Modeling of Data Reduction in Wireless Sensor Networks

• 作者: Glenn Patterson Mustafa Mehmet-Ali
• 来源期刊: 无线传感网络(英文)
• 学科: 医学
• 关键词: RANDOM Field Theory SPACE-TIME Behavior EXTREME VALUES DATA Reduction DATA Load Mean PACKET Delay
• 年，卷（期）: 2011,（8）
• 页码范围: 283-294
• 页数: 12页
• 分类号: R73

摘要

In this paper, we present a stochastic model for data in a Wireless Sensor Network (WSN) using random field theory. The model captures the space-time behavior of the underlying phenomenon being observed by the network. We present results regarding the size and spatial distribution of the regions of the network that sense statistically extreme values of the underlying phenomenon using the theory of extreme excursion regions. These results compliment many existing works in the literature that describe algorithms to reduce the data load, but lack an analytical approach to evaluate the size and spatial distribution of this load. We show that if only the statistically extreme data is transmitted in the network, then the data load can be significantly reduced. Finally, a simple performance model of a WSN is developed based on a collection of asynchronous M/M/1 servers that work in parallel. We derive several performance measures from this performance model. The presented results will be useful in the design of large scale sensor networks.