基于密度聚类的容迟网络路由协议

为了克服现有容迟网络消息冗余副本过多，数据传输时延较大的问题，对基于历史预测的Prophet路由协议进行优化，提出基于密度聚类的路由协议，采用聚类分析理论和生灭过程理论，准确构建和维护密度聚类簇，使网络中的消息副本得到实时控制.在此基础上，提出基于Q学习的随机线性网络编码策略，采用增强学习领域中的值函数估计法，通过中间节点高效获得线性独立的编码包，以提高网络编码效益.仿真实验结果表明，相比Epidemic和Prophet路由算法，该算法可以获得较高的消息投递率；在有足够缓存的情况下，数据传输时延得到了很好的控制，对容迟网络具有较强的动态适应性.

Routing Algorithm Based on Density Clustering for Delay Tolerant Network

In order to overcome the problem that there are too many message copies and large data transmission delay in the delay tolerant network, the author optimizes the Prophet routing protocol based on historical prediction, and propose a routing protocol based on density clustering. The algorithm adopts cluster analysis theory and birth and death process theory, the density cluster is constructed and maintained accurately, so that the message copies in the network can be controlled in real time. On this basis, the random linear network coding strategy based on Q-learning is proposed. The value function estimation method in the enhanced learning domain is adopted to obtain the linear independent coding packets efficiently through the intermediate nodes, so as to improve the coding efficiency of the network. Simulations show that this algorithm can obtain a higher message delivery rate in comparison with epidemic and Prophet routing algorithms, the data transmission delay can be well controlled under the condition of sufficient buffer thereafter. The algorithm has strong dynamic adaptability to the delay tolerant network.