ﻻ يوجد ملخص باللغة العربية
This paper presents a new strategy for scheduling soft real-time tasks on multiple identical cores. The proposed approach is based on partitioned CPU reservations and it uses a reclaiming mechanism to reduce the number of missed deadlines. We introduce the possibility for a task to temporarily migrate to another, less charged, CPU when it has exhausted the reserved bandwidth on its allocated CPU. In addition, we propose a simple load balancing method to decrease the number of deadlines missed by the tasks. The proposed algorithm has been evaluated through simulations, showing its effectiveness (compared to other multi-core reclaiming approaches) and comparing the performance of different partitioning heuristics (Best Fit, Worst Fit and First Fit).
When integrating hard, soft and non-real-time tasks in general purpose operating systems, it is necessary to provide temporal isolation so that the timing properties of one task do not depend on the behaviour of the others. However, strict budget enf
Real-time scheduling and locking protocols are fundamental facilities to construct time-critical systems. For parallel real-time tasks, predictable locking protocols are required when concurrent sub-jobs mutually exclusive access to shared resources.
Recent commercial hardware platforms for embedded real-time systems feature heterogeneous processing units and computing accelerators on the same System-on-Chip. When designing complex real-time application for such architectures, the designer needs
In this paper, we propose a synchronous protocol without periodicity for scheduling multi-mode real-time systems upon identical multiprocessor platforms. Our proposal can be considered to be a multiprocessor extension of the uniprocessor protocol called Minimal Single Offset protocol.
Myopic is a hard real-time process scheduling algorithm that selects a suitable process based on a heuristic function from a subset (Window)of all ready processes instead of choosing from all available processes, like original heuristic scheduling al