Scheduling and power control for energy-optimality of low duty cycled sensor networks

The main limitation of operating sensor networks autonomously is the finite battery capacity of sensor nodes. Sensors are usually operated at low duty cycle; that is, they remain in active mode for short duration of time, in order to prolong the network lifetime. However, operating at low duty cycle may result in significant performance degradation in system operation. Hence, in this work, we quantitatively investigate the tradeoff between the duty cyle and network performance. Specifically, we address the design of efficient channel access protocol, by developing a scheduling algorithm based on well known Lyapunov optimization framework. Our proposed policy dynamically schedules transmissions of sensor nodes and their sleep cycles by taking into account the time-varying channel state information, traffic arrivals, and energy consumptions due to switching between operational modes. We analytically show that our policy is energy optimal in the sense that it achieves an energy consumption which is arbitrarily close to the global minimum solution. We use simulations to confirm our results