{"title":"Energy minimization for heterogeneous wireless sensor networks","authors":"Meikang Qiu, C. Xue, Z. Shao, Meilin Liu, E. Sha","doi":"10.3233/JEC-2009-0084","DOIUrl":null,"url":null,"abstract":"Lifetime is very important to wireless sensor networks since most sensors are equipped with non-rechargeable batteries. Therefore, energy and delay are critical issues for the research of sensor networks that have limited lifetime. Due to the uncertainties in execution time of some tasks, this paper models each varied execution time as a probabilistic random variable with the consideration of applications' performance requirements to solve the MAP (Mode Assignment with Probability) problem. Using probabilistic design, we propose an optimal algorithm to minimize the total energy consumption while satisfying the timing constraint with a guaranteed confidence probability. The experimental results show that our approach achieves significant energy saving than previous work. For example, our algorithm achieves an average improvement of 32.6% on total energy consumption.","PeriodicalId":422048,"journal":{"name":"J. Embed. Comput.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Embed. Comput.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/JEC-2009-0084","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
Abstract
Lifetime is very important to wireless sensor networks since most sensors are equipped with non-rechargeable batteries. Therefore, energy and delay are critical issues for the research of sensor networks that have limited lifetime. Due to the uncertainties in execution time of some tasks, this paper models each varied execution time as a probabilistic random variable with the consideration of applications' performance requirements to solve the MAP (Mode Assignment with Probability) problem. Using probabilistic design, we propose an optimal algorithm to minimize the total energy consumption while satisfying the timing constraint with a guaranteed confidence probability. The experimental results show that our approach achieves significant energy saving than previous work. For example, our algorithm achieves an average improvement of 32.6% on total energy consumption.
寿命对于无线传感器网络来说非常重要,因为大多数传感器都配备了不可充电电池。因此,能量和延迟是有限寿命传感器网络研究的关键问题。由于某些任务的执行时间存在不确定性,本文将每次变化的执行时间建模为一个概率随机变量,并考虑应用程序的性能需求来解决MAP (Mode Assignment with Probability)问题。利用概率设计,提出了一种以保证置信度概率满足时间约束的最小化总能耗的优化算法。实验结果表明,该方法比以往的方法节能效果显著。例如,我们的算法在总能耗上平均提高了32.6%。