DPS: A dynamic procrastination scheduler for multi-core/multi-processor hard real time systems
Shubhangi K. Gawali, Biju K. Raveendran · 2016
Energy consumption plays an important role in designing embedded devices. In recent years, leakage energy gained significant importance in overall energy consumption. This paper addresses leakage energy at operating system level by optimizing scheduler level energy consumption. This is achieved by (i) modifying the first fit allocation algorithm (MFF) to increase shutdown duration of some processors by allocating low frequency tasks to that processors and (ii) maximizing the shutdown duration using dynamic procrastination algorithm (DPS). The procrastination is achieved by postponing the execution of upcoming jobs whenever possible by meeting all timing constraints. This helps in improving shutdown duration along with reducing decision points and static energy consumption. Shutdown decision is based on pre-computed shutdown threshold which is architecture and task set dependent. The experimental evaluation of the proposed algorithm with synthetically generated benchmark program suites shows 88.66%, 14.75% and 1% of saving in total energy consumption over no procrastination (NOPRO) with MFF task allocation, static procrastination (STATICPRO) with MFF task allocation and DPS with FF task allocation respectively.