intelligence algorithm, firefly algorithm, for optimization of that hard multiobjective problem. We tested our approach on standard benchmark data and compared results with other techniques from literature. Our proposed approach was better considering all quality measures: coverage, energy consumption, robustness and convergence speed.