Paper Info
Title
Heavy-Traffic Optimality of a Stochastic Network Under Utility-Maximizing Resource Allocation
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.
Year
DOI
Venue
2008
10.1287/opre.1070.0455
Operations Research
Keywords
Field
DocType
resource allocation,stochastic network,head-of-the-line processor-sharing mechanism,stochastic processing network,diffusion limit,lya- punov function.,general utility function,network state,so-called fixed-point state,resource pooling,difiusion limit,utility-maximizing resource allocation,heavy-traffic optimality,resource allocation optimizes,∞uid limit,allocation scheme,cost function,heavy-tra-c optimality,concurrent resource occupancy,stochastic process,real time control,optimization problem,lyapunov function,fixed point
Lyapunov function,Fluid limit,Mathematical optimization,Pooling,Server,Resource allocation,Shared resource,Optimization problem,Fixed-point theorem,Operations management,Mathematics
Journal
Volume
Issue
ISSN
56
2
0030-364X
Citations 
PageRank 
References 
10
0.69
21
Authors
2
Name
Order
Citations
PageRank
Hengqing Ye110012.30
David D. Yao2861140.51