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arXiv 0907.3977cs.NI
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流级动态下的最优调度问题

Throughput-Optimal Opportunistic Scheduling in the Presence of Flow-Level Dynamics

Shihuan Liu, Lei Ying, R. Srikant

摘要:

我们认为在无线网络中的多用户调度与信道变化和流量水平的动态。最近,它已被证明,最大权重算法,这是吞吐量最优的网络中具有固定数量的用户,无法实现最大吞吐量的存在下,流级动态。在本文中,我们提出了一种新算法,称为基于工作负载的学习调度算法,该算法可证明是吞吐量最优的,不需要信道和用户需求的先验知识,并且性能显着优于之前建议的算法。

英文摘要:

We consider multiuser scheduling in wireless networks with channel variations and flow-level dynamics. Recently, it has been shown that the MaxWeight algorithm, which is throughput-optimal in networks with a fixed number users, fails to achieve the maximum throughput in the presence of flow-level dynamics. In this paper, we propose a new algorithm, called workload-based scheduling with learning, which is provably throughput-optimal, requires no prior knowledge of channels and user demands, and performs significantly better than previously suggested algorithms.

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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