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Titlebook: Algorithmic Aspects of Cloud Computing; Third International Dan Alistarh,Alex Delis,George Pallis Conference proceedings 2018 Springer Int

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發(fā)表于 2025-3-21 16:50:51 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Algorithmic Aspects of Cloud Computing
期刊簡稱Third International
影響因子2023Dan Alistarh,Alex Delis,George Pallis
視頻videohttp://file.papertrans.cn/153/152902/152902.mp4
學(xué)科分類Lecture Notes in Computer Science
圖書封面Titlebook: Algorithmic Aspects of Cloud Computing; Third International  Dan Alistarh,Alex Delis,George Pallis Conference proceedings 2018 Springer Int
影響因子.This book constitutes the thoroughly refereed post-conferenceproceedings of the Second International Workshop on Algorithmic Aspectsof Cloud Computing, ALGOCLOUD 2017, held in Vienna, Austria, in September 2017..The 9 revised full papers were carefully reviewed and selected from 27 submissions.?.The aim of the workshop is to present research activities and results on topics related to algorithmic, design, and development aspects of modern cloud-based systems..
Pindex Conference proceedings 2018
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沙發(fā)
發(fā)表于 2025-3-21 20:51:43 | 只看該作者
978-3-319-74874-0Springer International Publishing AG 2018
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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/a/image/152902.jpg
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David Gontier,Jianfeng Lu,Christoph Ortnerrformance scientific domain, datacenters consist of low-cost servers for high-volume data processing, communication and storage. Datacenter owners prioritize capital and operating costs (often measured in performance per watt) over ultimate performance.
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Eduardo V. Lude?a,Roberto López-Boadaomputing infrastructure. This paper initiates the algorithmic study of the fundamental underlying problem of how to efficiently route traffic through a given set of Virtualized Network Functions (VNFs). We are given a link-capacitated network ., a source-destination pair . and a set of waypoints . (
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https://doi.org/10.1007/3-540-61132-0 much harder due to the dynamic nature of the workload and the fact that while long term statistics about the demand may be known, it is impossible to predict the exact demand in each point in time. As a result, service providers either over allocate resources and hurt the service cost efficiency, o
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https://doi.org/10.1007/3-540-61131-2g and storage engines, each featuring different models in computation, storage and execution as well as performance. Multi-Engine Analytics present a solution towards adaptive, cost-based complex workflow scheduling to the best available underlying technology. To achieve this in the Graph Analytics
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發(fā)表于 2025-3-23 05:52:26 | 只看該作者
https://doi.org/10.1007/3-540-61131-2se works aim to incorporate such information in a meaningful way in the computation of queries. In this paper, we propose a framework of query evaluation in the presence of uncertainty, based on probabilistic automata, which are simple yet efficient computational models. We showcase this method on r
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