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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.


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Journal ArticleDOI
TL;DR: Information-weighted consensus algorithms for distributed maximum a posteriori parameter estimation, and their extension to the information- Weighted consensus filter (ICF) for state estimation are proposed.
Abstract: Due to their high fault-tolerance and scalability to large networks, consensus-based distributed algorithms have recently gained immense popularity in the sensor networks community. Large-scale camera networks are a special case. In a consensus-based state estimation framework, multiple neighboring nodes iteratively communicate with each other, exchanging their own local information about each target's state with the goal of converging to a single state estimate over the entire network. However, the state estimation problem becomes challenging when some nodes have limited observability of the state. In addition, the consensus estimate is suboptimal when the cross-covariances between the individual state estimates across different nodes are not incorporated in the distributed estimation framework. The cross-covariance is usually neglected because the computational and bandwidth requirements for its computation become unscalable for a large network. These limitations can be overcome by noting that, as the state estimates at different nodes converge, the information at each node becomes correlated. This fact can be utilized to compute the optimal estimate by proper weighting of the prior state and measurement information. Motivated by this idea, we propose information-weighted consensus algorithms for distributed maximum a posteriori parameter estimation, and their extension to the information-weighted consensus filter (ICF) for state estimation. We compare the performance of the ICF with existing consensus algorithms analytically, as well as experimentally by considering the scenario of a distributed camera network under various operating conditions.

254 citations

Journal ArticleDOI
TL;DR: This paper presents an overview of the SDD-1 design and its solutions to the above problems.
Abstract: The declining cost of computer hardware and the increasing data processing needs of geographically dispersed organizations have led to substantial interest in distributed data management. SDD-1 is a distributed database management system currently being developed by Computer Corporation of America. Users interact with SDD-1 precisely as if it were a nondistributed database system because SDD-1 handles all issues arising from the distribution of data. These issues include distributed concurrency control, distributed query processing, resiliency to component failure, and distributed directory management. This paper presents an overview of the SDD-1 design and its solutions to the above problems.This paper is the first of a series of companion papers on SDD-1 (Bernstein and Shipman [2], Bernstein et al. [4], and Hammer and Shipman [14]).

253 citations

Journal ArticleDOI
TL;DR: Several paradigms—examples or models—for process interaction in distributed computations are described, illustrated by solving problems, including parallel sorting, file servers, computing the topology of a network, distributed termination detection, replicated databases, and parallel adaptive quadrature.
Abstract: Distributed computations are concurrent programs in which processes communicate by message passing. Such programs typically execute on network architectures such as networks of workstations or distributed memory parallel machines (i.e., multicomputers such as hypercubes). Several paradigms—examples or models—for process interaction in distributed computations are described. These include networks of filters, clients, and servers, heartbeat algorithms, probe/echo algorithms, broadcast algorithms, token-passing algorithms, decentralized servers, and bags of tasks. These paradigms are appliable to numerous practical problems. They are illustrated by solving problems, including parallel sorting, file servers, computing the topology of a network, distributed termination detection, replicated databases, and parallel adaptive quadrature. Solutions to all problems are derived in a step-wise fashion from a general specification of the problem to a concrete solution. The derivations illustrate techniques for developing distributed algorithms.

252 citations

Proceedings ArticleDOI
14 Sep 2003
TL;DR: Algorithms for finding minimum energy disjoint paths in an all-wireless network are developed, for both the node and link-disjoint cases, and it is found that link- Disjointpaths consume substantially less energy than node-disJoint paths.
Abstract: We develop algorithms for finding minimum energy disjoint paths in an all-wireless network, for both the node and link-disjoint cases. Our major results include a novel polynomial time algorithm that optimally solves the minimum energy 2 link-disjoint paths problem, as well as a polynomial time algorithm for the minimum energy k node-disjoint paths problem. In addition, we present efficient heuristic algorithms for both problems. Our results show that link-disjoint paths consume substantially less energy than node-disjoint paths. We also found that the incremental energy of additional link-disjoint paths is decreasing. This finding is somewhat surprising due to the fact that in general networks additional paths are typically longer than the shortest path. However, in a wireless network, additional paths can be obtained at lower energy due to the broadcast nature of the wireless medium. Finally, we discuss issues regarding distributed implementation and present distributed versions of the optimal centralized algorithms presented in the paper.

252 citations

Journal ArticleDOI
TL;DR: An Improved Genetic Algorithm to solve the Distributed and Flexible Job-shop Scheduling problem is proposed and has been compared with other algorithms for distributed scheduling and evaluated with satisfactory results on a large set of distributed-and-flexible scheduling problems derived from classical job-shop scheduling benchmarks.

252 citations


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