Abstract
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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