Local adaptive sampling for wireless sensor network powered by energy harvesting

被引：5

作者：

Yan, Junfang ^{[1
]}

Pei, Li ^{[1
]}

Chen, Zhiwei ^{[1
]}

Wang, Mengjiao ^{[2
]}

机构：

[1] Beijing Jiaotong Univ, Inst Lightwave Technol, Beijing 100044, Peoples R China

[2] Mid Sweden Univ, Sch ITM, S-85230 Sundsvall, Sweden

来源：

OPTIK | 2012年 / 123卷 / 23期

关键词：

Wireless sensor network; Adaptive sampling; Power management; Energy monitoring;

D O I：

10.1016/j.ijleo.2011.11.011

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

For a sensor network, energy limitation is always a key factor to affect the continuous work of a sensor node. A good idea is harvesting energy from the environment to support the node to work continuously. However, energy from environment is varied with time, weather and season. So in order to use the varied environment energy, it is necessary to find a way to achieve real-time monitoring and adaptive working. In this paper, an algorithm called "Adaptive Sampling" was proposed to adapt the sample mode to the present energy condition. Simulation proves that the algorithm can make the CO2 sensor flexibly achieve adaptive sampling under different energy condition with the least MSE 2.7767. This algorithm can be widely used in wireless sensor network power by energy harvesting for local adaptive sampling. (C) 2011 Elsevier GmbH. All rights reserved.

引用

页码：2195 / 2197

页数：3

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