Faster Linear Iterations for Distributed Averaging
2008 (English)In: Proceedings of the 17th IFAC World Congress, 2008, 2008Conference paper (Refereed)
Distributed averaging problems are a subclass of distributed consensus problems,which have received substantial attention from several research communities. Although many ofthe proposed algorithms are linear iterations, they vary both in structure and state dimension.In this paper, we investigate the performance benefits of adding extra states to distributedaveraging iterations. We establish conditions for convergence and discuss possible ways ofoptimizing the convergence rates. By numerical examples, it is shown that the performance canbe significantly increased by adding extra states. Finally, we provide necessary and sufficientconditions for convergence of a more general version of distributed averaging iterations.
Place, publisher, year, edition, pages
IdentifiersURN: urn:nbn:se:kth:diva-79739DOI: 10.3182/20080706-5-KR-1001.00482OAI: oai:DiVA.org:kth-79739DiVA: diva2:499915
Faster Linear Iterations for Distributed Averaging. World Congress. COEX, Korea, South. 2008-07-06 - 2008-07-11
QC 201205072012-02-132012-02-092012-10-18Bibliographically approved