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This work was supported by Grant PID2021-124502OB-C41 funded by MCIN/AEI/10.13039/501100011033 and, by "ERDF A way of making Europe", by the "European Union". This work was also supported by PAID-10-20 (UPV). There was no additional external funding received for this study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Allocation algorithms for multicore partitioned mixed-criticality real-time systems

Publicated to:Peerj Computer Science. 10 e2609-e2609 - 2024-12-20 10(), DOI: 10.7717/peerj-cs.2609

Authors: Ortiz, Luis; Guasque, Ana; Balbastre, Patricia; Simo, Jose

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Abstract

Multicore systems introduced a performance increase over previous monocore systems. As these systems are increasingly finding application in critical domains, it arises a necessity to develop novel methodologies for their efficient resource allocation. In addition, it is particularly important to consider the criticality of applications when scheduling such systems. In multicore systems, scheduling also includes the allocation of tasks to cores. In architectures based on spatial and temporal partitioning, it is also necessary to allocate partitions. Consideration of all these variables when scheduling a critical multicore partitioned system is a major challenge. In this article, a hypervisor partitioned framework for mixed-criticality systems is proposed. In this sense, the allocation process has been split in two different parts. The initial phase will allocate tasks to partitions according to the criticality of the system. This is achieved through the implementation of a Mixed- Integer Linear Programming (MILP) algorithm. The second phase involves the allocation of tasks to cores, employing both, an additional MILP algorithm and a modified worst fit decrease utilisation approach. Experimental results show that the combination of both strategies leads to feasible scheduling and, in addition, to a reduction of the overhead introduced by the hypervisor.

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