Title: A clustering allocation and scheduling analysis approach for multiprocessor dependent real-time tasks
Authors: Faten Mrabet; Walid Karamti; Adel Mahfoudhi
Addresses: Faculty of Economics and Management, University of Sfax, Sfax, Tunisia ' Department of Computer Science, College of Computer, Qassim University, Buraydah, Qassim, Saudi Arabia; Data Engineering and Semantics Research Unit, Faculty of Sciences of Sfax, University of Sfax, Sfax, Tunisia ' College of Computers and Information Technology, Taif University, Al Hawiyah, Taif, Saudi Arabia; Data Engineering and Semantics Research Unit, Faculty of Sciences of Sfax, University of Sfax, Sfax, Tunisia
Abstract: The ultimate objective in this paper is to propose a new method for dependent tasks clustering by considering the inter-tasks communication cost, the inter-clusters communication cost (inter-calculation units), the precedence impact and the execution cost. The optimal Munkres assignment algorithm is used for an optimal total execution cost. Tasks deadlines and their imposed precedence obligations are taken into consideration to lead a fast and safe exact scheduling analysis of each partition separately while giving pertinent feedback. Experimental results highlight the effectiveness of the proposed approach by comparing it with optimal ones. The outcome shows better results in the total execution cost and gives exact scheduling analysis results.
Keywords: multiprocessor real-time systems; dependent tasks; clustering and allocation; heterogeneous multiprocessor architecture; partitioned scheduling; scheduling analysis.
International Journal of Computer Applications in Technology, 2022 Vol.70 No.1, pp.48 - 71
Received: 08 Oct 2021
Accepted: 11 Jan 2022
Published online: 03 Apr 2023 *