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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
04 Nov 2010
TL;DR: This paper analytically model the subscribers' preferences and their energy consumption patterns in form of carefully selected utility functions based on concepts from microeconomics and proposes a distributed algorithm which automatically manages the interactions among the ECC units at the smart meters and the energy provider.
Abstract: In this paper, we consider a smart power infrastructure, where several subscribers share a common energy source. Each subscriber is equipped with an energy consumption controller (ECC) unit as part of its smart meter. Each smart meter is connected to not only the power grid but also a communication infrastructure such as a local area network. This allows two-way communication among smart meters. Considering the importance of energy pricing as an essential tool to develop efficient demand side management strategies, we propose a novel real-time pricing algorithm for the future smart grid. We focus on the interactions between the smart meters and the energy provider through the exchange of control messages which contain subscribers' energy consumption and the real-time price information. First, we analytically model the subscribers' preferences and their energy consumption patterns in form of carefully selected utility functions based on concepts from microeconomics. Second, we propose a distributed algorithm which automatically manages the interactions among the ECC units at the smart meters and the energy provider. The algorithm finds the optimal energy consumption levels for each subscriber to maximize the aggregate utility of all subscribers in the system in a fair and efficient fashion. Finally, we show that the energy provider can encourage some desirable consumption patterns among the subscribers by means of the proposed real-time pricing interactions. Simulation results confirm that the proposed distributed algorithm can potentially benefit both subscribers and the energy provider.

995 citations

Journal ArticleDOI
TL;DR: In this article, an abstract model and a comprehensive taxonomy for describing resource management architectures is developed, which is used to identify approaches followed in the implementation of existing resource management systems for very large-scale network computing systems known as Grids.
Abstract: The resource management system is the central component of distributed network computing systems. There have been many projects focused on network computing that have designed and implemented resource management systems with a variety of architectures and services. In this paper, an abstract model and a comprehensive taxonomy for describing resource management architectures is developed. The taxonomy is used to identify approaches followed in the implementation of existing resource management systems for very large-scale network computing systems known as Grids. The taxonomy and the survey results are used to identify architectural approaches and issues that have not been fully explored in the research. Copyright © 2001 John Wiley & Sons, Ltd.

993 citations

Journal ArticleDOI
TL;DR: The paper presents the “textbook” architecture for distributed query processing and a series of techniques that are particularly useful for distributed database systems, and discusses different kinds of distributed systems such as client-server, middleware (multitier), and heterogeneous database systems and shows how query processing works in these systems.
Abstract: Distributed data processing is becoming a reality. Businesses want to do it for many reasons, and they often must do it in order to stay competitive. While much of the infrastructure for distributed data processing is already there (e.g., modern network technology), a number of issues make distributed data processing still a complex undertaking: (1) distributed systems can become very large, involving thousands of heterogeneous sites including PCs and mainframe server machines; (2) the state of a distributed system changes rapidly because the load of sites varies over time and new sites are added to the system; (3) legacy systems need to be integrated—such legacy systems usually have not been designed for distributed data processing and now need to interact with other (modern) systems in a distributed environment. This paper presents the state of the art of query processing for distributed database and information systems. The paper presents the “textbook” architecture for distributed query processing and a series of techniques that are particularly useful for distributed database systems. These techniques include special join techniques, techniques to exploit intraquery paralleli sm, techniques to reduce communication costs, and techniques to exploit caching and replication of data. Furthermore, the paper discusses different kinds of distributed systems such as client-server, middleware (multitier), and heterogeneous database systems, and shows how query processing works in these systems.

980 citations

Proceedings Article
10 Jun 2002
TL;DR: A distributed algorithm for determining the positions of nodes in an ad-hoc, wireless sensor network is explained in detail and shows that, given an average connectivity of at least 12 nodes and 10% anchors, the algorithm performs well with up to 40% errors in distance measurements.
Abstract: A distributed algorithm for determining the positions of nodes in an ad-hoc, wireless sensor network is explained in detail. Details regarding the implementation of such an algorithm are also discussed. Experimentation is performed on networks containing 400 nodes randomly placed within a square area, and resulting error magnitudes are represented as percentages of each node’s radio range. In scenarios with 5% errors in distance measurements, 5% anchor node population (nodes with known locations), and average connectivity levels between neighbors of 7 nodes, the algorithm is shown to have errors less than 33% on average. It is also shown that, given an average connectivity of at least 12 nodes and 10% anchors, the algorithm performs well with up to 40% errors in distance measurements.

967 citations

Proceedings ArticleDOI
01 Dec 2005
TL;DR: An old distributed algorithm for reaching consensus that has received a fair amount of recent attention is discussed, in which a number of agents exchange their values asynchronously and form weighted averages with (possibly outdated) values possessed by their neighbors.
Abstract: We discuss an old distributed algorithm for reaching consensus that has received a fair amount of recent attention. In this algorithm, a number of agents exchange their values asynchronously and form weighted averages with (possibly outdated) values possessed by their neighbors. We overview existing convergence results, and establish some new ones, for the case of unbounded intercommunication intervals.

964 citations


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