Name
Title | ||
|---|---|---|
QoS-Aware Power Management for Energy Harvesting Wireless Sensor Network Utilizing Reinforcement Learning |
Abstract | ||
|---|---|---|
A reinforcement learning (RL) method for Quality of Service (QoS)-aware power management (PM) of an energy harvesting wireless sensor network, named QoS-aware RLPM, is proposed in this paper. The RL environment for each sensor node is represented by the observable measurements of harvesting energy and residual energy stored in the battery. To achieve QoS-awareness, the proposed QoS-aware RLPM attempts to satisfy various QoS demands by adjusting the duty-cycle rate of sensor node according to the observable measurements. The outcomes of these interactions are evaluated by rewards that express how well the duty-cycle rate adjustments satisfy QoS requests under energy neutrality criteria [1]. The QoS-aware RLPM learns the adjustment strategy of the duty-cycle rate by interacting with the environment and at the same time the QoS of the sensor network is maintained. Experiment results show that the proposed method satisfies the QoS requests under the energy neutrality criteria and performs better than the adaptive duty-cycling method of [1]. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/CSE.2009.83 | CSE (2) |
Keywords | Field | DocType |
duty-cycle rate,residual energy,energy neutrality criterion,qos-aware power management,network utilizing reinforcement learning,harvesting energy,various qos demand,sensor node,energy harvesting wireless sensor,qos-aware rlpm,sensor network,observable measurement,qos request,learning artificial intelligence,wireless sensor network,duty cycle,quality of service,reinforcement learning,sensors,satisfiability,energy harvesting,wireless sensor networks,embedded system | Sensor node,Power management,Key distribution in wireless sensor networks,Computer science,Computer network,Quality of service,Energy harvesting,Battery (electricity),Wireless sensor network,Distributed computing,Reinforcement learning | Conference |
Citations | PageRank | References |
8 | 0.56 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Roy Chaoming Hsu | 1 | 84 | 11.76 |
| Cheng-Ting Liu | 2 | 48 | 6.45 |
| Kuan-Chieh Wang | 3 | 56 | 3.74 |
| Wei-Ming Lee | 4 | 20 | 3.46 |