关键词: 传感器节点选择, 误差精度, 工作概率, 0-1整数规划, 模糊规划

Abstract:

This paper presents a novel fuzzy-programming based sensor selection approach for the field reconstruction in wireless sensor networks. The information of the interpolation point is predicted by using the inverse distance weighted interpolation method and the normal operating probability of each node is computed based on the principle of inclusion-exclusion. Then, the minimal number of the required sensor nodes is computed by the utilization of the 0-1 integer programming to achieve the requirements of normal operating probability, accuracy of each node. Whats more, the fuzzy-programming is used to compute the required sensor number according to the error threshold and the fuzzy operating probability. We evaluate the 0-1 integer programming and fuzzy-programming based on the temperature sensor data. The results show that the fuzzy programming algorithm can reduce the number of sensor nodes by about 35% compared with 0-1 integer programming under the same constraint.

Key words: sensor node selection;error accuracy, working probability;0-1 integer programming;fuzzy programming