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Community-Aware Opportunistic Routing in Mobile Social Networks

机译:移动社交网络中的社区感知机会路由

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摘要

Mobile social networks (MSNs) are a kind of delay tolerant network that consists of lots of mobile nodes with social characteristics. Recently, many social-aware algorithms have been proposed to address routing problems in MSNs. However, these algorithms tend to forward messages to the nodes with locally optimal social characteristics, and thus cannot achieve the optimal performance. In this paper, we propose a distributed optimal Community-Aware Opportunistic Routing (CAOR) algorithm. Our main contributions are that we propose a home-aware community model, whereby we turn an MSN into a network that only includes community homes. We prove that, in the network of community homes, we can still compute the minimum expected delivery delays of nodes through a reverse Dijkstra algorithm and achieve the optimal opportunistic routing performance. Since the number of communities is far less than the number of nodes in magnitude, the computational cost and maintenance cost of contact information are greatly reduced. We demonstrate how our algorithm significantly outperforms the previous ones through extensive simulations, based on a real MSN trace and a synthetic MSN trace.
机译:移动社交网络(MSN)是一种延迟容忍网络,它由许多具有社交特征的移动节点组成。最近,已经提出了许多社交意识算法来解决MSN中的路由问题。但是,这些算法倾向于将消息转发到具有局部最佳社会特征的节点,因此无法实现最佳性能。在本文中,我们提出了一种分布式的最佳社区感知机会路由(CAOR)算法。我们的主要贡献是,我们提出了一种家庭感知的社区模型,借此将MSN变成仅包含社区住宅的网络。我们证明,在社区住宅网络中,我们仍然可以通过反向Dijkstra算法计算节点的最小预期交付延迟,并获得最佳的机会路由性能。由于社区的数量远远少于节点的数量,因此大大降低了联系信息的计算成本和维护成本。我们将基于真实的MSN跟踪和合成的MSN跟踪,通过广泛的仿真演示我们的算法如何明显优于以前的算法。

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