Mc-Adapt

Abstract

Recent embedded systems are becoming integrated systems with components of different criticality. To tackle this, mixed-criticality systems aim to provide different levels of timing assurance to components of different criticality levels while achieving efficient resource utilization. Many approaches have been proposed to execute more lower-criticality tasks without affecting the timeliness of higher-criticality tasks. Those previous approaches however have at least one of the two limitations; i) they penalize all lower-criticality tasks at once upon a certain situation, or ii) they make the decision how to penalize lower-criticality tasks at design time. As a consequence, they under-utilize resources by imposing an excessive penalty on low-criticality tasks. Unlike those existing studies, we present a novel framework, called MC-ADAPT, that aims to minimally penalize lower-criticality tasks by fully reflecting the dynamically changing system behavior into adaptive decision making. Towards this, we propose a new scheduling algorithm and develop its runtime schedulability analysis capable of capturing the dynamic system state. Our proposed algorithm adaptively determines which task to drop based on the runtime analysis. To determine the quality of task dropping solution, we propose the speedup factor for task dropping while the conventional use of the speedup factor only evaluates MC scheduling algorithms in terms of the worst-case schedulability. We apply the speedup factor for a newly-defined task dropping problem that evaluates task dropping solution under different runtime scheduling scenarios. We derive that MC-ADAPT has a speedup factor of 1.619 for task drop. This implies that MC-ADAPT can behave the same as the optimal scheduling algorithm with optimal task dropping strategy does under any runtime scenario if the system is sped up by a factor of 1.619.

Towards Fully Jitterless Applications: Periodic Scheduling in Multiprocessor MCSs Using a Table-Driven Approach

“…In event-driven schedulers, the scheduling points are defined by task completion and task arrival events. Examples of event-driven schedulers were introduced in [15][16][17][18][19]. A popular event-driven scheduling algorithm in MCSs is Earliest Deadline First with Virtual Deadlines (EDF-VD) for two criticality levels (Hi-high criticality and Lo-low criticality) [13].…”

Learning-Oriented QoS- and Drop-Aware Task Scheduling for Mixed-Criticality Systems

“…Modern embedded systems in various applications such as automotive, avionics, and medical devices, are getting more complex due to integrating many functions with different criticality levels into a common platform [1][2][3]. In these systems (called Mixed-Criticality (MC) systems), the correct execution of all tasks with higher criticality levels (HC tasks) must be guaranteed in any situation, while low-criticality tasks (LC tasks) can be penalized in emergency situations [2,4,5]. For instance, drones are an MC system, where the engine control (i.e., the function that ensures the safe execution of the operation) is an HC task, and the process of recording a video (which is its main mission) is considered as an LC task [6,7].…”

“…In addition, their policies unnecessarily drop LC tasks, which degrades their service requirements in favor of HC tasks in the H I mode. In addition, some run-time approaches improve the QoS by proposing a new scheduling policy or exploiting the dynamic slacks [4,8,12]. However, due to the lack of complete observation of the MC system's behaviour, the decision may be ineffective, and there may be no guarantee of meeting the LC tasks' service requirements.…”

Multi-core mixed-criticality real-time scheduling

“…This seriously impacts the performance which may not be suitable for many practical systems that require minimum service guarantees for these tasks [37,50]. To overcome this problem, several techniques have been proposed in the past for single-core [36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][51][52][53][54] and multi-core MC systems [55][56][57][58]. These approaches can broadly be classified as follows.…”

“…Since this is highly unlikely to occur in practice, another possible research direction is to consider task-level mode switch rather than system-level mode switch. In particular, techniques such as MC-Adapt [44] have been developed CHAPTER 7: CONCLUSIONS AND FUTURE WORK 121 that consider task-level mode switch where only a subset of HC tasks switch to the HC mode.…”