计算机科学 ›› 2020, Vol. 47 ›› Issue (11): 316-321.doi: 10.11896/jsjkx.200400075
张昊, 管昕洁, 白光伟
ZHANG Hao, GUAN Xin-jie, BAI Guang-wei
摘要： 无线传感器网络在环境感知、目标跟踪等方面占据了重要地位。为了能够及时地为传感器节点补充能量,提出了一种基于强化学习的低功耗、高能效的移动路径充电算法。无线传感器网络采用移动充电车对传感器节点进行充电,将Q-Learning算法与epsilon-greedy算法相结合,以最短路径依次完成所有传感器节点的充电。现有的相关研究通常忽略了传感器节点自身所能承受电量的最大值,容易导致传感器节点因充电过程中电量超出最大值而暂停工作,因此限制了移动充电车的充电时间。结果表明,所提移动充电策略的效用更高,与传统的Q-Learning算法和贪心算法相比,训练周期大幅度下降且实现了能量利用率最大化。
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