Control of end-to-end delay tails in a multiclass network: LWDF discipline optimality

成果类型:
Article
署名作者:
Stolyar, AL
署名单位:
Alcatel-Lucent; Lucent Technologies; AT&T
刊物名称:
ANNALS OF APPLIED PROBABILITY
ISSN/ISSBN:
1050-5164
DOI:
10.1214/aoap/1060202838
发表日期:
2003
页码:
1151-1206
关键词:
queuing-networks Markovian processes due-date STABILITY CONVERGENCE criteria
摘要:
We consider a multiclass queueing network with N customer classes, each having an arbitrary fixed route through the network. (Thus, the network is not necessarily feedforward.) We show that the largest weighted delay first (LWDF) discipline is an optimal scheduling discipline in the network in the following sense. Let w(i) be the (random) instantaneous largest end-to-end delay of a class i customer in the network in stationary regime. For any set of positive constants alpha(1), . . . , alpha(N), the LWDF discipline associated with this set maximizes (among all disciplines) the quantity (1) (min)(i=1,)(,N) [alpha(1) lim(n-->infinity) (-1)/(n) log P (w(i) > n)] = lim(n-->infinity) (-1)/(n) log P (r > n), where r = max(i) w(i)/alpha(i) is the maximal weighted delay in the network. [This result is a generalization of the single-server result proved by A. L. Stolyar and K. Ramanan in Ann. Appl. Probab. 11 (2001) 1-48.] As the key element of the proof, we establish the following critical node property: In a LWDF network, there exists a most likely path to build large r, which is a most likely path to do so in one of the network nodes in isolation. Such a most likely path has a very simple structure: its parameters [and the optimal value of (1)] can be computed by solving a finite-dimensional optimization problem for each network node.