
Fault-Tolerant Energy-Aware Task Scheduling on Multiprocessor System for Fixed-Priority Real-Time Tasks
Author(s) -
Kiran Arora,
Sandeep Bansal,
Rakesh Kumar Bansal
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.a5177.119119
Subject(s) - computer science , multiprocessing , fault tolerance , backup , earliest deadline first scheduling , scheduling (production processes) , workload , distributed computing , parallel computing , fixed priority pre emptive scheduling , dynamic priority scheduling , multiprocessor scheduling , efficient energy use , rate monotonic scheduling , real time computing , embedded system , schedule , operating system , engineering , operations management , electrical engineering
Energy-aware real-time scheduling is gaining attention in recent years owing to environmental concerns and applications in numerous fields. System reliability also gets affected adversely with increasing energy dissipations posing serious challenges before the researchers. Keeping these in view, in recent times researchers have diverted to combining issues of fault-tolerance and energy efficiency. In literature, DVFS and DPM, most commonly used techniques for power management in task scheduling, are often combined with Primary/Backup technique to achieve fault tolerance against transient and permanent faults. Optimal algorithms, Earliest deadline first (EDF) and Rate-Monotonic (RM), meant for scheduling dynamic and fixed priority tasks respectively, have mainly been analyzed using a dual-processor approach for fault-tolerance and energy efficiency. In this paper, to handle higher workload of fixed-priority real-time tasks, energy-aware fault-tolerant scheduling algorithms are proposed for multiprocessor systems with balanced and unbalanced number of main and auxiliary processors. Simulations over extensive task-sets indicate that balanced approach is more energy-efficient than the unbalanced one.