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Deployment of a Connected Reinforced Backbone Network with a Limited Number of Backbone Nodes

机译:具有有限数量的骨干节点的连接的增强型骨干网络的部署

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摘要

In recent years, we have witnessed a surge of interest in enabling communications over meshed wireless networks. Particularly, supporting peer-to-peer communications over a multihop wireless network has great potential in enabling ubiquitous computing. However, many wireless nodes have limited capabilities, for example, sensor nodes or small handheld devices. Also, the end-to-end capacity and delay degrade significantly as the path length increases with the number of network nodes. In these scenarios, the deployment of a backbone network could potentially facilitate higher performance network communications. In this paper, we study the novel reinforced backbone network (RBN) deployment problem considering the practical limitation in the number of available backbone nodes and enforcing backbone network connectivity. We propose an iterative and adaptive (ITA) algorithm for efficient backbone network deployment. In addition, in order to provide the performance bound, we redefine and solve the problem by implementing the genetic algorithm. Finally, we present our simulation results under various settings and compare the performance of the proposed ITA algorithm and the genetic algorithm. Our study indicates that the proposed ITA algorithm is promising for deploying a connected RBN with a limited number of available backbone nodes.
机译:近年来,我们见证了对通过网状无线网络进行通信的兴趣激增。特别是,支持多跳无线网络上的对等通信在启用普适计算方面具有巨大潜力。但是,许多无线节点的功能有限,例如,传感器节点或小型手持设备。另外,随着路径长度随着网络节点数量的增加,端到端的容量和延迟也会大大降低。在这些情况下,骨干网的部署可能会促进更高性能的网络通信。在本文中,我们考虑到可用骨干节点数量的实际限制并加强骨干网络的连接性,研究了新型的增强骨干网络(RBN)部署问题。我们提出了一种有效的骨干网络部署的迭代和自适应(ITA)算法。另外,为了提供性能界限,我们通过实现遗传算法来重新定义和解决问题。最后,我们展示了在各种设置下的仿真结果,并比较了所提出的ITA算法和遗传算法的性能。我们的研究表明,提出的ITA算法有望在有限数量的可用骨干节点上部署连接的RBN。

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