In this paper, a simple and flexible method for increasing the lifetime of fixed or mobile wireless sensor networks is proposed. Based on past residual energy information reported by the sensor nodes, the sink node or another central node dynamically optimizes the communication activity levels of the sensor nodes to save energy without sacrificing the data throughput. The activity levels are defined to represent portions of time or time-frequency slots in a frame, during which the sensor nodes are scheduled to communicate with the sink node to report sensory measurements. Besides node mobility, it is considered that sensors’ batteries may be recharged via a wireless power transmission or equivalent energy harvesting scheme, bringing to the optimization problem an even more dynamic character. We report large increased lifetimes over the non-optimized network and comparable or even larger lifetime improvements with respect to an idealized greedy algorithm that uses both the real-time channel state and the residual energy information.
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