Efficient scheduling for minimum latency aggregation in wireless sensor networks

An important application for sensor networks is to collect data sensed from the environment and send it to a data collection point or a sink node using a convergecast tree. Considerable savings in energy can be obtained by aggregating data at intermediate nodes along the way to the sink. We study the problem of finding a minimum latency aggregation tree and transmission schedule in wireless sensor networks. This problem is referred to as Minimum Latency Aggregation Scheduling (MLAS) in the literature and has been proven to be NP-Complete. We present a new algorithm for building an aggregation tree. Furthermore, we propose two new approaches for building a TDMA transmission schedule to perform aggregation on a given tree. We evaluate the performance of our algorithms through extensive simulations on randomly generated graphs and we compare them to the previous state of the art. Our results show that both our new scheduling algorithms when combined with our new tree-building algorithm obtain significantly lower latencies than that of the previous best algorithm.