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A distributed and asynchronous approach for optimizing weighted graph matchings in wireless network services

机译:在无线网络服务中优化加权图匹配的分布式异步方法

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摘要

Weighted graph matching is one of the most fundamental graph theoretical problems used in network design, especially in wireless network services such as radio resource allocation, physical layer security, energy-efficient partner selection and optimizing storage capacity. In this paper we present a distributed heuristic which provides nearly-optimal weighted matchings in polynomial time. We also propose an algorithm to decrease the number of transmitted messages to provide energy-efficient operation. Our approaches assume the asynchronous communication model and small messages havingO(log (n)) bits. These assumptions directly fit the battery powered wireless networks such as wireless ad hoc and sensor networks. To the best of our knowledge, we propose the first distributed weighted matching algorithm which benefits from augmentation of augmenting paths having size larger than 3 for these networks. We also provide results of our simulations on synthetic geometric graphs to model wireless networks. Extensive simulations reveal that our algorithm improves the approximation performances of the other weighted matching algorithms and closes the gap between the approximation ratio and the optimum up to 32%.
机译:加权图匹配是网络设计中最基本的图理论问题之一,尤其是在无线网络服务中,例如无线电资源分配,物理层安全性,节能伙伴选择和优化存储容量。在本文中,我们提出了一种分布式启发式算法,该算法可在多项式时间内提供近乎最佳的加权匹配。我们还提出了一种减少传输消息数量以提供节能操作的算法。我们的方法假设异步通信模型和具有O(log(n))位的小消息。这些假设直接适合电池供电的无线网络,例如无线ad hoc和传感器网络。据我们所知,我们提出了第一种分布式加权匹配算法,该算法得益于这些网络的大小大于3的增强路径的增强。我们还提供了合成几何图上的仿真结果,以对无线网络进行建模。大量的仿真表明,我们的算法提高了其他加权匹配算法的逼近性能,并缩小了逼近率与最优值之间的差距,最高可达32%。

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