IEEE Transactions on Wireless Communications · 2009 · 251 citations · 10 references
EngineeringWireless Sensor SystemEnergy EfficiencyPower ControlSensor ConnectivityGreen NetworkingReplenishable SensorsSingle-hop Transmission PolicyLogisticsSystems EngineeringInternet Of ThingsPower ManagementMarkov Chain ModelGeneric ModelComputer EngineeringEnergy StorageMobile ComputingEnergy ManagementEdge ComputingBusinessRobust RoutingSensor OptimizationEnergy-efficient Networking
Energy harvesting from the environment is increasingly used to replenish wireless sensor networks, yet power management remains critical due to stochastic replenishment uncertainty. This study introduces a generic mathematical framework to determine optimal single‑hop transmission policies for replenishable sensor networks. Using a Markov chain model of energy renewal modes, the authors derive optimal transmission thresholds for sensors with varying energy budgets, allowing reward values to be tailored to specific design objectives. The derived thresholds maximize the average reward rate, yielding significant performance gains over a simple transmit‑all policy that sends every message whenever energy is available.
Energy harvesting from the working environment has received increasing attention in the research of wireless sensor networks. Recent developments in this area can be used to replenish the power supply of sensors. However, power management is still a crucial issue for such networks due to the uncertainty of stochastic replenishment. In this paper, we propose a generic mathematical framework to characterize the policy for single hop transmission over a replenishable sensor network. Firstly, we introduce a Markov chain model to describe different modes of energy renewal. Then, we derive the optimal transmission policy for sensors with different energy budgets. Depending on the energy status of a sensor and the reward for successfully transmitting a message, we prove the existence of optimal thresholds that maximize the average reward rate. Our results are quite general since the reward values can be made application-specific for different design objectives. Compared with the unconditional transmit-all policy, which transmits every message as long as the energy storage is positive, the proposed optimal transmission policy is shown to achieve significant gains in the average reward rate.
10
Ian F. Akyildiz, Weilian Su, Yogesh Sankarasubramaniam · IEEE Communications Magazine · 2002 · 13.6K citations
Energy-aware wireless microsensor networks
Vijay Raghunathan, Curt Schurgers, Sung Min Park et al. · IEEE Signal Processing Magazine · 2002 · 1.7K citations
Sensor Networks, Topology Control, Electrical Engineering +14
PicoRodio supports ad hoc ultra-low power wireless networking
Jan M. Rabaey, M.J. Ammer, J.L. da Silva et al. · Computer · 2000 · 1K citations