SDAM: A New Data Aggregation Approach for Wireless Sensor Networks

In this paper, a novel scalable scheme, scalable data aggregation monitoring (SDAM), is proposed for efficient data gathering with aggregation (fusion) in wireless sensor networks (WSN). Different from existing schemes, SDAM not only optimizes data transmission cost, but also incorporates the function of data fusion, which is crucial for emerging sensor networks with data management and high availability requirements. Employing a randomized algorithm that allows fusion points to be chosen by nodes´ data amount, SDAM can achieve high availability for sensor nodes, which results the optimal solution for nowadays system setup. Simulation results demonstrate that SDAM scheme can reflect the node status promptly, and save the network throughput of sensor nodes. Therefore, the lifetime of WSN is significantly extended.