Optimizing the resource requirements of hierarchical scheduling systems

Author:

Kim Jin Hyun1,Legay Axel1,Traonouez Louis-Marie1,Boudjadar Abdeldjalil2,Nyman Ulrik3,Larsen Kim G.3,Lee Insup4,Choi Jin-Young5

Affiliation:

1. INRIA/IRISA, France

2. Linköping University, Sweden

3. Aalborg University, Denmark

4. University of Pennsylvania

5. Korea University, S. Korea

Abstract

Compositional reasoning on hierarchical scheduling systems is a well-founded formal method that can construct schedulable and optimal system configurations in a compositional way. However, a compositional framework formulates the resource requirement of a component, called an interface, by assuming that a resource is always supplied by the parent components in the most pessimistic way. For this reason, the component interface demands more resources than the amount of resources that are really sufficient to satisfy sub-components. We provide two new supply bound functions which provides tighter bounds on the resource requirements of individual components. The tighter bounds are calculated by using more information about the scheduling system. We evaluate our new tighter bounds by using a model-based schedulability framework for hierarchical scheduling systems realized as Uppaal models. The timed models are checked using model checking tools Uppaal and Uppaal SMC, and we compare our results with the state of the art tool CARTS.

Publisher

Association for Computing Machinery (ACM)

Subject

Engineering (miscellaneous),Computer Science (miscellaneous)

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Model-based optimization of ARINC-653 partition scheduling;International Journal on Software Tools for Technology Transfer;2021-02-07

2. A Model-Based Approach to Optimizing Partition Scheduling of Integrated Modular Avionics Systems;Electronics;2020-08-09

3. High-level frameworks for the specification and verification of scheduling problems;International Journal on Software Tools for Technology Transfer;2017-09-04

4. Information Leakage as a Scheduling Resource;Lecture Notes in Computer Science;2017

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