Efficient flow-control algorithm cooperating with energy allocation scheme for solar-powered WSNs

Recently, solar energy emerged as a feasible supplement to battery power for wireless sensor networks (WSNs) which are expected to operate for long periods. Since solar energy can be harvested periodically and permanently, solar-powered WSNs can use the energy more efficiently for various network-wide performances than traditional battery-based WSNs of which aim is mostly to minimize the energy consumption for extending the network lifetime. However, using solar power in WSNs requires a different energy management from battery-based WSNs since solar power is a highly varying energy supply. Therefore, firstly we describe a time-slot-based energy allocation scheme to use the solar energy optimally, based on expectation model for harvested solar energy. Then, we propose a flow-control algorithm to maximize the amount of data collected by the network, which cooperates with our energy allocation scheme. Our algorithms run on each node in a distributed manner using only local information of its neighbors, which is a suitable approach for scalable WSNs. We implement indoor and outdoor testbeds of solar-powered WSN and demonstrate the efficiency of our approaches on them.