Name
Abstract | ||
|---|---|---|
We present Overlapping Cluster Decomposition (OCD), a novel distributed algorithm for network optimization targeted for networks with dynamic demands and link prices. OCD uses a dual decomposition of the global problem into local optimization problems in each node's neighborhood. The local solutions are then reconciled to find the global optimal solution. While OCD is a descent method and thus may converge slowly in a static network, we show that OCD can more rapidly adapt to changing network conditions than previously proposed firstorder and Newton-like network optimization algorithms. Therefore, OCD yields better solutions over time than previously proposed methods at a comparable communication cost. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/Allerton.2012.6483208 | Communication, Control, and Computing |
Keywords | Field | DocType |
distributed algorithms,optimisation,OCD,descent method,distributed algorithm,dual decomposition,dynamic demands,link prices,network optimization,overlapping cluster decomposition | Mathematical optimization,Computer science,Distributed algorithm,Optimization algorithm,Local search (optimization),Network conditions,Distributed computing | Conference |
ISSN | ISBN | Citations |
2474-0195 | 978-1-4673-4537-8 | 1 |
PageRank | References | Authors |
0.35 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stacy Patterson | 1 | 1 | 0.35 |
| Mike P. Wittie | 2 | 164 | 15.71 |
| Kevin C. Almeroth | 3 | 2551 | 209.40 |
| Bamieh, B. | 4 | 73 | 4.27 |