NDLI: Convergence analysis of distributed subgradient methods over random networks

Content Provider	IEEE Xplore Digital Library
Author	Lobel, I. Ozdaglar, A.
Copyright Year	2008
Description	Author affiliation: Oper. Res. Center, Massachusetts Inst. of Technol., Cambridge, MA (Lobel, I.) \|\| Dept. of Electr. Eng. & Comput. Sci., Massachusetts Inst. of Technol., Cambridge, MA (Ozdaglar, A.)
Abstract	We consider the problem of cooperatively minimizing the sum of convex functions, where the functions represent local objective functions of the agents. We assume that each agent has information about his local function, and communicate with the other agents over a time-varying network topology. For this problem, we propose a distributed subgradient method that uses averaging algorithms for locally sharing information among the agents. In contrast to previous works that make worst-case assumptions about the connectivity of the agents (such as bounded communication intervals between nodes), we assume that links fail according to a given stochastic process. Under the assumption that the link failures are independent and identically distributed over time (possibly correlated across links), we provide convergence results and convergence rate estimates for our subgradient algorithm.
Starting Page	353
Ending Page	360
File Size	629435
Page Count	8
File Format	PDF
ISBN	9781424429257
DOI	10.1109/ALLERTON.2008.4797579
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-09-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wireless sensor networks Network servers Operations research Network topology Stochastic processes Optimization methods Communication system control Cost function Computer networks Convergence
Content Type	Text
Resource Type	Article

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