Clustering-Based Approximate Scheme for Data Aggregation over Sensor Networks
基于分簇的传感器网络数据聚集估算机制

In this paper, a hierarchical clustering-based approximate scheme for in-network aggregation over sensor networks called CASA (clustering-based approximate scheme for data aggregation) is proposed, CASAachieves a good performance in terms of lifetime by minimizing overall energy consumption for communicationsand balancing energy load among all nodes, while maintaining user-specified quality of data requirement. CASA adopts an optimal parameter for the cluster size, which can well handle the hierarchical approximate work for in-network aggregation with the minimized communication cost. Furthermore, an adaptive tolerance-reallocating scheme is leveraged to further reduce the overall communication cost and maintain a load balance according to various data change rates over deployment regions. Experimental results indicate that significant benefits can be achieved through this CASA approximate scheme.