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Titlebook: Cooperative Task-Oriented Computing; Algorithms and Compl Chryssis Georgiou,Alexander A. Shvartsman Book 2011 Springer Nature Switzerland A

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書目名稱Cooperative Task-Oriented Computing
副標(biāo)題Algorithms and Compl
編輯Chryssis Georgiou,Alexander A. Shvartsman
視頻videohttp://file.papertrans.cn/239/238015/238015.mp4
叢書名稱Synthesis Lectures on Distributed Computing Theory
圖書封面Titlebook: Cooperative Task-Oriented Computing; Algorithms and Compl Chryssis Georgiou,Alexander A. Shvartsman Book 2011 Springer Nature Switzerland A
描述Cooperative network supercomputing is becoming increasingly popular for harnessing the power of the global Internet computing platform. A typical Internet supercomputer consists of a master computer or server and a large number of computers called workers, performing computation on behalf of the master. Despite the simplicity and benefits of a single master approach, as the scale of such computing environments grows, it becomes unrealistic to assume the existence of the infallible master that is able to coordinate the activities of multitudes of workers. Large-scale distributed systems are inherently dynamic and are subject to perturbations, such as failures of computers and network links, thus it is also necessary to consider fully distributed peer-to-peer solutions. We present a study of cooperative computing with the focus on modeling distributed computing settings, algorithmic techniques enabling one to combine efficiency and fault-tolerance in distributed systems, and the exposition of trade-offs between efficiency and fault-tolerance for robust cooperative computing. The focus of the exposition is on the abstract problem, called Do-All, and formulated in terms of a system of
出版日期Book 2011
版次1
doihttps://doi.org/10.1007/978-3-031-02005-6
isbn_softcover978-3-031-00877-1
isbn_ebook978-3-031-02005-6Series ISSN 2155-1626 Series E-ISSN 2155-1634
issn_series 2155-1626
copyrightSpringer Nature Switzerland AG 2011
The information of publication is updating

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2155-1626 pical Internet supercomputer consists of a master computer or server and a large number of computers called workers, performing computation on behalf of the master. Despite the simplicity and benefits of a single master approach, as the scale of such computing environments grows, it becomes unrealis
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Conventional Time Study Rating, be optimal. Indeed, for any . tasks and . processors . under this assumption, all tasks are performed with constant computational overhead per task, and since only one processor ever completes an assigned task, the work is . = Θ. + . = Θ
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In this chapter, we consider the . problem in the message-passing model. We start by showing how to solve . by emulating shared memory in message-passing systems, then present algorithms that solve . using message passing directly. In particular, we present the following algorithms:
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In this final chapter, we survey selected additional research topics that deal with the . problem in the following distributed message-passing settings:
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