Heavy-Traffic Optimality of a Stochastic Network Under Utility-Maximizing Resource Allocation

We study a stochastic network that consists of a set of servers processing multiple classes of jobs. Each class of jobs requires a concurrent occupancy of several servers while being processed, and each server is shared among the job classes in a head-of-the-line processor-sharing mechanism. The all...

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Veröffentlicht in:	Operations research Jg. 56; H. 2; S. 453 - 470
Hauptverfasser:	Ye, Heng-Qing, Yao, David D
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Linthicum, MD INFORMS 01.03.2008 Institute for Operations Research and the Management Sciences
Schlagworte:	Applied sciences Brownian motion Computer networks concurrent resource occupancy Cost functions diffusion limit Exact sciences and technology fluid limit heavy-traffic optimality Hyperlinks Information networks Integers Learning models (Stochastic processes) Lyapunov function Markov analysis Minimization of cost Network servers Operational research. Management science Optimal solutions Queueing networks Real time Resource allocation resource pooling Safety and security measures Stochastic models stochastic processing network Studies Transmission Control Protocol/Internet Protocol (Computer network protocol) Utility functions utility-maximizing resource allocation Workloads United States utility-maximizing resource allocation heavy-traffic optimality Utility function Resource allocation Asymptotic optimality Resource sharing resource pooling Real time diffusion limit Optimization fluid limit stochastic processing network Fixed point theorem Heavy traffic Cost function concurrent resource occupancy Lyapunov function
ISSN:	0030-364X, 1526-5463
Online-Zugang:	Volltext
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