Semi-Partitioned Scheduling of Dynamic Real-Time Workload: A Practical Approach Based on Analysis-Driven Load Balancing

Recent work showed that semi-partitioned scheduling can achieve near-optimal schedulability performance, is simpler to implement compared to global scheduling, and less heavier in terms of runtime overhead, thus resulting in an excellent choice for implementing real-world systems. However, semi-partitioned scheduling typically leverages an off-line design to allocate tasks across the available processors, which requires a-priori knowledge of the workload. Conversely, several simple global schedulers, as global earliest-deadline first (G-EDF), can transparently support dynamic workload without requiring a task-allocation phase. Nonetheless, such schedulers exhibit poor worst-case performance. This work proposes a semi-partitioned approach to efficiently schedule dynamic real-time workload on a multiprocessor system. A linear-time approximation for the C=D splitting scheme under partitioned EDF scheduling is first presented to reduce the complexity of online scheduling decisions. Then, a load-balancing algorithm is proposed for admitting new real-time workload in the system with limited workload re-allocation. A large-scale experimental study shows that the linear-time approximation has a very limited utilization loss compared to the exact technique and the proposed approach achieves very high schedulability performance, with a consistent improvement on G-EDF and pure partitioned EDF scheduling

Semi-Partitioned Scheduling of Dynamic Real-Time Workload: A Practical Approach Based on Analysis-Driven Load Balancing

Recent work showed that semi-partitioned scheduling can achieve near-optimal schedulability performance, is simpler to implement compared to global scheduling, and less heavier in terms of runtime overhead, thus resulting in an excellent choice for implementing real-world systems. However, semi-partitioned scheduling typically leverages an off-line design to allocate tasks across the available processors, which requires a-priori knowledge of the workload. Conversely, several simple global schedulers, as global earliest-deadline first (G-EDF), can transparently support dynamic workload without requiring a task-allocation phase. Nonetheless, such schedulers exhibit poor worst-case performance. This work proposes a semi-partitioned approach to efficiently schedule dynamic real-time workload on a multiprocessor system. A linear-time approximation for the C=D splitting scheme under partitioned EDF scheduling is first presented to reduce the complexity of online scheduling decisions. Then, a load-balancing algorithm is proposed for admitting new real-time workload in the system with limited workload re-allocation. A large-scale experimental study shows that the linear-time approximation has a very limited utilization loss compared to the exact technique and the proposed approach achieves very high schedulability performance, with a consistent improvement on G-EDF and pure partitioned EDF scheduling

Efficient schedulability tests for real-time embedded systems with urgent routines

Task scheduling is one of the key mechanisms to ensure timeliness in embedded real-time systems. Such systems have often the need to execute not only application tasks but also some urgent routines (e.g. error-detection actions, consistency checkers, interrupt handlers) with minimum latency. Although fixed-priority schedulers such as Rate-Monotonic (RM) are in line with this need, they usually make a low processor utilization available to the system. Moreover, this availability usually decreases with the number of considered tasks. If dynamic-priority schedulers such as Earliest Deadline First (EDF) are applied instead, high system utilization can be guaranteed but the minimum latency for executing urgent routines may not be ensured. In this paper we describe a scheduling model according to which urgent routines are executed at the highest priority level and all other system tasks are scheduled by EDF. We show that the guaranteed processor utilization for the assumed scheduling model is at least as high as the one provided by RM for two tasks, namely 2(2√−1). Seven polynomial time tests for checking the system timeliness are derived and proved correct. The proposed tests are compared against each other and to an exact but exponential running time test

On the effectiveness of cache partitioning in hard real-time systems

In hard real-time systems, cache partitioning is often suggested as a means of increasing the predictability of caches in pre-emptively scheduled systems: when a task is assigned its own cache partition, inter-task cache eviction is avoided, and timing verification is reduced to the standard worst-case execution time analysis used in non-pre-emptive systems. The downside of cache partitioning is the potential increase in execution times. In this paper, we evaluate cache partitioning for hard real-time systems in terms of overall schedulability. To this end, we examine the sensitivity of (i) task execution times and (ii) pre-emption costs to the size of the cache partition allocated and present a cache partitioning algorithm that is optimal with respect to taskset schedulability. We also devise an alternative algorithm which primarily optimises schedulability but also minimises processor utilization. We evaluate the performance of cache partitioning compared to state-of-the-art pre-emption cost analysis based on benchmark code and on a large number of synthetic tasksets with both fixed priority and EDF scheduling. This allows us to derive general conclusions about the usability of cache partitioning and identify taskset and system parameters that influence the relative effectiveness of cache partitioning. We also examine the improvement in processor utilization obtained using an alternative cache partitioning algorithm, and the tradeoff in terms of increased analysis time

Cutting-plane algorithms for preemptive uniprocessor real-time scheduling problems

Fixed-point iteration algorithms like RTA (response time analysis) and QPA (quick processor-demand analysis) are arguably the most popular ways of solving schedulability problems for preemptive uniprocessor FP (fixed-priority) and EDF (earliest-deadline-first) systems. Several IP (integer program) formulations have also been proposed for these problems, but it is unclear whether the algorithms for solving these formulations are related to RTA and QPA. By discovering connections between the problems and the algorithms, we show that RTA and QPA are, in fact, suboptimal cutting-plane algorithms for specific IP formulations of FP and EDF schedulability, where optimality is defined with respect to convergence rate. We propose optimal cutting-plane algorithms for these IP formulations. We compare the new algorithms with RTA and QPA on large collections of synthetic systems to gauge the improvement in convergence rates and running times.Comment: 45 pages, 5 figures. Changes in v2: new terms like CP-KERN are added to explain ideas more clearly; models include release jitter. Changes in v3: typos are fixed; evaluation section is modified so that it is in sync with public code. Changes in v4: algorithm, theoretical and empirical analyses are improved. Changes in v5: minor structural changes, acknowledgements adde

Real-time operating system support for multicore applications

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Automação e Sistemas, Florianópolis, 2014Plataformas multiprocessadas atuais possuem diversos níveis da memória cache entre o processador e a memória principal para esconder a latência da hierarquia de memória. O principal objetivo da hierarquia de memória é melhorar o tempo médio de execução, ao custo da previsibilidade. O uso não controlado da hierarquia da cache pelas tarefas de tempo real impacta a estimativa dos seus piores tempos de execução, especialmente quando as tarefas de tempo real acessam os níveis da cache compartilhados. Tal acesso causa uma disputa pelas linhas da cache compartilhadas e aumenta o tempo de execução das aplicações. Além disso, essa disputa na cache compartilhada pode causar a perda de prazos, o que é intolerável em sistemas de tempo real críticos. O particionamento da memória cache compartilhada é uma técnica bastante utilizada em sistemas de tempo real multiprocessados para isolar as tarefas e melhorar a previsibilidade do sistema. Atualmente, os estudos que avaliam o particionamento da memória cache em multiprocessadores carecem de dois pontos fundamentais. Primeiro, o mecanismo de particionamento da cache é tipicamente implementado em um ambiente simulado ou em um sistema operacional de propósito geral. Consequentemente, o impacto das atividades realizados pelo núcleo do sistema operacional, tais como o tratamento de interrupções e troca de contexto, no particionamento das tarefas tende a ser negligenciado. Segundo, a avaliação é restrita a um escalonador global ou particionado, e assim não comparando o desempenho do particionamento da cache em diferentes estratégias de escalonamento. Ademais, trabalhos recentes confirmaram que aspectos da implementação do SO, tal como a estrutura de dados usada no escalonamento e os mecanismos de tratamento de interrupções, impactam a escalonabilidade das tarefas de tempo real tanto quanto os aspectos teóricos. Entretanto, tais estudos também usaram sistemas operacionais de propósito geral com extensões de tempo real, que afetamos sobre custos de tempo de execução observados e a escalonabilidade das tarefas de tempo real. Adicionalmente, os algoritmos de escalonamento tempo real para multiprocessadores atuais não consideram cenários onde tarefas de tempo real acessam as mesmas linhas da cache, o que dificulta a estimativa do pior tempo de execução. Esta pesquisa aborda os problemas supracitados com as estratégias de particionamento da cache e com os algoritmos de escalonamento tempo real multiprocessados da seguinte forma. Primeiro, uma infraestrutura de tempo real para multiprocessadores é projetada e implementada em um sistema operacional embarcado. A infraestrutura consiste em diversos algoritmos de escalonamento tempo real, tais como o EDF global e particionado, e um mecanismo de particionamento da cache usando a técnica de coloração de páginas. Segundo, é apresentada uma comparação em termos da taxa de escalonabilidade considerando o sobre custo de tempo de execução da infraestrutura criada e de um sistema operacional de propósito geral com extensões de tempo real. Em alguns casos, o EDF global considerando o sobre custo do sistema operacional embarcado possui uma melhor taxa de escalonabilidade do que o EDF particionado com o sobre custo do sistema operacional de propósito geral, mostrando claramente como diferentes sistemas operacionais influenciam os escalonadores de tempo real críticos em multiprocessadores. Terceiro, é realizada uma avaliação do impacto do particionamento da memória cache em diversos escalonadores de tempo real multiprocessados. Os resultados desta avaliação indicam que um sistema operacional "leve" não compromete as garantias de tempo real e que o particionamento da cache tem diferentes comportamentos dependendo do escalonador e do tamanho do conjunto de trabalho das tarefas. Quarto, é proposto um algoritmo de particionamento de tarefas que atribui as tarefas que compartilham partições ao mesmo processador. Os resultados mostram que essa técnica de particionamento de tarefas reduz a disputa pelas linhas da cache compartilhadas e provê garantias de tempo real para sistemas críticos. Finalmente, é proposto um escalonador de tempo real de duas fases para multiprocessadores. O escalonador usa informações coletadas durante o tempo de execução das tarefas através dos contadores de desempenho em hardware. Com base nos valores dos contadores, o escalonador detecta quando tarefas de melhor esforço o interferem com tarefas de tempo real na cache. Assim é possível impedir que tarefas de melhor esforço acessem as mesmas linhas da cache que tarefas de tempo real. O resultado desta estratégia de escalonamento é o atendimento dos prazos críticos e não críticos das tarefas de tempo real.Abstracts: Modern multicore platforms feature multiple levels of cache memory placed between the processor and main memory to hide the latency of ordinary memory systems. The primary goal of this cache hierarchy is to improve average execution time (at the cost of predictability). The uncontrolled use of the cache hierarchy by realtime tasks may impact the estimation of their worst-case execution times (WCET), specially when real-time tasks access a shared cache level, causing a contention for shared cache lines and increasing the application execution time. This contention in the shared cache may leadto deadline losses, which is intolerable particularly for hard real-time (HRT) systems. Shared cache partitioning is a well-known technique used in multicore real-time systems to isolate task workloads and to improve system predictability. Presently, the state-of-the-art studies that evaluate shared cache partitioning on multicore processors lack two key issues. First, the cache partitioning mechanism is typically implemented either in a simulated environment or in a general-purpose OS (GPOS), and so the impact of kernel activities, such as interrupt handlers and context switching, on the task partitions tend to be overlooked. Second, the evaluation is typically restricted to either a global or partitioned scheduler, thereby by falling to compare the performance of cache partitioning when tasks are scheduled by different schedulers. Furthermore, recent works have confirmed that OS implementation aspects, such as the choice of scheduling data structures and interrupt handling mechanisms, impact real-time schedulability as much as scheduling theoretic aspects. However, these studies also used real-time patches applied into GPOSes, which affects the run-time overhead observed in these works and consequently the schedulability of real-time tasks. Additionally, current multicore scheduling algorithms do not consider scenarios where real-time tasks access the same cache lines due to true or false sharing, which also impacts the WCET. This thesis addresses these aforementioned problems with cache partitioning techniques and multicore real-time scheduling algorithms as following. First, a real-time multicore support is designed and implemented on top of an embedded operating system designed from scratch. This support consists of several multicore real-time scheduling algorithms, such as global and partitioned EDF, and a cache partitioning mechanism based on page coloring. Second, it is presented a comparison in terms of schedulability ratio considering the run-time overhead of the implemented RTOS and a GPOS patched with real-time extensions. In some cases, Global-EDF considering the overhead of the RTOS is superior to Partitioned-EDF considering the overhead of the patched GPOS, which clearly shows how different OSs impact hard realtime schedulers. Third, an evaluation of the cache partitioning impacton partitioned, clustered, and global real-time schedulers is performed.The results indicate that a lightweight RTOS does not impact real-time tasks, and shared cache partitioning has different behavior depending on the scheduler and the task's working set size. Fourth, a task partitioning algorithm that assigns tasks to cores respecting their usage of cache partitions is proposed. The results show that by simply assigning tasks that shared cache partitions to the same processor, it is possible to reduce the contention for shared cache lines and to provideHRT guarantees. Finally, a two-phase multicore scheduler that provides HRT and soft real-time (SRT) guarantees is proposed. It is shown that by using information from hardware performance counters at run-time, the RTOS can detect when best-effort tasks interfere with real-time tasks in the shared cache. Then, the RTOS can prevent best effort tasks from interfering with real-time tasks. The results also show that the assignment of exclusive partitions to HRT tasks together with the two-phase multicore scheduler provides HRT and SRT guarantees, even when best-effort tasks share partitions with real-time tasks

A Practical Comparison of Scheduling Algorithms for Mixed Criticality Embedded Systems

With the consolidation of automotive control processes onto single highperformance ECUs the issue of running, and thus scheduling, processes of varying criticality on a single CPU has moved to the fore. This has resulted in a number of new algorithms for scheduling such systems, for example Adaptive Mixed Criticality (AMC). This project attempts to measure the performance of some of these algorithms on a singlecore embedded system CPU and compares them in order to shed some light on their different advantages and disadvantages

Cluster Based Real Time Scheduling for Distributed System

Real time tasks scheduling on a distributed system is a complex problem. The existing real time tasks scheduling techniques are primarily based on partitioned and global scheduling. In partitioned based scheduling the tasks are assigned on a dedicated processor. The advantages of partitioned based approach is existing uni-processor scheduling techniques can be used; no migration overheads but task assignment is NP hard problem and optimal utilization of processing nodes is not possible. In global scheduling all tasks are maintained in a single tasks queue and allocated to multiple processing nodes. The advantage of global scheduling is optimal utilization of processing nodes but suffer from high migration and preemption overheads. This paper proposed cluster based real time tasks scheduling on a distributed system which is a hybrid scheduling approach where processing nodes group into cluster and scheduling using global scheduling. The simulation result shows that the proposed scheduling increases the tasks acceptance ratio, resource utilization as compared to partitioned and global scheduling and reduces migration as well as preemption overheads

On-line schedulability tests for adaptive reservations in fixed priority scheduling

Adaptive reservation is a real-time scheduling technique in which each application is associated a fraction of the computational resource (a reservation) that can be dynamically adapted to the varying requirements of the application by using appropriate feedback control algorithms. An adaptive reservation is typically implemented by using an aperiodic server (e.g. sporadic server) algorithm with fixed period and variable budget. When the feedback law demands an increase of the reservation budget, the system must run a schedulability test to check if there is enough spare bandwidth to accommodate such increase. The schedulability test must be very fast, as it may be performed at each budget update, i.e. potentially at each instance of a task; yet, it must be as efficient as possible, to maximize resource usage. In this paper, we tackle the problem of performing an efficient on-line schedulability test for adaptive resource reservations in fixed priority schedulers. In the literature, a number of algorithms have been proposed for on-line admission control in fixed priority systems. We describe four of these tests, with increasing complexity and performance. In addition, we propose a novel on-line test, called Spare-Pot al- gorithm, which has been specifically designed for the problem at hand, and which shows a good cost/performance ratio compared to the other tests