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An efficient deadline constrained and data locality aware dynamic scheduling framework for multitenancy clouds
Concurrency and Computation: Practice and Experience ( IF 2 ) Pub Date : 2020-09-30 , DOI: 10.1002/cpe.6037
Jia Ru 1 , Yun Yang 1 , John Grundy 2 , Jacky Keung 3 , Li Hao 4
Affiliation  

Scheduling and resource allocation in clouds is used to harness the power of the underlying resource pool. Service providers can meet quality of service (QoS) requirements of tenants specified in Service Level Agreements. Improving resource allocation ensures that all tenants will receive fairer access to system resources, which improves overall utilization and throughput. Real‐time applications and services require critical deadlines in order to guarantee QoS. A growing number of data‐intensive applications drive the optimization of scheduling through utilizing data locality in which the scheduler locates a task and ensures the task's relevant data to be on the same server. Choosing suitable scheduling mechanisms for running applications that support multitenancy has consistently been a major challenge. This work proposes a new adaptive Deadline constrained and Data locality aware Dynamic Scheduling Framework “ 3DSF“ that orchestrates different schedulers based on varied requirements. This framework considers tenants' deadline‐based QoS requirements, cloud system's performance and a method of resource allocation to improve resource utilization, system throughput and reduce jobs' completion time. 3DSF contains: (a) a real‐time, preemptive, deadline constrained job scheduler, (b) an optimized data locality aware scheduler, (c) an improved Dominant Resource Fairness greedy resource allocation approach, and (d) an adaptive suite to integrate above‐mentioned schedulers together.

中文翻译:

针对多租户云的有效的截止日期约束和数据位置感知的动态调度框架

云中的调度和资源分配用于利用基础资源池的功能。服务提供商可以满足服务水平协议中指定的租户的服务质量(QoS)要求。改善资源分配可确保所有租户都能更公平地访问系统资源,从而提高了整体利用率和吞吐量。实时应用程序和服务需要关键的截止日期才能保证QoS。越来越多的数据密集型应用程序通过利用调度程序在其中定位任务并确保任务的相关数据位于同一服务器上的数据局部性来推动调度的优化。为运行支持多租户的应用程序选择合适的调度机制一直是一个重大挑战。这项工作提出了一种新的自适应截止日期约束和数据局部性感知的动态调度框架“ 3DSF”,该框架根据不同的需求来协调不同的调度器。该框架考虑了租户基于截止日期的QoS要求,云系统的性能以及一种提高资源利用率,系统吞吐量和减少作业完成时间的资源分配方法。3DSF包含:(a)实时,抢占式,截止日期受限的作业调度程序,(b)优化的数据位置感知调度程序,(c)改进的“主导资源公平性”贪婪资源分配方法,以及(d)集成的自适应套件上述调度程序一起。该框架考虑了租户基于截止日期的QoS要求,云系统的性能以及一种提高资源利用率,系统吞吐量并减少作业完成时间的资源分配方法。3DSF包含:(a)实时,抢占式,截止日期受限的作业调度程序,(b)优化的数据位置感知调度程序,(c)改进的“主导资源公平性”贪婪资源分配方法,以及(d)集成的自适应套件上述调度程序一起。该框架考虑了租户基于截止日期的QoS要求,云系统的性能以及一种提高资源利用率,系统吞吐量并减少作业完成时间的资源分配方法。3DSF包含:(a)实时,抢占式,截止日期受限的作业调度程序,(b)优化的数据位置感知调度程序,(c)改进的“主导资源公平性”贪婪资源分配方法,以及(d)集成的自适应套件上述调度程序一起。
更新日期:2020-09-30
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