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Distributed algorithm

About: Distributed algorithm is a research topic. Over the lifetime, 20416 publications have been published within this topic receiving 548109 citations.


Papers
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Proceedings ArticleDOI
08 May 2006
TL;DR: The algorithm, called NCBB, is branch and bound search with modifications for efficiency in a multiagent setting, which has significantly better performance than another polynomial-space algorithm, ADOPT, on random graph coloring problems.
Abstract: We present a new polynomial-space algorithm for solving Distributed Constraint Optimization problems (DCOP). The algorithm, called NCBB, is branch and bound search with modifications for efficiency in a multiagent setting. Two main features of the algorithm are: (a) using different agents to search non-intersecting parts of a search space concurrently, and (b) communicating lower bounds on solution cost every time there is a possibility the bounds might change due to changed variable assignments. The first leads to a better utilization of computational resources of multiple participating agents, while the second provides for more efficient pruning of search space.Experimental results show that NCBB has significantly better performance than another polynomial-space algorithm, ADOPT, on random graph coloring problems. Under assumptions of cheap communication it also has comparable performance with DPOP despite using only polynomial memory as opposed to exponential memory for DPOP.

118 citations

Journal ArticleDOI
TL;DR: This work determines the call blocking performance of channel-allocation algorithms where every channel is available for use in every cell and where decisions are made by mobiles/portables based only on local observations and suggests that an aggressive algorithm could provide a substantially reduced blocking probability.
Abstract: We determine the call blocking performance of channel-allocation algorithms where every channel is available for use in every cell and where decisions are made by mobiles/portables based only on local observations. Using a novel Erlang-B approximation method, together with simulation, we demonstrate that even the simplest algorithm, the timid, compares favorably with impractical, centrally administered fixed channel allocation. Our results suggest that an aggressive algorithm, that is, one requiring call reconfigurations, could provide a substantially reduced blocking probability. We also present some algorithms which take major steps toward achieving the excellent blocking performance of the hypothetical aggressive algorithm but having the stability of the timid algorithm. >

118 citations

Journal ArticleDOI
TL;DR: This letter proposes a distributed algorithm which requires only local information and is scalable to a large number of UAV-BSs and proves its convergence and conduct simulations with a real data set to evaluate its performance.
Abstract: This letter studies the network performance improvement by deploying flying base stations mounted on unmanned aerial vehicles (UAV-BSs) during some occasional events. Specifically, we consider the problem to minimize the average UAV-user distance while keeping the UAV-BSs connected to the stationary base stations. We propose a distributed algorithm which requires only local information and is scalable to a large number of UAV-BSs. We prove its convergence and conduct simulations with a real data set to evaluate its performance.

118 citations

Proceedings ArticleDOI
02 May 2001
TL;DR: A distributed version of the algorithm for model-checking LTL that performs nested depth-first search algorithm in distributed SPIN is presented, and its complexity is discussed.
Abstract: In this paper we propose a distributed algorithm for model-checking LTL. In particular, we explore the possibility of performing nested depth-first search algorithm in distributed SPIN. A distributed version of the algorithm is presented, and its complexity is discussed.

118 citations

Journal ArticleDOI
TL;DR: The structure of the dual allows the successful application of a distributed asynchronous method whereby relaxation iterations are carried out in parallel by several processors in arbitrary order and with arbitrarily large interprocessor communication delays.
Abstract: We consider the solution of the single commodity strictly convex network flow problem in a distributed asynchronous computation environment. The dual of this problem is unconstrained, differentiable, and well suited for solution via Gauss-Seidel relaxation. We show that the structure of the dual allows the successful application of a distributed asynchronous method whereby relaxation iterations are carried out in parallel by several processors in arbitrary order and with arbitrarily large interprocessor communication delays.

117 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202381
2022135
2021583
2020759
2019876
2018845