Energy-efficient thermal-aware multiprocessor scheduling for real-time tasks using TCPNs

We present an energy-effcient thermal-aware real-time global scheduler for a set of hard real-time (HRT) tasks running on a multiprocessor system. This global scheduler fulfills the thermal and temporal constraints by handling two independent variables, the task allocation time and the selection of clock frequency. To achieve its goal, the proposed scheduler is split into two stages. An off-line stage, based on a deadline partitioning scheme, computes the cycles that the HRT tasks must run per deadline interval at the minimum clock frequency to save energy while honoring the temporal and thermal constraints, and computes the maximum frequency at which the system can run below the maximum temperature. Then, an on-line, event-driven stage performs global task allocation applying a Fixed-Priority Zero-Laxity policy, reducing the overhead of quantum-based or interval-based global schedulers. The on-line stage embodies an adaptive scheduler that accepts or rejects soft RT aperiodic tasks throttling CPU frequency to the upper lowest available one to minimize power consumption while meeting time and thermal constraints. This approach leverages the best of two worlds: the off-line stage computes an ideal discrete HRT multiprocessor schedule, while the on-line stage manage soft real-time aperiodic tasks with minimum power consumption and maximum CPU utilization

Laxity dynamics and LLF schedulability analysis on multiprocessor platforms

LLF (Least Laxity First) scheduling, which assigns a higher priority to a task with a smaller laxity, has been known as an optimal preemptive scheduling algorithm on a single processor platform. However, little work has been made to illuminate its characteristics upon multiprocessor platforms. In this paper, we identify the dynamics of laxity from the system’s viewpoint and translate the dynamics into LLF multiprocessor schedulability analysis. More specifically, we first characterize laxity properties under LLF scheduling, focusing on laxity dynamics associated with a deadline miss. These laxity dynamics describe a lower bound, which leads to the deadline miss, on the number of tasks of certain laxity values at certain time instants. This lower bound is significant because it represents invariants for highly dynamic system parameters (laxity values). Since the laxity of a task is dependent of the amount of interference of higher-priority tasks, we can then derive a set of conditions to check whether a given task system can go into the laxity dynamics towards a deadline miss. This way, to the author’s best knowledge, we propose the first LLF multiprocessor schedulability test based on its own laxity properties. We also develop an improved schedulability test that exploits slack values. We mathematically prove that the proposed LLF tests dominate the state-of-the-art EDZL tests. We also present simulation results to evaluate schedulability performance of both the original and improved LLF tests in a quantitative manner

Control techniques for thermal-aware energy-efficient real time multiprocessor scheduling

La utilización de microprocesadores multinúcleo no sólo es atractiva para la industria sino que en muchos ámbitos es la única opción. La planificación tiempo real sobre estas plataformas es mucho más compleja que sobre monoprocesadores y en general empeoran el problema de sobre-diseño, llevando a la utilización de muchos más procesadores /núcleos de los necesarios. Se han propuesto algoritmos basados en planificación fluida que optimizan la utilización de los procesadores, pero hasta el momento presentan en general inconvenientes que los alejan de su aplicación práctica, no siendo el menor el elevado número de cambios de contexto y migraciones.Esta tesis parte de la hipótesis de que es posible diseñar algoritmos basados en planificación fluida, que optimizan la utilización de los procesadores, cumpliendo restricciones temporales, térmicas y energéticas, con un bajo número de cambios de contexto y migraciones, y compatibles tanto con la generación fuera de línea de ejecutivos cíclicos atractivos para la industria, como de planificadores que integran técnicas de control en tiempo de ejecución que permiten la gestión eficiente tanto de tareas aperiódicas como de desviaciones paramétricas o pequeñas perturbaciones.A este respecto, esta tesis contribuye con varias soluciones. En primer lugar, mejora una metodología de modelo que representa todas las dimensiones del problema bajo un único formalismo (Redes de Petri Continuas Temporizadas). En segundo lugar, propone un método de generación de un ejecutivo cíclico, calculado en ciclos de procesador, para un conjunto de tareas tiempo real duro sobre multiprocesadores que optimiza la utilización de los núcleos de procesamiento respetando también restricciones térmicas y de energía, sobre la base de una planificación fluida. Considerar la sobrecarga derivada del número de cambios de contexto y migraciones en un ejecutivo cíclico plantea un dilema de causalidad: el número de cambios de contexto (y en consecuencia su sobrecarga) no se conoce hasta generar el ejecutivo cíclico, pero dicho número no se puede minimizar hasta que se ha calculado. La tesis propone una solución a este dilema mediante un método iterativo de convergencia demostrada que logra minimizar la sobrecarga mencionada.En definitiva, la tesis consigue explotar la idea de planificación fluida para maximizar la utilización (donde maximizar la utilización es un gran problema en la industria) generando un sencillo ejecutivo cíclico de mínima sobrecarga (ya que la sobrecarga implica un gran problema de los planificadores basados en planificación fluida).Finalmente, se propone un método para utilizar las referencias de la planificación fuera de línea establecida en el ejecutivo cíclico para su seguimiento por parte de un controlador de frecuencia en línea, de modo que se pueden afrontar pequeñas perturbaciones y variaciones paramétricas, integrando la gestión de tareas aperiódicas (tiempo real blando) mientras se asegura la integridad de la ejecución del conjunto de tiempo real duro.Estas aportaciones constituyen una novedad en el campo, refrendada por las publicaciones derivadas de este trabajo de tesis.<br /

Energy-Efficient Thermal-Aware Scheduling for RT Tasks Using TCPN

This work leverages TCPNs to design an energy-efficient, thermal-aware real-time scheduler for a multiprocessor system that normally runs in a low state energy at maximum system utilization but its capable of increasing the clock frequency to serve aperiodic tasks, optimizing energy, and honoring temporal and thermal constraints. An off-line stage computes the minimum frequency required to run the periodic tasks at maximum CPU utilization, the proportion of each task''s job to be run on each CPU, the maximum clock frequency that keeps temperature under a limit, and the available cycles (slack) with respect to the system with minimum frequency. Then, a Zero-Laxity online scheduler dispatches the periodic tasks according to the offline calculation. Upon the arrival of aperiodic tasks, it increases clock frequency in such a way that all periodic and aperiodic tasks are properly executed. Thermal and temporal requirements are always guaranteed, and energy consumption is minimized

Real-time scheduling in multicore : time- and space-partitioned architectures

Tese de doutoramento, Informática (Engenharia Informática), Universidade de Lisboa, Faculdade de Ciências, 2014The evolution of computing systems to address size, weight and power consumption (SWaP) has led to the trend of integrating functions (otherwise provided by separate systems) as subsystems of a single system. To cope with the added complexity of developing and validating such a system, these functions are maintained and analyzed as components with clear boundaries and interfaces. In the case of real-time systems, the adopted component-based approach should maintain the timeliness properties of the function inside each individual component, regardless of the remaining components. One approach to this issue is time and space partitioning (TSP)—enforcing strict separation between components in the time and space domains. This allows heterogeneous components (different real-time requirements, criticality, developed by different teams and/or with different technologies) to safely coexist. The concepts of TSP have been adopted in the civil aviation, aerospace, and (to some extent) automotive industries. These industries are also embracing multiprocessor (or multicore) platforms, either with identical or nonidentical processors, but are not taking full advantage thereof because of a lack of support in terms of verification and certification. Furthermore, due to the use of the TSP in those domains, compatibility between TSP and multiprocessor is highly desired. This is not the present case, as the reference TSP-related specifications in the aforementioned industries show limited support to multiprocessor. In this dissertation, we defend that the active exploitation of multiple (possibly non-identical) processor cores can augment the processing capacity of the time- and space-partitioned (TSP) systems, while maintaining a compromise with size, weight and power consumption (SWaP), and open room for supporting self-adaptive behavior. To allow applying our results to a more general class of systems, we analyze TSP systems as a special case of hierarchical scheduling and adopt a compositional analysis methodology.Fundação para a Ciência e a Tecnologia (FCT, SFRH/BD/60193/2009, programa PESSOA, projeto SAPIENT); the European Space Agency Innovation (ESA) Triangle Initiative program through ESTEC Contract 21217/07/NL/CB, Project AIR-II; the European Commission Seventh Framework Programme (FP7) through project KARYON (IST-FP7-STREP-288195)

Real-Time Sensor Networks and Systems for the Industrial IoT

The Industrial Internet of Things (Industrial IoT—IIoT) has emerged as the core construct behind the various cyber-physical systems constituting a principal dimension of the fourth Industrial Revolution. While initially born as the concept behind specific industrial applications of generic IoT technologies, for the optimization of operational efficiency in automation and control, it quickly enabled the achievement of the total convergence of Operational (OT) and Information Technologies (IT). The IIoT has now surpassed the traditional borders of automation and control functions in the process and manufacturing industry, shifting towards a wider domain of functions and industries, embraced under the dominant global initiatives and architectural frameworks of Industry 4.0 (or Industrie 4.0) in Germany, Industrial Internet in the US, Society 5.0 in Japan, and Made-in-China 2025 in China. As real-time embedded systems are quickly achieving ubiquity in everyday life and in industrial environments, and many processes already depend on real-time cyber-physical systems and embedded sensors, the integration of IoT with cognitive computing and real-time data exchange is essential for real-time analytics and realization of digital twins in smart environments and services under the various frameworks’ provisions. In this context, real-time sensor networks and systems for the Industrial IoT encompass multiple technologies and raise significant design, optimization, integration and exploitation challenges. The ten articles in this Special Issue describe advances in real-time sensor networks and systems that are significant enablers of the Industrial IoT paradigm. In the relevant landscape, the domain of wireless networking technologies is centrally positioned, as expected

Sincronização de processos em sistemas de tempo real no contexto de multiprocessadores

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Automação e Sistemas, Florianópolis, 2012Sistemas computacionais de tempo real são identificados como aqueles sistemas computacionais submetidos a requisitos de natureza temporal. Nestes sistemas, os resultados devem estar corretos não somente do ponto de vista lógico, mas também devem ser gerados no momento correto. Em tais sistemas, quando existe o compartilhamento de recursos, a sincronização de tarefas no acesso a estes é fundamental para garantir tanto a exclusão mútua, quanto a limitação no tempo de espera (evitando inversões de prioridade descontroladas), visto que isto pode induzir as tarefas a gerarem seus resultados em momentos incorretos (perda de deadlines ou não atendimento de algum requisito temporal). O não atendimento de um requisito temporal pode resultar em consequências catastróficas tanto no sentido econômico quanto em vidas humanas, dependendo do tipo de sistema. Para sincronização em multiprocessadores, alguns protocolos para escalonamento particionado foram propostos, como o Multiprocessor Priority Ceiling Protocol (MPCP), Flexible Multiprocessor Locking Protocol (FMLP) e o Multiprocessor Stack Resource Policy (MSRP). Neste contexto, esta dissertação de mestrado propõe duas variações para o protocolo MPCP, com as devidas análises de escalonabilidade e fatores de bloqueios associados. No entanto, ambas as variações podem ser encaradas também como variações do FMLP, dependendo do ponto de vista, pois abrangem características comuns a ambos os protocolos. Tais variações são o MPCP não preemptivo e MPCP com enfileiramento FIFO. Esta dissertação também apresenta comparações empíricas entre as propostas apresentadas e os protocolos existentes. Como resultados gerais, as propostas apresentadas se mostraram competitivas tanto em escalonabilidade quanto em overhead de implementação. O MPCP com enfileiramento FIFO se posicionou muito bem em sua versão baseada em suspensão. O MPCP não preemptivo, em sua versão baseada em spin obteve resultados muito próximos ao FMLP short. Do ponto de vista prático, as variações propostas facilitam a utilização em sistemas reais, quando comparadas com as propostas originais.Abstract : Real-time computational systems are identified as those systems subjected requirements of temporal nature. In these systems, the results should be correct not only from logical point of view, but also must be generated at the right time. In such systems, when there is resource sharing, tasks synchronization on access to these resources is essential to ensure both mutual exclusion and limitation of the waiting time (avoiding uncontrolled priority inversion), as this may induce the tasks to generate their results at wrong times (miss of deadlines or not meet a time requirement). A failure to meet a time requirement can result in catastrophic consequences both in the economic sense and in human lives, depending on the type of the system. For synchronization in multiprocessors, some protocols have been proposed for partitioned scheduling, as the Multiprocessor Priority Ceiling Protocol (MPCP), Flexible Multiprocessor Locking Protocol (FMLP) and Multiprocessor Stack Resource Policy (MSRP). In this context, this dissertation proposes two changes to the MPCP protocol, with appropriate schedulability analysis and blocking factors associated. However, both variants can also be viewed as variations of FMLP, depending on the point of view, because they cover features common to both protocols. Such variations are the nonpreemptive MPCP and the MPCP with FIFO queuing. This dissertation also presents empirical comparisons between the previously mentioned well-known protocols and the proposed variations. As general results, the proposals have showed to be competitive in both schedulability and implementation overhead. The MPCP with FIFO queuing was positioned very well in the suspension-based version. The nonpreemptive MPCP, in his spin-based version obtained results very close to the FMLP short. From a practical standpoint, the proposed changes facilitate the implementation in real systems, when compared to the original proposals

Maximising microprocessor reliability through game theory and heuristics

PhD ThesisEmbedded Systems are becoming ever more pervasive in our society, with most routine daily tasks now involving their use in some form and the market predicted to be worth USD 220 billion, a rise of 300%, by 2018. Consumers expect more functionality with each design iteration, but for no detriment in perceived performance. These devices can range from simple low-cost chips to expensive and complex systems and are a major cost driver in the equipment design phase. For more than 35 years, designers have kept pace with Moore's Law, but as device size approaches the atomic limit, layouts are becoming so complicated that current scheduling techniques are also reaching their limit, meaning that more resource must be reserved to manage and deliver reliable operation. With the advent of many-core systems and further sources of unpredictability such as changeable power supplies and energy harvesting, this reservation of capability may become so large that systems will not be operating at their peak efficiency. These complex systems can be controlled through many techniques, with jobs scheduled either online prior to execution beginning or online at each time or event change. Increased processing power and job types means that current online scheduling methods that employ exhaustive search techniques will not be suitable to define schedules for such enigmatic task lists and that new techniques using statistic-based methods must be investigated to preserve Quality of Service. A new paradigm of scheduling through complex heuristics is one way to administer these next levels of processor effectively and allow the use of more simple devices in complex systems; thus reducing unit cost while retaining reliability a key goal identified by the International Technology Roadmap for Semi-conductors for Embedded Systems in Critical Environments. These changes would be beneficial in terms of cost reduction and system exibility within the next generation of device. This thesis investigates the use of heuristics and statistical methods in the operation of real-time systems, with the feasibility of Game Theory and Statistical Process Control for the successful supervision of high-load and critical jobs investigated. Heuristics are identified as an effective method of controlling complex real-time issues, with two-person non-cooperative games delivering Nash-optimal solutions where these exist. The simplified algorithms for creating and solving Game Theory events allow for its use within small embedded RISC devices and an increase in reliability for systems operating at the apex of their limits. Within this Thesis, Heuristic and Game Theoretic algorithms for a variety of real-time scenarios are postulated, investigated, refined and tested against existing schedule types; initially through MATLAB simulation before testing on an ARM Cortex M3 architecture functioning as a simplified automotive Electronic Control Unit.Doctoral Teaching Account from the EPSRC