Stochastic optimal control for a general class of dynamic resource allocation problems

被引：0

作者：

机构：

[1] H. Milton Stewart School of ISyE, Georgia Institute of Technology, Atlanta

[2] Mathematical Sciences Department, IBM Thomas J. Watson Research Center, Yorktown Heights

[3] Centrum Wiskunde and Informatica

来源：

| 1600年 / Association for Computing Machinery, 2 Penn Plaza, Suite 701, New York, NY 10121-0701, United States卷 / 41期

关键词：

Resource allocation;

D O I：

10.1145/2518025.2518027

中图分类号：

学科分类号：

摘要：

We consider a general class of dynamic resource allocation problems within a stochastic optimal control framework. This class of problems arises in a wide variety of applications, each of which intrinsically involves resources of different types and demand with uncertainty and/or variability. The goal is to dynamically allocate capacity for every resource type in order to serve the uncertain/ variable demand and maximize the expected net-benefit over a time horizon of interest based on the rewards and costs associated with the different resources. We derive the optimal control policy within a singular control setting, which includes easily implementable algorithms for governing the dynamic adjustments to resource allocation capacities over time. Numerical experiments investigate various issues of both theoretical and practical interest, quantifying the significant benefits of our approach over alternative optimization approaches.

引用

页码：3 / 14

页数：11

共 19 条

[1]

Amur H., Cipar J., Gupta V., Ganger G., Kozuch M., Schwann K., Robust and flexible power-proportional storage, Proc. ACM SoCC, (2010)

[2]

Benes V., Shepp L., Witsenhausen H., Some solvable stochastic control problems, Stochastics, 4, 1, pp. 39-83, (1980)

[3]

Chen G., He W., Liu J., Nath S., Rigas L., Xiao L., Zhao F., Energy-aware server provisioning and load dispatching for connection-intensive Internet services, Proc. NSDI, (2008)

[4]

Ciocan D.F., Farias V., Model predictive control for dynamic resource allocation, Mathematics of Operations Research, 37, 3, pp. 501-525, (2012)

[5]

Clark C., Fraser K., Hand S., Hansen J., Jul E., Limpach C., Pratt I., Warfield A., Live migration of virtual machines, Proc. USENIX NSDI, (2005)

[6]

Gao X., Lu Y., Sharma M., Squillante M.S., Bosman J.W., Stochastic Optimal Control for A Class of Dynamic Resource Allocation Problems, (2012)

[7]

Ghosh S., Kalagnanam J., Katz D., Squillante M., Zhang X., Integration of demand response and renewable resources for power generation management, Proc. IEEE ISGT, (2011)

[8]

Guenter B., Jain N., Williams C., Managing cost, performance, and reliability tradeoffs for energy-aware server provisioning, Proc. IEEE INFOCOM, (2011)

[9]

Jagannathan K., Menache I., Modiano E., Zussman G., Non-cooperative spectrum access - The dedicated vs free spectrum choice, IEEE JSAC, 30, 11, (2012)

[10]

Karatzas I., Shreve S.E., Brownian Motion and Stochastic Calculus, (1991)

← 1 2 →