Priority assignment on partitioned multiprocessor systems with shared resources

Driven by industry demand, there is an increasing need to develop real-time multiprocessor systems which contain shared resources. The Multiprocessor Stack Resource Policy (MSRP) and Multiprocessor resource sharing Protocol (MrsP) are two major protocols that manage access to shared resources. Both...

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Main Authors: Zhao, Shuai, Chang, Wanli, Wei, Ran, Liu, Weichen, Guan, Nan, Burns, Alan, Wellings, Andy
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/159498
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1594982022-06-24T01:22:22Z Priority assignment on partitioned multiprocessor systems with shared resources Zhao, Shuai Chang, Wanli Wei, Ran Liu, Weichen Guan, Nan Burns, Alan Wellings, Andy School of Computer Science and Engineering Engineering::Computer science and engineering Priority Assignment Resource Sharing Driven by industry demand, there is an increasing need to develop real-time multiprocessor systems which contain shared resources. The Multiprocessor Stack Resource Policy (MSRP) and Multiprocessor resource sharing Protocol (MrsP) are two major protocols that manage access to shared resources. Both of them can be applied to Fixed-Priority Preemptive Scheduling (FPPS), which is enforced by most commercial real-time systems regulations, and which requires task priorities to be assigned before deployment. Along with MSRP and MrsP, there exist two forms of schedulability tests that bound the worst-case blocking time due to resource accesses: the traditional ones being more widely adopted and the more recently developed holistic ones which deliver tighter analysis. On uniprocessor systems, there are several well-established optimal priority assignment algorithms. Unfortunately, on multiprocessor systems with shared resources, the issue of priority assignment has not been adequately understood. In this article, we investigate three mainstream priority assignment algorithms-Deadline Monotonic Priority Ordering (DMPO), Audsley's Optimal Priority Assignment (OPA), and Robust Priority Assignment (RPA), in the context of partitioned multiprocessor systems with shared resources. Our contributions are multifold: First, we prove that DMPO is optimal with the traditional schedulability tests. Second, two counter examples are given as evidence that DMPO is not optimal with the tighter holistic schedulability tests. Third, we then analyze the pessimism arising from the adoption of OPA and RPA with the holistic tests. Lastly, we propose a Slack-based Priority Ordering (SPO) algorithm that minimises such pessimism, and has polynomial time complexity. Comprehensive experiments show that SPO outperforms (i.e., results in a larger number of schedulable systems) DMPO, OPA, and RPA in general with the holistic schedulability tests, by up to 15 percent. With the theoretical contributions, this paper is a useful guide to priority assignment in real-time partitioned multiprocessor systems with shared resources. 2022-06-24T01:22:22Z 2022-06-24T01:22:22Z 2020 Journal Article Zhao, S., Chang, W., Wei, R., Liu, W., Guan, N., Burns, A. & Wellings, A. (2020). Priority assignment on partitioned multiprocessor systems with shared resources. IEEE Transactions On Computers, 70(7), 1006-1018. https://dx.doi.org/10.1109/TC.2020.3000051 0018-9340 https://hdl.handle.net/10356/159498 10.1109/TC.2020.3000051 2-s2.0-85086741686 7 70 1006 1018 en IEEE Transactions on Computers © 2020 IEEE. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering
Priority Assignment
Resource Sharing
spellingShingle Engineering::Computer science and engineering
Priority Assignment
Resource Sharing
Zhao, Shuai
Chang, Wanli
Wei, Ran
Liu, Weichen
Guan, Nan
Burns, Alan
Wellings, Andy
Priority assignment on partitioned multiprocessor systems with shared resources
description Driven by industry demand, there is an increasing need to develop real-time multiprocessor systems which contain shared resources. The Multiprocessor Stack Resource Policy (MSRP) and Multiprocessor resource sharing Protocol (MrsP) are two major protocols that manage access to shared resources. Both of them can be applied to Fixed-Priority Preemptive Scheduling (FPPS), which is enforced by most commercial real-time systems regulations, and which requires task priorities to be assigned before deployment. Along with MSRP and MrsP, there exist two forms of schedulability tests that bound the worst-case blocking time due to resource accesses: the traditional ones being more widely adopted and the more recently developed holistic ones which deliver tighter analysis. On uniprocessor systems, there are several well-established optimal priority assignment algorithms. Unfortunately, on multiprocessor systems with shared resources, the issue of priority assignment has not been adequately understood. In this article, we investigate three mainstream priority assignment algorithms-Deadline Monotonic Priority Ordering (DMPO), Audsley's Optimal Priority Assignment (OPA), and Robust Priority Assignment (RPA), in the context of partitioned multiprocessor systems with shared resources. Our contributions are multifold: First, we prove that DMPO is optimal with the traditional schedulability tests. Second, two counter examples are given as evidence that DMPO is not optimal with the tighter holistic schedulability tests. Third, we then analyze the pessimism arising from the adoption of OPA and RPA with the holistic tests. Lastly, we propose a Slack-based Priority Ordering (SPO) algorithm that minimises such pessimism, and has polynomial time complexity. Comprehensive experiments show that SPO outperforms (i.e., results in a larger number of schedulable systems) DMPO, OPA, and RPA in general with the holistic schedulability tests, by up to 15 percent. With the theoretical contributions, this paper is a useful guide to priority assignment in real-time partitioned multiprocessor systems with shared resources.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Zhao, Shuai
Chang, Wanli
Wei, Ran
Liu, Weichen
Guan, Nan
Burns, Alan
Wellings, Andy
format Article
author Zhao, Shuai
Chang, Wanli
Wei, Ran
Liu, Weichen
Guan, Nan
Burns, Alan
Wellings, Andy
author_sort Zhao, Shuai
title Priority assignment on partitioned multiprocessor systems with shared resources
title_short Priority assignment on partitioned multiprocessor systems with shared resources
title_full Priority assignment on partitioned multiprocessor systems with shared resources
title_fullStr Priority assignment on partitioned multiprocessor systems with shared resources
title_full_unstemmed Priority assignment on partitioned multiprocessor systems with shared resources
title_sort priority assignment on partitioned multiprocessor systems with shared resources
publishDate 2022
url https://hdl.handle.net/10356/159498
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