Prediction-based resource allocation model for real time tasks

Qureshi, Muhammad Shuaib and Qureshi, Muhammad Bilal and Raza, Ali and Ul Qayyum, Noor and Shah, Asadullah (2018) Prediction-based resource allocation model for real time tasks. In: 2018 IEEE 5th International Conference on Engineering Technologies and Applied Sciences (ICETAS), 22nd-23rd November 2018, Bangkok, Thailand. (Unpublished)

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Abstract

High performance computing (HPC) platforms provides computing, storage and communication facilities to process real-time applications efficiently. Such applications produce less important results if the deadlines are missed. Most of the real-time algorithms decently schedule applications tasks offline, but they usually take longer in processing which results in deadlines miss when tasks need some data from remote storage locations. In this paper, we propose a prediction-based model which analyze task feasibility before scheduling on the HPC resources when tasks have data-intensive constraints. The main advantage of the prediction analysis modules is to save time by refraining further analysis on non-scheduled tasks. The model helps in searching suitable resources and improved resource utilization by considering task workload in advance.

Item Type:	Conference or Workshop Item (Invited Papers)
Additional Information:	6566/68563
Uncontrolled Keywords:	Index terms – HPC; Real-time systems; Resource allocation; Scheduling
Subjects:	T Technology > T Technology (General) > T10.5 Communication of technical information
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology
Depositing User:	Prof Asadullah Shah
Date Deposited:	04 Jan 2019 10:57
Last Modified:	13 Jun 2019 09:51
URI:	http://irep.iium.edu.my/id/eprint/68563

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