Affiliation:
1. Hunan University, Changsha, China
2. University of Maryland, Maryland, USA
3. Singapore University of Technology and Design, Singapore
Abstract
In wireless sensor networks, owing to the limited energy of the sensor node, it is very meaningful to propose a dynamic scheduling scheme with data management that reduces energy as soon as possible. However, traditional techniques treat data management as an isolated process on only selected individual nodes. In this article, we propose an aggressive data reduction architecture, which is based on error control within sensor segments and integrates three parallel dynamic control mechanisms. We demonstrate that this architecture not only achieves energy savings but also guarantees the data accuracy specified by the application. Furthermore, based on this architecture, we propose two implementations. The experimental results show that both implementations can raise the energy savings while keeping the error at an predefined and acceptable level. We observed that, compared with the basic implementation, the enhancement implementation achieves a relatively higher data accuracy. Moreover, the enhancement implementation is more suitable for the harsh environmental monitoring applications. Further, when both implementations achieve the same accuracy, the enhancement implementation saves more energy. Extensive experiments on realistic historical soil temperature data confirm the efficacy and efficiency of two implementations.
Funder
National Science Foundation
Hunan University Junior Scholar Development Fund
National Natural Science Foundation of China
Research and Implementation of User's Identity Recognition Based on Mobile Sensors
Important National Science & Technology Support Projects of China
Publisher
Association for Computing Machinery (ACM)
Subject
Hardware and Architecture,Software
Cited by
8 articles.
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