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Maximizing Uniform Multicast Throughput in Multi-Channel Dense Wireless Sensor Networks

机译:在多通道密集无线传感器网络中最大化统一组播吞吐量

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This paper investigates the problem of maximizing uniform multicast throughput (MUMT) for multi-channel dense wireless sensor networks, where all nodes locate within one-hop transmission range and can communicate with each other on multiple orthogonal channels. This kind of networks show wide application in the real world, and maximizing uniform multicast throughput for these networks is worth deep studying. Previous researches have proved MUMT problem is NP-hard. However, previous researches are either hard to implement, or use too many relay nodes to complete the multicast task, and thus incur high overhead or poor performance. To efficiently solve MUMT problem, we adopt the concept of the maximum independent set with the size constraint, and present one novel Single-Broadcast based Multicast algorithm called SBM based on the concept. We prove that SBM algorithm achieves a constant ratio to the theoretical throughput upper bound. Extensive experimental results demonstrate that, SBM performs better than existing work in terms of both the uniform multicast throughput and the total number of transmissions.
机译:本文研究了多通道密集无线传感器网络的最大化统一多播吞吐量(MUMT)的问题,在该网络中,所有节点都位于一跳传输范围内,并且可以在多个正交信道上相互通信。这种网络在现实世界中显示出广泛的应用,并且最大化这些网络的统一多播吞吐量值得深入研究。先前的研究已经证明MUMT问题是NP难的。然而,先前的研究要么难以实现,要么使用太多的中继节点来完成多播任务,从而导致高开销或性能低下。为了有效地解决MUMT问题,我们采用具有大小约束的最大独立集的概念,并提出了一种基于该概念的新颖的基于单播的组播算法SBM。我们证明SBM算法与理论吞吐量上限达到了恒定的比率。大量的实验结果表明,就统一多播吞吐量和传输总数而言,SBM的性能均优于现有工作。

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