MPAR：一种社会延迟容忍网络中运动模式感知的最优路由算法
MPAR: A Movement Pattern-Aware Optimal Routing for Social Delay Tolerant Networks
摘要：
社交延迟容忍网络是由具有社交特性的移动设备组成的一种特殊的延迟容忍网络。现有路由算法的研究成果往往对每个中继节点的可用收益进行单独评估，无法从全局角度实现路由算法的全局最优性能。在本文中，我们提出了一个运动模式感知最优路由（MPAR）的SDTN，通过选择最佳的中继节点设置为每个消息，这最终基于运行一个搜索算法的超立方体的解决方案空间。具体地，可以从节点的移动记录中提取一组节点的移动模式。然后得到中继节点集合和目的节点的共同访问位置集合，通过该集合可以进一步评估中继节点集合的共同交付概率。在寻找最优中继节点集的过程中，采用了局部搜索和禁忌搜索两种策略，并证明了基于禁忌搜索的Tabu-MPAR路由算法能够引导中继节点集向最优中继节点集演化.我们演示了如何通过大量的模拟，合成SDTN移动模型的基础上，MPAR算法显着优于以前的。
英文摘要：
Social Delay Tolerant Networks (SDTNs) are a special kind of Delay Tolerant Network (DTN) that consists of a number of mobile devices with social characteristics. The current research achievements on routing algorithms tend to separately evaluate the available profit for each prospective relay node and cannot achieve the global optimal performance in an overall perspective. In this paper, we propose a Movement Pattern-Aware optimal Routing (MPAR) for SDTNs, by choosing the optimal relay node(s) set for each message, which eventually based on running a search algorithm on a hyper-cube solution space. Concretely, the movement pattern of a group of node(s) can be extracted from the movement records of nodes. Then the set of commonly visited locations for the relay node(s) set and the destination node is obtained, by which we can further evaluate the co-delivery probability of the relay node(s) set. Both local search scheme and tabu-search scheme are utilized in finding the optimal set, and the tabu-search based routing Tabu-MPAR is proved able to guide the relay node(s) set in evolving to the optimal one. We demonstrate how the MPAR algorithm significantly outperforms the previous ones through extensive simulations, based on the synthetic SDTN mobility model.
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