Heavy-Traffic Delay Insensitivity in Connection-Level Models of Data Transfer with Proportionally Fair Bandwidth Sharing

Heavy-Traffic Delay Insensitivity in Connection-Level Models of Data Transfer with Proportionally Fair Bandwidth Sharing
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具有按比例公平带宽共享的连接级数据传输模型中的大流量延迟不敏感

DOI:
10.1145/3199524.3199565
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发表时间:
2018
期刊:
ACM SIGMETRICS Performance Evaluation Review
影响因子:
--
通讯作者:
Ying, Lei
Ying, Lei
中科院分区:
--
文献类型:
--
作者:
Wang, Weina;Maguluri, Siva Theja;Srikant, R.;Ying, Lei

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受数据中心网络延迟性能严格要求的推动,我们研究了数据传输流之间带宽共享的连接级模型,其中文件大小具有阶段型分布,并使用按比例公平的带宽分配。我们通过将适当选择的李亚普诺夫函数的稳态漂移设置为零来分析稳态下的预期文件数。我们考虑大流量的情况,并获得系统中预期文件数量的渐近严格界限。我们的结果表明,按比例公平的带宽分配下的预期文件数量在大流量中对文件大小分布不敏感,从而补充了 Vlasiou 等人的扩散近似结果。 [20]。
Motivated by the stringent requirements on delay performance in data center networks, we study a connection-level model for bandwidth sharing among data transfer flows, where file sizes have phase-type distributions and proportionally fair bandwidth allocation is used. We analyze the expected number of files in steady-state by setting the steady-state drift of an appropriately chosen Lyapunov function equal to zero. We consider the heavy-traffic regime and obtain asymptotically tight bounds on the expected number of files in the system. Our results show that the expected number of files under proportionally fair bandwidth allocation is insensitive in heavy traffic to file size distributions, thus complementing the diffusion approximation result of Vlasiou et al. [20].
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