Dyna-Routing: Multi Criteria Reinforcement Learning Routing for Wireless Sensor Networks with Lossy Links

被引：0
|
作者：
Udenze, Adrian [1 ]
McDonald-Maier, Klaus [1 ]
机构：
[1] Univ Essex, Sch Comp Sci & Elect Engn, Embedded & Intelligent Syst Res Grp, Colchester CO4 3SQ, Essex, England
来源：
AD HOC & SENSOR WIRELESS NETWORKS | 2011年 / 11卷 / 3-4期
基金：
英国工程与自然科学研究理事会;
关键词：
Wireless Sensor Networks (WSN); Routing; Lossy Links; Reinforcement Learning (RL); Multi-Criteria RL;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Finding optimal routes for packet delivery in a WSN is presented as a multi-criteria optimization problem termed Dyna-Routing. Delay in delivering packets to sinks, energy used for transmitting packets, rate of energy depletion in respective nodes and also, properties of the transmission medium are used to form metrics for evaluating routing options. A Dyna Reinforcement Learning algorithm suitable for non deterministic environments is used to speed up learning such that minimal energy is wasted on suboptimal action choices. Simulation results of Dyna-Routing compared to other machine learning routing approaches show a marked increase in the lifespan of nodes and the network in general.
引用
收藏
页码：285 / 306
页数：22
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