Abstract
Most existing research considers homogeneous sensor networks, which suffer from performance bottleneck and poor scalability. In this paper, we adopt a heterogeneous sensor network model to overcome these problems. Sensing coverage is a fundamental problem in sensor networks and has been well studied over the past years. However, most coverage algorithms only consider the uniform coverage problem, that is, all the areas have the same coverage degree requirement. In many scenarios, some key areas need high coverage degree while other areas only need low coverage degree. We propose a differentiated coverage algorithm which can provide different coverage degrees for different areas. The algorithm is energy efficient since it only keeps minimum number of sensors to work. The performance of the differentiated coverage algorithm is evaluated through extensive simulation experiments. Our results show that the algorithm performs much better than any other differentiated coverage algorithm.
Highlights
Sensor networks hold the promise of facilitating large-scale, real-time data processing in complex environments
We propose a novel differentiated coverage algorithm for wireless sensor networks
We evaluate the performance of the differentiated coverage (DC) algorithm, and compare DC with another differentiated coverage algorithm in [9], which we refer to as differentiated surveillance (DS) algorithm
Summary
Sensor networks hold the promise of facilitating large-scale, real-time data processing in complex environments. Recent research has found that significant energy savings can be achieved by dynamic management of node duty cycles in sensor networks with high node density In this approach, some nodes are scheduled to sleep (or enter a power saving mode) while the remaining active nodes provide continuous service. Most existing researches consider the uniform sensing coverage problem in sensor networks, for example, PEAS [4] and OGDC [5] In these algorithms, nodes switch to sleeping state as long as their neighbors can provide sensing coverage for them. It is not efficient to support the same high degree of coverage for some less important areas To handle this issue, in this paper we propose a differentiated coverage algorithm for sensor networks.
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