{"title":"Optimal Deployment of Mobile Sensors Nodes using Signal Strength Equalization","authors":"Shilpa Sharma, Harjiram Choudhary","doi":"10.1109/SCEECS.2018.8546990","DOIUrl":null,"url":null,"abstract":"Deployment of sensing nodes in remote areas like forests, mountains, etc. is not deterministic thus face problem of network disconnection. Solutions for the problem are still in their initial phase. The nodes may be dropped from the airplane or thrown manually to non-optimally cover the sensing area. Our aim is to optimally deploy, the randomly deployed movable nodes. The previous researches targeted the area coverage based on GPS locations alone, but due to complex geography and obstacles in wireless transmission the network may remain disconnected and crucial applications like forest fire detection may not be sensed deterministically. We use an adaptive signal strength equalization method to ensure connection between any two adjacent nodes. We argue that the resultant geometry of node clusters should be hexagonal in shape where the center node is equidistant from all the vertices and these vertices shall be common to nearby clusters. But geographic hexagons do not ensure proper signal due to obstacles in line-of-sight and signal strength may not be deterministic leading to network disconnection. We propose to create hexagonal geometry based on signal strength instead of distance alone. Our scheme ensures no network disconnections and coverage of whole geographic area which is of utmost priority. Once the complete deployment takes place all the hexagonal clusters have equal average signal strength.","PeriodicalId":446667,"journal":{"name":"2018 IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCEECS.2018.8546990","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Deployment of sensing nodes in remote areas like forests, mountains, etc. is not deterministic thus face problem of network disconnection. Solutions for the problem are still in their initial phase. The nodes may be dropped from the airplane or thrown manually to non-optimally cover the sensing area. Our aim is to optimally deploy, the randomly deployed movable nodes. The previous researches targeted the area coverage based on GPS locations alone, but due to complex geography and obstacles in wireless transmission the network may remain disconnected and crucial applications like forest fire detection may not be sensed deterministically. We use an adaptive signal strength equalization method to ensure connection between any two adjacent nodes. We argue that the resultant geometry of node clusters should be hexagonal in shape where the center node is equidistant from all the vertices and these vertices shall be common to nearby clusters. But geographic hexagons do not ensure proper signal due to obstacles in line-of-sight and signal strength may not be deterministic leading to network disconnection. We propose to create hexagonal geometry based on signal strength instead of distance alone. Our scheme ensures no network disconnections and coverage of whole geographic area which is of utmost priority. Once the complete deployment takes place all the hexagonal clusters have equal average signal strength.