Enhanced Preemptive Global Utility Accrual Real Time Scheduling Algorithms in Multicore Environment
Idawaty Ahmad, Mohamed Othman and Zuriati Ahmad Zulkarnain
DOI : 10.3844/jcssp.2015.1099.1107
Journal of Computer Science
Volume 11, Issue 12
This paper proposed an efficient real time scheduling algorithm using global scheduling paradigm running in multicore environment known as Global Preemptive Utility Accrual Scheduling (GPUAS) algorithm. The existing TUF/UA multiprocessor scheduling algorithms known as Greedy-Global Utility Accrual (G-GUA) and Non Greedy-Global Utility Accrual (NG-GUA) algorithms is seen to overlook the efficiency on its task scheduling algorithm. These algorithms have adapted the task migration attribute considering the load balancing problem in multi core platform. The existing PUAS uniprocessor scheduling algorithm is mapped into the multicore scheduling environment that consists of the global scheduling schemes considering the migration attribute of the executed tasks. The main principal of global scheduling is that it allows the executed tasks to migrate from one processor to the other processors whenever a scheduling event occurs in the system. The proposed GPUAS algorithm inherits the characteristics of PUAS in uniprocessor where it can preempt the highest PUD task at any event that occurs in the system. In this research, the proposed GPUAS algorithm enhanced the existing NG-GUA and G-GUA algorithms. The developed simulator has derived the set of parameter, events and performance metrics according to a detailed analysis of the base model. The proposed GPUAS algorithm achieved the highest accrued utility for the entire load range. The proposed GPUAS algorithm is more efficient than the existing algorithms, producing the highest accrued utility ratio and less abortion ratio making it more suitable and efficient for real time application domain.
© 2015 Idawaty Ahmad, Mohamed Othman and Zuriati Ahmad Zulkarnain. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.