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arXiv 1506.04729cs.NI
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基于相遇率估计的延迟容忍网络最优转发

Optimal Forwarding in Opportunistic Delay Tolerant Networks with Meeting Rate Estimations

Shohreh Shaghaghian, Mark Coates

摘要:

机会型容迟网络中的数据传输必须依赖节点间的非计划性的零星会议。在这些网络中的主要挑战是开发一种机制,基于该机制,节点可以学习做出几乎最优的转发决策规则,尽管没有网络拓扑的先验知识。理想情况下,转发机制应导致高递送概率、低平均延迟和网络资源的有效使用。在本文中,我们提出了集中式和分散式的单副本消息转发算法,在相对较强的假设下的网络行为,最大限度地减少预期的延迟从网络中的任何节点到一个特定的目的地。在证明了我们提出的算法的最优性,我们开发了一个分散的算法,涉及到一个递归的最大似然过程来估计会议率。我们确认,我们提出的算法在系统性能的改善,通过数值模拟的数据集从合成和现实世界的机会网络。

英文摘要:

Data transfer in opportunistic Delay Tolerant Networks (DTNs) must rely on unscheduled sporadic meetings between nodes. The main challenge in these networks is to develop a mechanism based on which nodes can learn to make nearly optimal forwarding decision rules despite having no a-priori knowledge of the network topology. The forwarding mechanism should ideally result in a high delivery probability, low average latency and efficient usage of the network resources. In this paper, we propose both centralized and decentralized single-copy message forwarding algorithms that, under relatively strong assumptions about the networks behaviour, minimize the expected latencies from any node in the network to a particular destination. After proving the optimality of our proposed algorithms, we develop a decentralized algorithm that involves a recursive maximum likelihood procedure to estimate the meeting rates. We confirm the improvement that our proposed algorithms make in the system performance through numerical simulations on datasets from synthetic and real-world opportunistic networks.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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