传感器网络中基于差异化加权数据压缩的汇聚算法

数据融合技术能有效地节省能量,提高信息的准确度.结合传感器网络自身的特点,本文提出了一种基于差异化加权数据压缩的汇聚算法(DADW),通过选择合适的融合点并对不同源节点的信息进行差异化加权处理,有效地提高了数据融合的精度,提供了可靠的服务质量保障.仿真结果表明,相对于已有的算法,该算法以一个很小数量级的能量损失获得了融合精度的显著提高.

Event Driven Aggregation Algorithms for Wireless Sensor Network

Data aggregation is critical in designing energy-efficient sensor networks. An event driven data aggregation algorithms (DADW) is presented in this paper. In DADW algorithms, the source node which is nearest to the event acts as aggregation point and different node information is given different weight value according to its distance from event. Compared to conventional data-centric algorithms, DADW has advantages with respect to data precision. We demonstrate the effectiveness of our design through simulations and then some conclusions are provided.