MORA: an Energy-Aware Slack Reclamation Scheme for Scheduling Sporadic Real-Time Tasks upon Multiprocessor Platforms

In this paper, we address the global and preemptive energy-aware scheduling problem of sporadic constrained-deadline tasks on DVFS-identical multiprocessor platforms. We propose an online slack reclamation scheme which profits from the discrepancy between the worst- and actual-case execution time of the tasks by slowing down the speed of the processors in order to save energy. Our algorithm called MORA takes into account the application-specific consumption profile of the tasks. We demonstrate that MORA does not jeopardize the system schedulability and we show by performing simulations that it can save up to 32% of energy (in average) compared to execution without using any energy-aware algorithm.Comment: 11 page

Federated Scheduling for Stochastic Parallel Real-time Tasks

Federated scheduling is a strategy to schedule parallel real-time tasks: It allocates a dedicated cluster of cores to high-utilization task (utilization \u3e1); It uses a multiprocessor scheduling algorithm to schedule and execute all low-utilization tasks sequentially, on a shared cluster of the remaining cores. Prior work has shown that federated scheduling has the best known capacity augmentation bound of 2 for parallel tasks with implicit deadlines. In this paper, we explore the soft real-time performance of federated scheduling and address the average-case workloads instead of the worst-case values. In particular, we consider stochastic tasks -- tasks for which execution time and critical-path length are random variables. In this case, we use bounded expected tardiness as the schedulability criterion. We define a stochastic capacity augmentation bound and prove that federated scheduling algorithms guarantee the same bound of 2 for stochastic tasks. We present three federated mapping algorithms for core allocation. All of them guarantee bounded expected tardiness and provide the same capacity augmentation bound; In practice, however, we expect them to provide different performances, both in terms of the task sets they can schedule and the actual tardiness they guarantee. Therefore, we performed numerical evaluations using randomly generated task sets to understand the practical differences between the three algorithms

Scheduling Techniques for Operating Systems for Medical and IoT Devices: A Review

Software and Hardware synthesis are the major subtasks in the implementation of hardware/software systems. Increasing trend is to build SoCs/NoC/Embedded System for Implantable Medical Devices (IMD) and Internet of Things (IoT) devices, which includes multiple Microprocessors and Signal Processors, allowing designing complex hardware and software systems, yet flexible with respect to the delivered performance and executed application. An important technique, which affect the macroscopic system implementation characteristics is the scheduling of hardware operations, program instructions and software processes. This paper presents a survey of the various scheduling strategies in process scheduling. Process Scheduling has to take into account the real-time constraints. Processes are characterized by their timing constraints, periodicity, precedence and data dependency, pre-emptivity, priority etc. The affect of these characteristics on scheduling decisions has been described in this paper

Mixed-criticality real-time task scheduling with graceful degradation

”The mixed-criticality real-time systems implement functionalities of different degrees of importance (or criticalities) upon a shared platform. In traditional mixed-criticality systems, under a hi mode switch, no guaranteed service is provided to lo-criticality tasks. After a mode switch, only hi-criticality tasks are considered for execution while no guarantee is made to the lo-criticality tasks. However, with careful optimistic design, a certain degree of service guarantee can be provided to lo-criticality tasks upon a mode switch. This concept is broadly known as graceful degradation. Guaranteed graceful degradation provides a better quality of service as well as it utilizes the system resource more efficiently. In this thesis, we study two efficient techniques of graceful degradation. First, we study a mixed-criticality scheduling technique where graceful degradation is provided in the form of minimum cumulative completion rates. We present two easy-to-implement admission-control algorithms to determine which lo-criticality jobs to complete in hi mode. The scheduling is done by following deadline virtualization, and two heuristics are shown for virtual deadline settings. We further study the schedulability analysis and the backward mode switch conditions, which are proposed and proved in (Guo et al., 2018). Next, we present a probabilistic scheduling technique for mixed-criticality tasks on multiprocessor systems where a system-wide permitted failure probability is known. The schedulability conditions are derived along with the processor allocation scheme. The work is extended from (Guo et al., 2015), where the probabilistic model is first introduced for independent task scheduling on a uniprocessor platform. We further consider the failure dependency between tasks while scheduling on multiprocessor platforms. We provide related theoretical analysis to show the correctness of our work. To show the effectiveness of our proposed techniques, we conduct a detailed experimental evaluation under different circumstances”--Abstract, page iii

Parallel Real-Time Scheduling for Latency-Critical Applications

In order to provide safety guarantees or quality of service guarantees, many of today\u27s systems consist of latency-critical applications, e.g. applications with timing constraints. The problem of scheduling multiple latency-critical jobs on a multiprocessor or multicore machine has been extensively studied for sequential (non-parallizable) jobs and different system models and different objectives have been considered. However, the computational requirement of a single job is still limited by the capacity of a single core. To provide increasingly complex functionalities of applications and to complete their higher computational demands within the same or even more stringent timing constraints, we must exploit the internal parallelism of jobs, where individual jobs are parallel programs and can potentially utilize more than one core in parallel. However, there is little work considering scheduling multiple parallel jobs that are latency-critical. This dissertation focuses on developing new scheduling strategies, analysis tools, and practical platform design techniques to enable efficient and scalable parallel real-time scheduling for latency-critical applications on multicore systems. In particular, the research is focused on two types of systems: (1) static real-time systems for tasks with deadlines where the temporal properties of the tasks that need to execute is known a priori and the goal is to guarantee the temporal correctness of the tasks prior to their executions; and (2) online systems for latency-critical jobs where multiple jobs arrive over time and the goal to optimize for a performance objective of jobs during the execution. For static real-time systems for parallel tasks, several scheduling strategies, including global earliest deadline first, global rate monotonic and a novel federated scheduling, are proposed, analyzed and implemented. These scheduling strategies have the best known theoretical performance for parallel real-time tasks under any global strategy, any fixed priority scheduling and any scheduling strategy, respectively. In addition, federated scheduling is generalized to systems with multiple criticality levels and systems with stochastic tasks. Both numerical and empirical experiments show that federated scheduling and its variations have good schedulability performance and are efficient in practice. For online systems with multiple latency-critical jobs, different online scheduling strategies are proposed and analyzed for different objectives, including maximizing the number of jobs meeting a target latency, maximizing the profit of jobs, minimizing the maximum latency and minimizing the average latency. For example, a simple First-In-First-Out scheduler is proven to be scalable for minimizing the maximum latency. Based on this theoretical intuition, a more practical work-stealing scheduler is developed, analyzed and implemented. Empirical evaluations indicate that, on both real world and synthetic workloads, this work-stealing implementation performs almost as well as an optimal scheduler

08071 Abstracts Collection -- Scheduling

From 10.02. to 15.02., the Dagstuhl Seminar 08071 ``Scheduling\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

A Survey of Research into Mixed Criticality Systems

This survey covers research into mixed criticality systems that has been published since Vestal’s seminal paper in 2007, up until the end of 2016. The survey is organised along the lines of the major research areas within this topic. These include single processor analysis (including fixed priority and EDF scheduling, shared resources and static and synchronous scheduling), multiprocessor analysis, realistic models, and systems issues. The survey also explores the relationship between research into mixed criticality systems and other topics such as hard and soft time constraints, fault tolerant scheduling, hierarchical scheduling, cyber physical systems, probabilistic real-time systems, and industrial safety standards