Data-centric energy efficient scheduling for densely deployed sensor networks

A key challenge in wireless sensor networks is to achieve maximal network lifetime with dynamic power management on sensor nodes. In this paper we investigate the node level power control scheduling on densely deployed sensor networks. We prove that given homogeneous Poisson sensing traffic in a sensor network, the routing traffic is heterogeneous. We then introduce a well defined power control model to adapt to heterogeneous traffic, and propose a data-centric energy efficient scheduling protocol under the power model. The simulation results show that our protocol can reduce about 61.4% of power consumption at the sensor node level and achieve 33.3% to 43.5% energy efficiency at the network level, compared to other existing protocols.