Heavy-traffic optimality of a stochastic network under utility-maximizing resource allocation

Hengqing Ye, David D. Yao

Research output: Journal article publicationJournal articleAcademic researchpeer-review

17 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)453-470
Number of pages18
JournalOperations Research
Issue number2
Publication statusPublished - 1 Mar 2008

ASJC Scopus subject areas

  • Computer Science Applications
  • Management Science and Operations Research


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