An altruistic compression-scheduling scheme for cluster-based wireless sensor networks

Data compression using temporal and/or spatial correlations has been extensively studied to prolong the lifetime of wireless sensor networks (WSNs). In order to maximize the gain of these techniques, this work proposes an off-line altruistic compression-scheduling (ACS) scheme for cluster-based WSNs. It schedules when and how (i.e. without compression, with either of temporal and spatial compression, or with both of them) each sensor node executes compression techniques. The optimum scheduling solution to maximize the network lifetime is obtained by solving a linear program, whose computational complexity and runtime are efficiently reduced by a grouping and filtering algorithm. In addition, we propose a transmission power increment (TPI) method for WSNs with isolated nodes to improve the spatial compression possibilities. It can be used in ACS to further extend the lifetime of such networks. The efficiency of ACS is demonstrated by extensive simulation results using realistic models. It increases the network lifetime by a factor of 1.67 to 12.49 depending on different temporal correlations for typical WSNs. Compared with previous scheduling methods, it further extends the network lifetime with even less runtime. The combination of TPI and ACS significantly prolongs the lifetime of networks with isolated nodes.