Energy efficient backup overloading schemes for fault tolerant scheduling of real-time tasks

Efficient energy management and fault tolerance are two key issues that demand judicious handling while scheduling real-time task-sets. Standby-sparing technique is available in literature for fault tolerance, while dynamic power management (DPM) and dynamic voltage scaling (DVS) schemes are exploited for energy management. However, usage of auxiliary processor for running backup jobs leads to increased energy consumption making fault tolerant scheduling energy inefficient. In the current work, overloading of backup jobs in overlapping time intervals is proposed, implemented and investigated for reducing energy consumption on auxiliary processor for scheduling real-time periodic tasks. Two energy efficient fault tolerant scheduling algorithms FEED-O and FEED-OD are proposed and extensive performance analysis through simulations is carried out indicating their usefulness especially at higher task-set utilization in comparison to other state-of-the-art algorithms.

Automated summary

Efficient energy management and fault tolerance are crucial in scheduling real-time task-sets. This study proposes two energy-efficient fault-tolerant scheduling algorithms, FEED-O and FEED-OD, which outperform other state-of-the-art algorithms, especially at high task-set utilization. By overloading backup jobs in overlapping time intervals, energy consumption on auxiliary processors can be reduced.