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

Abridge

书目名称Algorithmic Aspects of Cloud Computing影响因子(影响力)




书目名称Algorithmic Aspects of Cloud Computing影响因子(影响力)学科排名




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书目名称Algorithmic Aspects of Cloud Computing网络公开度学科排名




书目名称Algorithmic Aspects of Cloud Computing被引频次




书目名称Algorithmic Aspects of Cloud Computing被引频次学科排名




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书目名称Algorithmic Aspects of Cloud Computing年度引用学科排名




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书目名称Algorithmic Aspects of Cloud Computing读者反馈学科排名

魔鬼在游行

978-3-319-74874-0Springer International Publishing AG 2018

overture

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/a/image/152902.jpg

DAMP

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.

枫树

Eduardo V. Ludeña,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 . (

强所

Ancillary

Supplement

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

gregarious

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

斜坡

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