A Novel Fault Tolerant Scheduling Approach with Energy Optimization for Real-Time Embedded Systems

Abstract

In this paper, we address two critical yet conflicting aspects of real-time embedded systems: fault tolerance and energy consumption. We propose an Optimizing Energy consumption and Fault-Tolerant Scheduling Algorithm (OE FTS), designed to achieve simultaneous minimization of energy consumption and maximization of system reliability. OE FTS is based on a hybrid combination of active and passive replication and the Dynamic Voltage and Frequency Scaling (DVFS) technique. Active and passive replication are employed for tolerating multiple transient faults to improve reliability; therefore, Dynamic Voltage and Frequency Scaling (DVFS) technique is used for minimizing power consumption. We classify real-time tasks into critical and non-critical categories. Critical tasks are characterized by tight, stringent deadlines and limited execution time, while non-critical tasks have more flexible and less strict deadlines. This classification is used to decide which type of redundancy to apply and how to exploit the available slack time to lower the CPU frequency and voltage, thereby reducing energy consumption. Our technique is applied in a system designed to manage and execute several dependent tasks scheduled on a set of homogeneous processors linked by a multi-point connection. Our experimental findings confirm the effectiveness of the proposed approach which improves reliability while managing energy consumption.