Markov Decision Process Based Wireless Multicast Opportunistic Routing

被引：0

作者：

Ma Dianbo ^{[1
,2
]}

Tan Xiaobin ^{[1
,2
]}

Zhou Zijian ^{[1
,2
]}

Yu Shanjin ^{[1
,2
]}

机构：

[1] Univ Sci & Technol China, Dept Automat, Hefei 230027, Peoples R China

[2] Univ Sci & Technol China, CAS Key Lab Technol Geospatial Informat Proc & Ap, Hefei 230027, Peoples R China

来源：

2014 33RD CHINESE CONTROL CONFERENCE (CCC) | 2014年

关键词：

Markov Decision Process; Opportunistic Routing; Multicast; reward function; MESH NETWORKS; RELIABLE BROADCAST; HIGH-THROUGHPUT;

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：

There are more and more pervasive applications of Wireless Multicast Network, such as the video conference, the voice transmission and the software updates etc. The traditional wireless multicast routing method is to construct a multicast tree, which may ignore many available links. This paper presents Markov Decision Process Based Multicast Opportunistic Routing Model. Whether each node of the whole network has received a packet stands for different states of a Markov chains. That is to say that Markov state transition is a routing process. This paper provides a new approach for the study of wireless multicast networks routing. In the reward function of the model, the consumption of Request and ACK among the nodes is abundantly considered. In accordance with each state of the network, the network chooses the optimal forwarding nodes which make the reward function of the model maximum. The experiment and the simulation results proves MDP is most effective routing scheme, and meets with the network system's requirement.

引用

页码：5509 / 5514

页数：6

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