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2014 Article

Giulio M. Mancuso Scuola Superiore Sant'Anna, Pisa, Italy Enrico Bini Lund University, Lund, Sweden Gabriele Pannocchia University of Pisa, Italy

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Published in: · Journal ACM Transactions on Embedded Computing Systems (TECS) - Special Issue on Risk and Trust in Embedded Critical Systems, Special Issue on Real-Time, Embedded and Cyber-Physical Systems, Special Issue on Virtual Prototyping of Parallel and Embedded Systems (ViPES) TECS Homepage archive Volume 13 Issue 5s, November 2014 Article No. 161 ACM New York, NY, USA table of contents doi> 10.1145/2660496

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Table of Contents

In embedded real-time systems, task priorities are often assigned to meet deadlines. However, in control tasks, a late completion of a task has no catastrophic consequence; rather, it has a quantifiable impact in the control performance achieved by the task. In this article, we address the problem of determining the optimal assignment of priorities and periods of sampled-data control tasks that run over a shared computation unit. We show that the minimization of the overall cost can be performed efficiently using a branch and bound algorithm that can be further speeded up by allowing for a small degree of suboptimality. Detailed numerical simulations are presented to show the advantages of various branching alternatives, the overall algorithm effectiveness, and its scalability with the number of tasks.

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