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Titlebook: Job Scheduling Strategies for Parallel Processing; 15th International W Eitan Frachtenberg,Uwe Schwiegelshohn Conference proceedings 2010 T

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发表于 2025-3-21 16:19:04 | 显示全部楼层 |阅读模式
书目名称Job Scheduling Strategies for Parallel Processing
副标题15th International W
编辑Eitan Frachtenberg,Uwe Schwiegelshohn
视频video
概述unique visibility, state-of-the-art research,.fast-track conference proceedings
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Job Scheduling Strategies for Parallel Processing; 15th International W Eitan Frachtenberg,Uwe Schwiegelshohn Conference proceedings 2010 T
出版日期Conference proceedings 2010
关键词cloud computing; cluster computing; distributed computing; grid computing; grid workload; job scheduling;
版次1
doihttps://doi.org/10.1007/978-3-642-16505-4
isbn_softcover978-3-642-16504-7
isbn_ebook978-3-642-16505-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer-Verlag GmbH, DE
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Resource Provisioning in SLA-Based Cluster Computing,rallel computation for high service performance, availability, and reliability while satisfying a QoS and a fee negotiated between a customer and the application service provider. Simulation experiments demonstrate the applicability of the approach.
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An Advance Reservation-Based Co-allocation Algorithm for Distributed Computers and Network Bandwidt-allocation of both computing and network resources provided by multiple domains, and can reflect reservation options for resource administrators issues as a first step. The calculation times needed for selecting resources using an IP solver are acceptable for an on-line service.
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Risk Aware Overbooking for Commercial Grids,s the risk of SLA violations. This work presents an overbooking approach with an integrated risk assessment model. Simulations for this model, which are based on real-world job traces, show that overbooking offers significant opportunities for Grid and Cloud providers.
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Dynamic Proportional Share Scheduling in Hadoop,adline or budget optimizing agents on behalf of users. We describe the design and implementation of the DP scheduler and experimental results. We show that our scheduler enforces service levels more accurately and also scales to more users with distinct service levels than existing schedulers.
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978-3-642-16504-7The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer-Verlag GmbH, DE
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