基于马尔科夫决策的容迟网络路由算法

Study of the DTN routing algorithm based on the Markov decision

由于容迟容断网络面临的应用环境极为特殊,传统网络的路由协议无法适用于容迟容断网络.为了提高容迟容断网络的传输效率,同时减小网络延迟和网络开销,提出了基于马尔科夫决策的容迟容断网络路由算法.该算法具有学习功能,能够解决复杂的容迟容断网络环境中的高延迟和频繁割裂问题.仿真结果表明,基于马尔科夫决策的容迟容断网络在同等网络条件下,性能优于Epidem ic、PROPHET等同类路由算法.

Since the major application scenarios of the DTN（delay/disruption tolerant network） are extremely particular,routing protocols designed for the traditional networks are not suitable for it.In order to raise the transfer efficiency while reducing the network delay and network cost in the DTN,a routing algorithm based on the Markov Decision,named MRDDTN（Markov Route Decision in the DTN）,is proposed.The MRDDTN is self-learning and can solve problems in the complex network environment characterized by very long delay paths and frequent network partitions.Through simulative analysis,the MRDDTN is found to be able to achieve a better performance than Epidemic and PROPHET routing algorithms under the same network conditions.