Dynamic Resource Provisioning and Scheduling with Deadline Constraint in Elastic Cloud
Dynamic Resource Provisioning and Scheduling with Deadline Constraint in Elastic Cloud
复制标题
弹性云中具有期限约束的动态资源供应和调度
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Junde Song
中科院分区：
文献类型：
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作者：
Guan Le;Ke Xu;Junde Song
云计算是构建未来大规模IT系统架构的关键技术，云计算的主要优势之一是根据请求工作负载的波动为其客户提供弹性资源。在本文中，我们提出了自适应的资源管理策略来处理弹性云的最后期限限制的应用程序的请求。提出了自适应资源管理体系结构，将资源管理分为资源提供和作业调度两部分。基于排队论，通过引入平均间隔时间这一关键指标，设计了自适应服务的解析模型。针对不同的作业执行顺序偏好，提出了先到先服务（FCFS）、最短作业优先（SJF）和最近截止日期优先（NDF）三种作业调度策略。模拟评估已经建立了与现实的网格工作负载，结果表明，我们的供应模型提供了弹性的资源供应的动态工作负载和FCFS实现了更好的性能相比，其他调度策略。
Cloud computing is the promising key technology to build future architecture of massive IT systems and one of key benefits of cloud computing is to provide its customers with elastic resources according to the fluctuation of request workloads. In this paper, we propose adaptive resource management policy to handle requests of deadline-bound application with elastic cloud. Adaptive resource management architecture has been proposed, and we divide resource management into two parts, resource provision and job scheduling. We design analytical provision model for adaptive provision based on queuing theory, by introducing a key metric named average interval time. Three job scheduling policies are raised to dequeue appropriate jobs to execute, First-Come-First-Service (FCFS), Shortest Job First (SJF) and Nearest Deadline First (NDF), for different preference toward execution order. Simulation evaluation has been set up with realistic grid workload, and results show that our provisioning model gives elastic resource provisioning for dynamic workload and FCFS achieves better performance compared with other scheduling policies.