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Optimization-based network flow deadline scheduling

机译：基于优化的网络流截止日期调度

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摘要

Many network flows nowadays, especially in a data center environment, have associated deadlines by which they must be fully transmitted. Nevertheless, traditional transport protocols such as TCP, focus on concepts like throughput and fairness, and do not aim to satisfy flow deadlines. Motivated by this limitation, several alternative transport designs and solutions have been recently proposed. These approaches generally achieve a better performance in terms of the number of satisfied deadlines and are usually built upon various heuristics. In contrast to these previous works, this article approaches the problem directly from an optimization perspective. We first prove that the problem belongs to the class of NP-hard problems that do not even admit a constant ratio approximation solution (unless P=NP), and formulate it as a mixed integer-linear optimization program. Then, using linear programming approximations, we further develop offline and online optimization-based rate control algorithms to approach the problem. Flow-level simulation results indicate that the proposed algorithms can be near-optimal, and hence they can be served as benchmarks against which other solutions to this problem can be evaluated. We additionally performed simulations incorporating such real network features as deployment delays and packet-level granularity to evaluate the performance of the proposed algorithms in a more realistic environment.
机译：现在，许多网络流动，尤其是在数据中心环境中，具有必须完全传输的相关截止日期。然而，传统的传统传输协议，如TCP，专注于吞吐量和公平性等概念，并不旨在满足流动截止日期。通过这种限制，最近提出了几种替代传输设计和解决方案。这些方法通常在满意的截止日期的数量方面达到更好的性能，并且通常建立在各种启发式中。与这些以前的作品相比，本文直接从优化角度接近问题。我们首先证明问题属于甚至不承认恒定比率近似解（除非P = NP）的NP难题类别，并将其作为混合整数 - 线性优化程序。然后，使用线性编程近似，我们进一步开发了基于线和在线优化的速率控制算法来解决问题。流量级仿真结果表明，所提出的算法可以近乎最佳，因此它们可以作为基准来评估对该问题的其他解决方案。我们还执行了将这种真实网络功能的模拟，作为部署延迟和分组级粒度，以评估所提出的算法在更现实的环境中的性能。

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