Title :
Green energy optimization in energy harvesting wireless sensor networks
Author :
Jianchao Zheng ; Yueming Cai ; Xuemin Shen ; Zhongming Zheng ; Weiwei Yang
fDate :
11/1/2015 12:00:00 AM
Abstract :
This article studies the sensor activation control for the optimization of green energy utilization in an EH-WSN, where both energy generation and target distribution exhibit temporal and spatial diversities. Decentralized operation is considered for the green energy optimization in the EH-WSN. The optimization is achieved in two dimensions: dynamic (activation) mode adaptation in the temporal dimension and energy balancing in the spatial dimension. Due to the interactions among autonomous distributed sensors, game theory is applied to the local information based decentralized optimization for the spatial energy balancing problem. In addition, reinforcement learning techniques are proposed to address the temporal mode adaptation in the dynamic and unknown environment. Simulation results are provided to demonstrate the effectiveness of the proposed approaches.
Keywords :
energy harvesting; environmental factors; game theory; learning (artificial intelligence); optimisation; telecommunication computing; wireless sensor networks; EH-WSN; activation mode adaptation; autonomous distributed sensors; dynamic mode adaptation; energy balancing; energy generation; energy harvesting wireless sensor networks; game theory; green energy utilization optimization; local information based decentralized optimization; reinforcement learning techniques; sensor activation control; spatial diversities; spatial energy balancing problem; target distribution; temporal diversities; temporal mode adaptation; Game theory; Green computing; Green products; Learning (artificial intelligence); Optimization; Spatial diversity; Wireless sensor networks;
Journal_Title :
Communications Magazine, IEEE
DOI :
10.1109/MCOM.2015.7321985
