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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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Journal ArticleDOI
TL;DR: An energy-efficient distributed multichannel MAC protocol for CR networks (MMAC-CR), which significantly improves performance by borrowing the licensed spectrum and protects primary users (PUs) from interference, even in hidden terminal situations.
Abstract: A cognitive radio (CR) network should be able to sense its environment and adapt communication to utilize the unused licensed spectrum without interfering with licensed users. In this paper, we look at CR-enabled networks with distributed control. As CR nodes need to hop from channel to channel to make the most use of the spectrum opportunities, we believe distributed multichannel medium access control (MAC) protocols to be key enablers for these networks. In addition to the spectrum scarcity, energy is rapidly becoming one of the major bottlenecks of wireless operations and has to be considered as a key design criterion. We present here an energy-efficient distributed multichannel MAC protocol for CR networks (MMAC-CR). Simulation results show that the proposed protocol significantly improves performance by borrowing the licensed spectrum and protects primary users (PUs) from interference, even in hidden terminal situations. Sensing costs are evaluated and shown to contribute only 5% to the total energy cost.

209 citations

Journal ArticleDOI
17 Oct 2008
TL;DR: It is argued that distributed smart cameras represent key components for future embedded computer vision systems and that smart cameras will become an enabling technology for many new applications.
Abstract: Distributed smart cameras (DSCs) are real-time distributed embedded systems that perform computer vision using multiple cameras. This new approach has emerged thanks to a confluence of simultaneous advances in four key disciplines: computer vision, image sensors, embedded computing, and sensor networks. Processing images in a network of distributed smart cameras introduces several complications. However, we believe that the problems DSCs solve are much more important than the challenges of designing and building a distributed video system. We argue that distributed smart cameras represent key components for future embedded computer vision systems and that smart cameras will become an enabling technology for many new applications. We summarize smart camera technology and applications, discuss current trends, and identify important research challenges.

209 citations

Journal ArticleDOI
TL;DR: Cambridge University researchers developed middleware extensions that provide a flexible, scalable approach to distributed-application development that has provided support for emerging applications.
Abstract: In the late 1980s, software designers introduced middleware platforms to support distributed computing systems. Since then, the rapid evolution of technology has caused an explosion of distributed-processing requirements. Application developers now routinely expect to support multimedia systems and mobile users and computers. Timely response to asynchronous events is crucial to such applications, but current platforms do not adequately meet this need. Another need of existing and emerging applications is the secure interoperability of independent services in large-scale, widely distributed systems. Information systems serving organizations such as universities, hospitals, and government agencies require cross-domain interaction. To meet the needs of these applications, Cambridge University researchers developed middleware extensions that provide a flexible, scalable approach to distributed-application development. This article details the extensions they developed, explaining their distributed software approach and the support it has provided for emerging applications.

208 citations

Book
12 Mar 1997
TL;DR: Distributed Simulation brings together the many complex technologies for distributed simulation, including object-oriented, multilevel, and multi-resolution simulation, with strong emphasis on emerging simulation methodologies.
Abstract: From the Publisher: Simulation is a multi-disciplinary field, and significantsimulation research is dispersed across multiple fields of study. Distributed computer systems, software design methods, and new simulation techniques offer synergistic multipliers when joined together in a distributed simulation. Systems of most interest to the simulation practitioner are often the most difficult to model and implement. Distributed Simulation brings together the many complex technologies for distributed simulation. There is strong emphasis on emerging simulation methodologies, including object-oriented, multilevel, and multi-resolution simulation. Finally, one concise text provides a strong foundation for the development of high fidelity simulations in heterogeneous distributed computing environments!

208 citations

Journal ArticleDOI
TL;DR: This work introduces self-stabilizing protocols for synchronization that are used as building blocks by the leader-election algorithm and presents a simple, uniform, self-Stabilizing ranking protocol.
Abstract: A distributed system is self-stabilizing if it can be started in any possible global state. Once started the system regains its consistency by itself, without any kind of outside intervention. The self-stabilization property makes the system tolerant to faults in which processors exhibit a faulty behavior for a while and then recover spontaneously in an arbitrary state. When the intermediate period in between one recovery and the next faulty period is long enough, the system stabilizes. A distributed system is uniform if all processors with the same number of neighbors are identical. A distributed system is dynamic if it can tolerate addition or deletion of processors and links without reinitialization. In this work, we study uniform dynamic self-stabilizing protocols for leader election under readwrite atomicity. Our protocols use randomization to break symmetry. The leader election protocol stabilizes in O(/spl Delta/D log n) time when the number of the processors is unknown and O(/spl Delta/D), otherwise. Here /spl Delta/ denotes the maximal degree of a node, D denotes the diameter of the graph and n denotes the number of processors in the graph. We introduce self-stabilizing protocols for synchronization that are used as building blocks by the leader-election algorithm. We conclude this work by presenting a simple, uniform, self-stabilizing ranking protocol.

208 citations


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