In this study, the authors investigate the energy-aware quality of information (QoI) maximisation problem by jointly optimising the sensor selection, sampling rate, packet-dropped rate, and transmit power in wireless sensor networks. By introducing the weight parameters, the authors first present a revenue-cost (RC) function which combines the optimisation objectives of the QoI and energy expenditure into a single objective to capture the tradeoff between them. Then, a stochastic optimisation programming is formulated to maximise the long-term average RC value subject to the network stability constraint. Using the Lyapunov drift theory, the authors develop a collaborative sensing and transmit power control algorithm that can guarantee the worst-case delay for each packet. Simulation results demonstrate the advantages of the proposed algorithm.
['Pengfei Du', 'Qinghai Yang', 'Qingsu He', 'Kyung Sup Kwak']
Energy-aware quality of information maximisation for wireless sensor networks