摘要:面向QoS优化的软实时周期任务在线半分区多处理器调度

Behnaz Sanati, A. Cheng
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引用次数: 3

摘要

只提供摘要形式。多处理器实时调度算法可能遵循分区或全局方法,或者两者的某种混合,称为半分区。半分区实时调度算法通过允许任务子集迁移来扩展分区调度算法。考虑到“减少开销”的目标,这种策略最好是有边界限制的,并允许迁移任务仅在连续调用之间迁移(作业边界)。无边界限制的调度器允许作业迁移,如果作业维护大量缓存状态,那么迁移作业在实践中可能代价高昂。以前提出的软实时(SRT)任务的半分区算法,如EDF-fm和EDF-os,有两个阶段:离线分配阶段,任务分配给处理器,固定任务(不迁移)与迁移任务区分开来;以及在线执行阶段。在执行阶段,使用扩展EDF调度的规则。这些策略的目的是尽量减少迟到。本文提出了一种基于在线奖励的半分区方法来调度同构多处理器系统中的周期性软实时任务。我们使用在线选择两种近似算法,贪心和负载平衡,用于分区,这提供了处理时间的优化使用。该方法不需要先验信息。因此,不存在脱机阶段。我们的目标是通过最小化延迟和最大化在最小makespan内完成任务所获得的总奖励来提高QoS。因此,我们允许根据基于奖励的优先级和处理器的工作负载,将任何任务的不同作业分配给不同的处理器(在作业边界上迁移)。该方法还可以通过定义相应的截止日期,扩展到具有混合任务集(非周期性、零星和周期性)的直接SRT系统。许多实时应用程序都可以从该解决方案中受益,包括但不限于视频流服务器、多人视频游戏、移动网上银行和医疗监控系统。
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Poster Abstract: Online Semi-Partitioned Multiprocessor Scheduling of Soft Real-Time Periodic Tasks for QoS Optimization
Summary form only given. Multiprocessor real-time scheduling algorithms may follow a partitioned or global approach or some hybrid of the two, called semi-partitioning. Semi-partitioned real-time scheduling algorithms extend partitioned ones by allowing a subset of tasks to migrate. Given the goal of “less overhead”, it is desirable for such strategy to be boundary-limited, and allow a migrating task to migrate only between successive invocations (job boundaries). Non-boundary-limited schedulers allow jobs to migrate, which can be expensive in practice, if jobs maintain much cached state. Previously proposed semi-partitioned algorithms for soft real-time (SRT) tasks such as EDF-fm and EDF-os, have two phases: an offline assignment phase, where tasks are assigned to processors and fixed tasks (which do not migrate) are distinguished from migrating ones; and an online execution phase. In their execution phase, rules that extend EDF scheduling are used. These strategies aim to minimize tardiness. In this paper, we propose a new online reward-based semi-partitioning approach to schedule periodic soft real-time tasks in homogeneous multiprocessor systems. We use an online choice of two approximation algorithms, Greedy and Load-Balancing, for partitioning, which provides an optimized usage of processing time. In this method, no prior information is needed. Hence, there is no offline phase. Our objective is to enhance the QoS by minimizing tardiness and maximizing the total reward obtained by completed tasks in minimum makespan. Therefore, we allow different jobs of any task get assigned to different processors (migration at job boundaries) based on their reward-based priorities and workload of the processors. This method can also extend to direct SRT systems with mixed set of tasks (aperiodic, sporadic and periodic) by defining their deadline accordingly. Many real-time applications can benefit from this solution including but not limited to video streaming servers, multi-player video games, mobile online banking and medical monitoring systems.
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