Jointly optimal congestion and contention control based on network utility maximization

Jang Won Lee; Mung Chiang; A. Robert Calderbank

doi:10.1109/LCOMM.2006.1603389

Jointly optimal congestion and contention control based on network utility maximization

Jang Won Lee, Mung Chiang, A. Robert Calderbank

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Article › peer-review

108 Citations (Scopus)

Abstract

We study joint end-to-end congestion control and per-link medium access control (MAC) in ad-hoc networks. We use a network utility maximization formulation, in which by adjusting the types of utility functions, we can accommodate multi-class services as well as exploit the tradeoff between efficiency and fairness of resource allocation. Despite the inherent difficulties of non-convexity and non-separability of the optimization problem, we show that, with readily-verifiable sufficient conditions, we can develop a distributed algorithm that converges to the globally and jointly optimal rate allocation and persistence probabilities.

Original language	English
Pages (from-to)	216-218
Number of pages	3
Journal	IEEE Communications Letters
Volume	10
Issue number	3
DOIs	https://doi.org/10.1109/LCOMM.2006.1603389
Publication status	Published - 2006 Mar

Bibliographical note

Funding Information:
Manuscript received September 10, 2005. The associate editor coordinating the review of this letter and approving it for publication was Prof. Iakovos Venieris. This work was supported by Yonsei University research fund of 2005 and NSF Grants CCF-0440443, CNS-0417607, CCF-0448012, and CNS-0427677.

All Science Journal Classification (ASJC) codes

Modelling and Simulation
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/LCOMM.2006.1603389

Cite this

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AB - We study joint end-to-end congestion control and per-link medium access control (MAC) in ad-hoc networks. We use a network utility maximization formulation, in which by adjusting the types of utility functions, we can accommodate multi-class services as well as exploit the tradeoff between efficiency and fairness of resource allocation. Despite the inherent difficulties of non-convexity and non-separability of the optimization problem, we show that, with readily-verifiable sufficient conditions, we can develop a distributed algorithm that converges to the globally and jointly optimal rate allocation and persistence probabilities.

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Jointly optimal congestion and contention control based on network utility maximization

Abstract

Bibliographical note

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