This project examines wireless communication networks whose nodes have batteries that recharge by harvesting energy from the environment. We apply analytical models for battery recharging to evaluate fundamental multiple access, broadcast and relay network models composed of rechargeable nodes. The project objective is an enhanced understanding of the analytic fundamentals of rechargeable networks in order to contribute to the development and ultimate deployment of ecologically-friendly rechargeable networks.
In some applications, such as sensor networks for precision agriculture, we may ultimately deploy networks with biodegradable sensors that can be plowed under each season. In this case, a single-charge disposable battery that lasts through the growing season might make sense. On the other hand, the cost of biodegradable disposable devices may be reduced by the use of a smaller battery and a solar cell enabling battery recharging. When more complex non-biodegradable devices are deployed, someone will have to replace the batteries or clean up the sensors when the batteries are consumed. By comparison, energy replenishment can yield a network that lasts as long as the network's hardware and intended purpose remain viable; this may be arbitrarily longer than the lifetime of any suitable single-charge battery.
While average-power minimization is adequate to describe the lifetime of a device with a single-charge battery, a complete characterization of a network of rechargeable devices will depend on how the batteries are replenished. Energy recharging devices may include solar cells, vibration absorption devices, wind and water mills, thermoelectric generators that exploit local temperature gradients, and microbial fuel cells. Given this broad variety of existing devices and the high likelihood of the emergence of new devices, this project will not speculate on which renewable energy sources will become viable technologies. Instead we model energy recharging as an environmental stochastic process and we analyze and design communication and network protocols for nodes subject to stochastic recharging. In particular, the performance of a mobile device and its network will depend on how devices optimize their operation as a function of their battery states. In this project, we apply analytical models for battery recharging to evaluate fundamental multiple access, broadcast and relay network models composed of rechargeable nodes.
This is a 3-year NSF-funded project (joint with Prof. Sennur Ulukus of UMD) which started in 2010. The project is ongoing with several analytical results for alternative transmission policies and battery replenishment models (see figure below).
Sample results for "maximum reward optimal transmission policy" using a Markov model with hybrid battery replenishment modeled as a Poisson process