M. Nguyen, Hien M. Nguyen, Antonino Masaracchia, Cuong V. Nguyen
{"title":"Stochastic-Based Power Consumption Analysis for Data Transmission in Wireless Sensor Networks","authors":"M. Nguyen, Hien M. Nguyen, Antonino Masaracchia, Cuong V. Nguyen","doi":"10.4108/eai.13-6-2019.159123","DOIUrl":null,"url":null,"abstract":"Wireless sensor networks (WSNs) provide a lot of emerging applications. They suffer from some limitations such as energy constraints and cooperative demands essential to perform sensing or data routing. The networks could be exploited more effectively if they are well managed with power consumption since all sensors are randomly deployed in sensing areas needed to be observed without battery recharge or remote control. In this work, we proposed some stochastic-based methods to calculate total power consumption for such networks. We model common arbitrary networks with different types of sensing areas, circular and square shapes, then analyze and calculate the power consumption for data transmission based on statistic problems. Almost common data collection methods are employed such as cluster-based, tree-based, neighborhood based and random routing. In each method, the total power consumption is formulated and then simulated to be verified. This paper shows promise that all the formulas could be applied not only on WSNs but also mobile sensor networks (MSNs) while the mobile sensors are considered moving at random positions. Received on 05 June 2019; accepted on 12 June 2019; published on 13 June 2019","PeriodicalId":33474,"journal":{"name":"EAI Endorsed Transactions on Industrial Networks and Intelligent Systems","volume":"237 1","pages":"e5"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"EAI Endorsed Transactions on Industrial Networks and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4108/eai.13-6-2019.159123","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 13
Abstract
Wireless sensor networks (WSNs) provide a lot of emerging applications. They suffer from some limitations such as energy constraints and cooperative demands essential to perform sensing or data routing. The networks could be exploited more effectively if they are well managed with power consumption since all sensors are randomly deployed in sensing areas needed to be observed without battery recharge or remote control. In this work, we proposed some stochastic-based methods to calculate total power consumption for such networks. We model common arbitrary networks with different types of sensing areas, circular and square shapes, then analyze and calculate the power consumption for data transmission based on statistic problems. Almost common data collection methods are employed such as cluster-based, tree-based, neighborhood based and random routing. In each method, the total power consumption is formulated and then simulated to be verified. This paper shows promise that all the formulas could be applied not only on WSNs but also mobile sensor networks (MSNs) while the mobile sensors are considered moving at random positions. Received on 05 June 2019; accepted on 12 June 2019; published on 13 June 2019