A Review of Priority Assignment in Real-Time Systems

It is over 40 years since the first seminal work on priority assignment for real-time systems using fixed priority scheduling. Since then, huge progress has been made in the field of real-time scheduling with more complex models and schedulability analysis techniques developed to better represent and analyse real systems. This tutorial style review provides an in-depth assessment of priority assignment techniques for hard real-time systems scheduled using fixed priorities. It examines the role and importance of priority in fixed priority scheduling in all of its guises, including: preemptive and non-pre-emptive scheduling; covering single- and multi-processor systems, and networks. A categorisation of optimal priority assignment techniques is given, along with the conditions on their applicability. We examine the extension of these techniques via sensitivity analysis to form robust priority assignment policies that can be used even when there is only partial information available about the system. The review covers priority assignment in a wide variety of settings including: mixed-criticality systems, systems with deferred pre-emption, and probabilistic real-time systems with worstcase execution times described by random variables. It concludes with a discussion of open problems in the area of priority assignment

Task Allocation and Optimization of Distributed Embedded Systems with Simulated Annealing and Geometric Programming

We consider the task model of periodic tasks running on a network of processor nodes connected by a bus based on the time-triggered protocol, an industry-standard bus protocol designed for safety-critical automotive and avionics distributed embedded systems, and present an integrated optimization framework that jointly considers one or more of the following attributes: task-to-processor allocation, task priority assignment, task period assignment and bus access configuration. We adopt a hierarchical optimization framework, where each possible task allocation and priority assignment is treated as one top-level coarse-grained state, which may contain many lower-level fine-grained states defined by different task period assignments and bus access configurations. Simulated annealing is used to explore the top-level states, which calls a geometric programming solver as a subroutine to explore the lower-level states contained within a given top-level state. Performance evaluation shows that our framework has good performance in terms of solution quality and scalability