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Scheduling for End-to-End Deadline-Constrained Traffic With Reliability Requirements in Multihop Networks

机译:多跳网络中具有可靠性要求的端到端时限约束流量调度

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We attack the challenging problem of designing a scheduling policy for end-to-end deadline-constrained traffic with reliability requirements in a multihop network. It is well known that the end-to-end delay performance for a multihop flow has a complex dependence on the high-order statistics of the arrival process and the algorithm itself. Thus, neither the earlier optimization-based approaches that aim to meet the long-term throughput demands nor the solutions that focus on a similar problem for single-hop flows directly apply. Moreover, a dynamic programming-based approach becomes intractable for such multi-timescale quality-of-service (QoS)-constrained traffic in a multihop environment. This motivates us in this paper to develop a useful architecture that enables us to exploit the degree of freedom in choosing appropriate service discipline. Based on the new architecture, we propose three different approaches, each leading to an original algorithm. We study the performance of these algorithms in different scenarios to show both optimality characteristics and to demonstrate the favorable service discipline characteristics they possess. We provide extensive numerical results to compare the performance of all of these solutions to throughput-optimal back-pressure-type schedulers and to longest waiting-time-based schedulers that have provably optimal asymptotic performance characteristics. Our results reveal that the dynamic choice of service discipline of our proposed solutions yields substantial performance improvements compared to both of these types of traditional solutions under nonasymptotic conditions.
机译:我们解决了具有挑战性的问题,即为多跳网络中具有可靠性要求的端到端受时间限制的流量设计调度策略。众所周知,多跳流的端到端延迟性能对到达过程的高阶统计量和算法本身具有复杂的依赖性。因此,既没有旨在满足长期吞吐量需求的早期基于优化的方法,也没有直接关注解决单跳流量类似问题的解决方案。此外,对于多跳环境中的这种受多时间尺度服务质量(QoS)约束的流量,基于动态编程的方法变得棘手。这激励我们在本文中开发一种有用的体系结构,该体系结构使我们能够在选择适当的服务学科时利用自由度。基于新的体系结构,我们提出了三种不同的方法,每种方法都可以产生一种原始算法。我们研究了这些算法在不同场景下的性能,以显示最优性特征并证明它们具有良好的服务学科特征。我们提供了广泛的数值结果,以比较所有这些解决方案的性能与吞吐量最佳的背压型调度程序以及具有可证明的最佳渐近性能特征的最长的基于等待时间的调度程序。我们的结果表明,与在非渐近条件下的这两种传统解决方案相比,我们提出的解决方案的服务规则的动态选择可带来实质性的性能改进。

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