ATLAS: Aging-Aware Task Replication for Multicore Safety-Critical Systems

• Main Authors: Ansari, Mohsen, Safari, Sepideh, Yeganeh-Khaksar, Amir, Siyadatzadeh, Roozbeh, Gohari-Nazari, Pourya, Khdr, Heba, Shafiquen, Muhammad, Henkel, Jorg, Ejlali, Alireza
• Format: Conference Proceeding
• Language: English
• Subjects: Accelerated aging; Aging; Mapping; Multicore processing; Power demand; Real-time systems; Reliability; Safety-Critical Systems; Scheduling; System-on-chip; Task Replication; Timing; Voltage
• ISSN: 2642-7346
• DOI: 10.1109/RTAS58335.2023.00025

A major requirement of safety-critical systems is high reliability at low power consumption. Dynamic voltage and frequency (v/f) scaling (DVFS) techniques are widely exploited to reduce power consumption. However, DVFS through downscaling v/f levels has a negative impact on the reliability of the tasks running on the cores, and through upscaling v/f levels has circuitlevel aging effects. To achieve high reliability in multicore safetycritical systems, task replication as a fault-tolerant technique is an established way to deal with the negative effect of downscaling v/f levels, but it may accelerate aging effects due to elevating the on-chip temperatures. In this paper, we propose an aging-aware task replication (called ATLAS) method that solves the problem of satisfying the desired reliability target for a set of periodic hard real-time tasks which are executed on a multicore system. The proposed method satisfies the reliability target of the tasks through updating the required number of replicas for each task at different years. We replicate the tasks through our proposed formulas such that the reliability target is satisfied. However, task replication increases the temperature of the system and accelerates aging. To decelerate aging, we attempt to reduce the temperature while mapping and scheduling the tasks. We have also developed a modified demand bound function (DBF) for our aging-aware task replication method to verify scheduling the realtime tasks. Compared to the existing state-of-the-art techniques, experimental results for safety-critical applications on different configurations of multicore systems demonstrate the efficiency and effectiveness of our proposed method. Experiments show that our proposed method improves schedulability on average by 16.1% and reduces the temperature on average by 7.4°C compared to state-of-the-art methods while meeting the system reliability target.