Analysis of Different Sleep and Wakeup Strategies in Solar Powered Wireless Sensor Networks

We present a novel analytical framework to investigate the performances of different sleeping strategies in a wireless sensor network where a solar cell is used to charge the battery in a sensor node. While the energy generation process (i.e., solar radiation) in a solar cell is modeled by a stochastic process (i.e., a Markov chain), a linear battery model with relaxation effect is used for the battery capacity recovery process. Average queue length, packet dropping and packet blocking probabilities and packet delay distribution at each node are the major performance metrics. Developed based on a multi-dimensional discrete-time Markov chain, the presented model can be used to analyze the performances of different sleep and wakeup strategies at each node (e.g., strategies based on available battery capacity, channel state, solar radiation condition and queue length, and hybrid of these conditions). The numerical results obtained from the analytical model are validated by extensive simulations. The presented model would be useful for designing and optimizing sleeping strategies in a solar powered sensor network under energy and QoS constraints.