Energy-cognizant scheduling for preference-oriented fixed-priority real-time tasks

Energy management is one of the crucial design issues when executing real-time applications with stringent timing requirements. Dynamic slowdown of processor voltage if accompanied with processor shutdown method, helps in better saving energy. Traditionally, energy management has been applied to real-time scheduling algorithms that prioritize tasks based on timing parameters only, however, recently applications having tasks with different execution-preferences on the same computing unit found significant importance in various areas. In this paper, dynamic voltage scaling (DVS) and dynamic power management (DPM) techniques are used for energy management while scheduling preference-oriented fixed-priority periodic real-time tasks. Preference-oriented energy-aware rate-monotonic scheduling (PER) and preference-oriented extended energy-aware rate-monotonic scheduling (PEER) algorithms are proposed that maximize energy savings while fulfilling preference-value of tasks. Extensive simulations show that PER and PEER outperforms in terms of energy savings when compared to several related studies.