Performance analysis of an improved dynamic power management model in wireless sensor node

The energy consumption in the wireless sensor networks is a very critical issue which attracts immediate attention for the sake of the growing demand of the billion dollar market in future. The Dynamic Power Management (DPM) technique is a way of controlling and saving the energy usage in a sensor node. Previously, researchers have proposed lifetime improving stochastic models for wireless sensor networks and limited work has been done focusing on the wireless sensor node. This paper proposes an analyser based Semi-Markov model for DPM in the event-driven sensor node. The power consumption comparison with previously proposed models without this analyser shows the analyser significant contributes to lifetime improvement. The improved model is more power efficient, presents how the DPM model observes the input event arrival and power states of the sensor node components, and then dynamically manages the power consumption of the overall system. Further, to observe the effect of event arrival, missed events, waiting time, processor utilization on the power consumption and lifetime, the proposed DPM system with the single server queuing model is developed.