Efficient Optimization of Constrained Nonlinear Resource Allocation

Mung Chiang, Arak Sutivong

Research output: Contribution to conferencePaperpeer-review

5 Scopus citations


We present an efficient method to optimize network resource allocations under nonlinear Quality of Service (QoS) constraints. We first propose a suite of generalized proportional allocation schemes that can be obtained by minimizing the information-theoretic function of relative entropy. We then optimize over the allocation parameters, which are usually design variables an engineer can directly vary, either for a particular user or for the worst-case user, under constraints that lower bound the allocated resources for all other users. Despite the non-linearity in the objective and constraints, we show this suite of resource allocation optimization can be efficiently solved for global optimality through a convex optimization technique called geometric programming. This general method and its extensions are applicable to a wide array of resource allocation problems, including processor sharing, congestion control, admission control, and wireless network power control. We provide a specific example to efficiently optimize an admission control scheme.

Original languageEnglish (US)
Number of pages5
StatePublished - 2003
EventIEEE Global Telecommunications Conference GLOBECOM'03 - San Francisco, CA, United States
Duration: Dec 1 2003Dec 5 2003


OtherIEEE Global Telecommunications Conference GLOBECOM'03
Country/TerritoryUnited States
CitySan Francisco, CA

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Global and Planetary Change


Dive into the research topics of 'Efficient Optimization of Constrained Nonlinear Resource Allocation'. Together they form a unique fingerprint.

Cite this