To Örebro University

In this paper, we propose a new protocol for handling resource sharing among prioritized real-time applications composed on a multiprocessor platform. We propose an optimal priority assignment algorithm which assigns unique priorities to the applications based on information in their interfaces. We have performed experimental evaluations to compare the proposed protocol (called MSOS-Priority) to the current state of the art locking protocols under multiprocessor partitioned scheduling, i.e., MPCP, MSRP, FMLP, MSOS, and OMLP. The valuations show that MSOS-Priority mostly performs significantly better than alternative approaches.

Semi-partitioned scheduling has become the subject of recent interest for multiprocessors due to better utilization results, compared to conventional global and partitioned scheduling algorithms. Under semi-partitioned scheduling, a major group of tasks are assigned to fixed processors while a low number of tasks are allocated to more than one processor. Various task assigning techniques have recently been proposed in a semi-partitioned environment. However, a synchronization mechanism for resource sharing among tasks in semi-partitioned scheduling has not yet been investigated. In this paper we propose and evaluate two methods for handling resource sharing under semi-partitioned scheduling in multiprocessor platforms. The main challenge addressed in this paper is to serve the resource requests of tasks that are assigned to different processors.

Semi-partitioned scheduling has been the subject of recent interest, compared with conventional global and partitioned scheduling algorithms for multiprocessors, due to better utilization results. In semi-partitioned scheduling most tasks are assigned to fixed processors while a low number of tasks are split up and allocated to different processors. Various techniques have recently been proposed to assign tasks in a semi-partitioned environment. However, an appropriate resource sharing mechanism for handling the resource requests between tasks in semi-partitioned scheduling has not yet been investigated. In this paper we propose two methods for handling resource sharing under semi-partitioned scheduling in multiprocessor platforms. The main challenge is to handle the resource requests of tasks that are split over multiple processors.