A wireless sensor network usually has a large amount of nodes deployed in a area to report ambient reading, to detect abnormal events, or to monitor the region. Each sensor performs several tasks, such as computing, sensing and communicating. A node equipped with multiple sensors is able to participate in many sensing tasks to improve measurement accuracy. However, the contribution a new node can make to the corresponding sensing accuracy depends on the number of existing nodes while the energy cost will increase in a consistent way. Therefore, there is a tradeoff between the task accuracy and the energy cost. In this paper, we consider the dynamic fading fact of contribution of redundant sensor nodes and bring forward a Contribution Aware Task Allocation method to maximize the total accuracy efficiency of sensor network. The method is derived from max-weight resource allocation algorithm (i.e., K-M algorithm) and can guarantee the optimal of the solution. We compare our method with two other greedy and optimizing method. The experimental result shows our method outperform the competitors and are more efficiency.
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