4,451 research outputs found
Securing Real-Time Internet-of-Things
Modern embedded and cyber-physical systems are ubiquitous. A large number of
critical cyber-physical systems have real-time requirements (e.g., avionics,
automobiles, power grids, manufacturing systems, industrial control systems,
etc.). Recent developments and new functionality requires real-time embedded
devices to be connected to the Internet. This gives rise to the real-time
Internet-of-things (RT-IoT) that promises a better user experience through
stronger connectivity and efficient use of next-generation embedded devices.
However RT- IoT are also increasingly becoming targets for cyber-attacks which
is exacerbated by this increased connectivity. This paper gives an introduction
to RT-IoT systems, an outlook of current approaches and possible research
challenges towards secure RT- IoT frameworks
Real-time operating system support for multicore applications
Tese (doutorado) - Universidade Federal de Santa Catarina, Centro TecnolĂłgico, Programa de PĂłs-Graduação em Engenharia de Automação e Sistemas, FlorianĂłpolis, 2014Plataformas multiprocessadas atuais possuem diversos nĂveis da memĂłria cache entre o processador e a memĂłria principal para esconder a latĂŞncia da hierarquia de memĂłria. O principal objetivo da hierarquia de memĂłria Ă© melhorar o tempo mĂ©dio de execução, ao custo da previsibilidade. O uso nĂŁo 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 nĂveis da cache compartilhados. Tal acesso causa uma disputa pelas linhas da cache compartilhadas e aumenta o tempo de execução das aplicações. AlĂ©m disso, essa disputa na cache compartilhada pode causar a perda de prazos, o que Ă© intolerável em sistemas de tempo real crĂticos. O particionamento da memĂłria cache compartilhada Ă© uma tĂ©cnica 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 memĂłria cache em multiprocessadores carecem de dois pontos fundamentais. Primeiro, o mecanismo de particionamento da cache Ă© tipicamente implementado em um ambiente simulado ou em um sistema operacional de propĂłsito geral. Consequentemente, o impacto das atividades realizados pelo nĂşcleo do sistema operacional, tais como o tratamento de interrupções e troca de contexto, no particionamento das tarefas tende a ser negligenciado. Segundo, a avaliação Ă© restrita a um escalonador global ou particionado, e assim nĂŁo comparando o desempenho do particionamento da cache em diferentes estratĂ©gias 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 teĂłricos. Entretanto, tais estudos tambĂ©m usaram sistemas operacionais de propĂłsito 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 nĂŁo 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 estratĂ©gias de particionamento da cache e com os algoritmos de escalonamento tempo real multiprocessados da seguinte forma. Primeiro, uma infraestrutura de tempo real para multiprocessadores Ă© 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 tĂ©cnica de coloração de páginas. Segundo, Ă© 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 propĂłsito 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 propĂłsito geral, mostrando claramente como diferentes sistemas operacionais influenciam os escalonadores de tempo real crĂticos em multiprocessadores. Terceiro, Ă© realizada uma avaliação do impacto do particionamento da memĂłria cache em diversos escalonadores de tempo real multiprocessados. Os resultados desta avaliação indicam que um sistema operacional "leve" nĂŁo 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, Ă© proposto um algoritmo de particionamento de tarefas que atribui as tarefas que compartilham partições ao mesmo processador. Os resultados mostram que essa tĂ©cnica de particionamento de tarefas reduz a disputa pelas linhas da cache compartilhadas e provĂŞ garantias de tempo real para sistemas crĂticos. Finalmente, Ă© proposto um escalonador de tempo real de duas fases para multiprocessadores. O escalonador usa informações coletadas durante o tempo de execução das tarefas atravĂ©s 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 Ă© possĂvel impedir que tarefas de melhor esforço acessem as mesmas linhas da cache que tarefas de tempo real. O resultado desta estratĂ©gia de escalonamento Ă© o atendimento dos prazos crĂticos e nĂŁo crĂticos 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 survey of techniques for reducing interference in real-time applications on multicore platforms
This survey reviews the scientific literature on techniques for reducing interference in real-time multicore systems, focusing on the approaches proposed between 2015 and 2020. It also presents proposals that use interference reduction techniques without considering the predictability issue. The survey highlights interference sources and categorizes proposals from the perspective of the shared resource. It covers techniques for reducing contentions in main memory, cache memory, a memory bus, and the integration of interference effects into schedulability analysis. Every section contains an overview of each proposal and an assessment of its advantages and disadvantages.This work was supported in part by the Comunidad de Madrid Government "Nuevas TĂ©cnicas de Desarrollo de Software de Tiempo Real Embarcado Para Plataformas. MPSoC de PrĂłxima GeneraciĂłn" under Grant IND2019/TIC-17261
Real-Time Virtualization and Cloud Computing
In recent years, we have observed three major trends in the development of complex real-time embedded systems. First, to reduce cost and enhance flexibility, multiple systems are sharing common computing platforms via virtualization technology, instead of being deployed separately on physically isolated hosts. Second, multi-core processors are increasingly being used in real-time systems. Third, developers are exploring the possibilities of deploying real-time applications as virtual machines in a public cloud. The integration of real-time systems as virtual machines (VMs) atop common multi-core platforms in a public cloud raises significant new research challenges in meeting the real-time latency requirements of applications.
In order to address the challenges of running real-time VMs in the cloud, we first present RT-Xen, a novel real-time scheduling framework within the popular Xen hypervisor. We start with single-core scheduling in RT-Xen, and present the first work that empirically studies and compares different real-time scheduling schemes on a same platform. We then introduce RT-Xen 2.0, which focuses on multi-core scheduling and spanning multiple design spaces, including priority schemes, server schemes, and scheduling policies. Experimental results demonstrate that when combined with compositional scheduling theory, RT-Xen can deliver real-time performance to an application running in a VM, while the default credit scheduler cannot. After that, we present RT-OpenStack, a cloud management system designed to support co-hosting real-time and non-real-time VMs in a cloud. RT-OpenStack studies the problem of running real-time VMs together with non-real-time VMs in a public cloud. Leveraging the resource interface and real-time scheduling provided by RT-Xen, RT-OpenStack provides real-time performance guarantees to real-time VMs, while achieving high resource utilization by allowing non-real-time VMs to share the remaining CPU resources through a novel VM-to-host mapping scheme. Finally, we present RTCA, a real-time communication architecture for VMs sharing a same host, which maintains low latency for high priority inter-domain communication (IDC) traffic in the face of low priority IDC traffic
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