Network Topology and Communication-Computation Tradeoffs in Decentralized Optimization

In decentralized optimization, nodes cooperate to minimize an overall objective function that is the sum (or average) of per-node private objective functions. Algorithms interleave local computations with communication among all or a subset of the nodes. Motivated by a variety of applications..decen...

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Vydáno v:Proceedings of the IEEE Ročník 106; číslo 5; s. 953 - 976
Hlavní autoři: Nedic, Angelia, Olshevsky, Alex, Rabbat, Michael G.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.05.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Computer architecture
Consensus algorithms
Convergence
Decentralized control
distributed averaging
distributed optimization
gossip algorithms
Graph theory
Linear programming
multiagent systems
Multiple robots
Network topologies
Network topology
Optimization
Peer-to-peer computing
ISSN:0018-9219, 1558-2256
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Shrnutí:In decentralized optimization, nodes cooperate to minimize an overall objective function that is the sum (or average) of per-node private objective functions. Algorithms interleave local computations with communication among all or a subset of the nodes. Motivated by a variety of applications..decentralized estimation in sensor networks, fitting models to massive data sets, and decentralized control of multirobot systems, to name a few..significant advances have been made toward the development of robust, practical algorithms with theoretical performance guarantees. This paper presents an overview of recent work in this area. In general, rates of convergence depend not only on the number of nodes involved and the desired level of accuracy, but also on the structure and nature of the network over which nodes communicate (e.g., whether links are directed or undirected, static or time varying). We survey the state-of-theart algorithms and their analyses tailored to these different scenarios, highlighting the role of the network topology.
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ISSN:0018-9219
1558-2256
DOI:10.1109/JPROC.2018.2817461