Asynchronous subgradient methods with unbounded delays for communication networks

Nikolaos Gatsis, Georgios B Giannakis

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations

Abstract

Dual decomposition coupled with the subgradient method has found application to optimal resource management in communication networks, as it can lead to distributed and scalable algorithms. Network entities - nodes or functional layers - exchange Lagrange multipliers and primal minimizers of the Lagrangian function towards optimizing a network-wide performance metric. It is of interest to study the performance of the resultant algorithms when such exchanges are delayed or lost. This paper deals with such asynchronous dual subgradient methods in separable convex programming. In this scenario, the subgradient vector is a sum of components, each possibly corresponding to an outdated Lagrange multiplier, and not the current one. A number of network entities is allowed to prematurely stop updating their corresponding variables, thereby effecting infinite delay between the current iterate and the multipliers used for a number of subgradient components. Conditions for convergence of the algorithm are developed. Specific applications include multipath routing in wireline networks and cross-layer optimization in wireless networks. Numerical tests for multipath routing in the Abilene network topology are presented.

Original languageEnglish (US)
Article number6426107
Pages (from-to)5870-5875
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
DOIs
StatePublished - Dec 1 2012
Event51st IEEE Conference on Decision and Control, CDC 2012 - Maui, HI, United States
Duration: Dec 10 2012Dec 13 2012

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