On maximizing the lifetime for data aggregation in wireless sensor networks using virtual data aggregation trees

Abstract

Data gathering is a basic requirement in many applications of wireless sensor networks (WSNs). Because the energy of sensors is limited, the data-gathering mechanism must be carefully designed to save the energy consumption of sensors to prolong the network lifetime. Recently, many researchers have studied gathering data efficiently in WSNs to minimize the total energy consumption when a fixed number of data are allowed to be aggregated into one packet. However, when the total energy consumption is minimized, the energy consumption of sensors for data gathering cannot be guaranteed to be balanced, and thus, the network lifetime cannot be guaranteed to be maximized. This motivates us to study the problem of scheduling virtual data aggregation trees to maximize the network lifetime when a fixed number of data are allowed to be aggregated into one packet, termed the Maximum Lifetime Data Aggregation Tree Scheduling (MLDATS) problem. The MLDATS problem is shown to be NP-complete in the paper. In addition, a local-tree-reconstruction-based scheduling algorithm (LTRBSA) is proposed for the MLDATS problem. We use simulations to evaluate and demonstrate the performance of the LTRBSA when the sink has 2-hop, 3-hop, and all information in the networks. Simulation results show that the LTRBSA of using sink’s 3-hop information provides comparable performances to that of using all information in the networks, and outperforms other methods proposed in the simulation.