Real-time queueing network theory

J. Lehoczky
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引用次数: 84

Abstract

This paper presents real-time queueing network theory, the extension of real-time queueing theory introduced by J.P. Lehoczky (1996) to Jackson queueing networks. This theory describes the behavior of standard Jackson queueing networks when the tasks have end-to-end deadlines. This theory is focused on describing the instantaneous multidimensional profiles of the lead-times of all the tasks in all the nodes of the network. The earliest end-to-end deadline first policy is used at all nodes in the network, although the theory permits other scheduling policies and different policies at different nodes. The real-time network problem is formulated in general, but it is analyzed under heavy traffic conditions where the traffic intensity at each node approaches 1. In this case, the multivariate queue length process converges to a Brownian network, a multivariate Brownian motion constrained to the first orthant. The conditional multivariate lead-time profiles at each of the nodes given the queue lengths converge to a deterministic profile. This characterization is borne out by simulation, and is used to design and evaluate queue control policies to reduce task lateness.
实时排队网络理论
本文提出了实时排队网络理论,即j.p Lehoczky(1996)提出的实时排队理论在Jackson排队网络中的扩展。该理论描述了当任务具有端到端截止日期时标准杰克逊队列网络的行为。该理论侧重于描述网络中所有节点中所有任务的交付时间的瞬时多维概况。在网络的所有节点上使用最早的端到端截止时间优先策略,但理论允许使用其他调度策略,并且在不同节点上使用不同的策略。实时网络问题是一般情况下的问题,但在每个节点的交通强度趋近于1的大交通条件下进行分析。在这种情况下,多元队列长度过程收敛到一个布朗网络,一个约束于第一正交的多元布朗运动。给定队列长度的每个节点上的条件多变量前置时间概要收敛为确定性概要。仿真验证了这一特性,并将其用于设计和评估队列控制策略,以减少任务延迟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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