A Hierarchical Multi-Parent Cluster-Based Data Aggregation Framework for WSNs

One of the major issues in wireless sensor network applications is the way how to minimize energy consumption in the process of data transfer. Data in wireless sensor networks should be aggregated in order to save energy and bandwidth. There are lots of works on the area of fault-tolerant and efficient data aggregation for WSNs in different approach. In this paper an efficient fault tolerant data aggregation framework is proposed based on a hierarchical multi-parent clustering fashion addressing how to determine faulty nodes, how to recover lost/corrupted data and how to minimize energy and bandwidth for longer network lifetime. The proposed approach uses a hierarchical clustering in which each cluster will have two heads/primary and secondary/to aggregate sensed data and simultaneously maximize the communication efficiency with in the cluster. Moreover, the framework uses both the spatial and temporal characteristics of nodes with in and across clusters to substitute missed values based on regression analysis.