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

Heng-Qing Ye () and David D. Yao ()
Additional contact information
Heng-Qing Ye: Department of Logistics, Faculty of Business, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, and School of Business, National University of Singapore, Singapore
David D. Yao: Department of Industrial Engineering and Operations Research, Columbia University, New York, New York 10027

Operations Research, 2008, vol. 56, issue 2, 453-470

Abstract: 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 allocation of the service capacities is a real-time control mechanism: in each network state, the resource allocation is the solution to an optimization problem that maximizes a general utility function. Whereas this resource allocation optimizes in a “greedy” fashion with respect to each state, we establish its asymptotic optimality in terms of (a) deriving the fluid and diffusion limits of the network under this allocation scheme, and (b) identifying a cost function that is minimized in the diffusion limit, along with a characterization of the so-called fixed-point state of the network.

Keywords: stochastic processing network; concurrent resource occupancy; utility-maximizing resource allocation; fluid limit; diffusion limit; resource pooling; heavy-traffic optimality; Lyapunov function (search for similar items in EconPapers)
Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://dx.doi.org/10.1287/opre.1070.0455 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:56:y:2008:i:2:p:453-470

Access Statistics for this article

More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().