Practical performance analysis of real-time multiprocessor scheduling algorithms

This paper presents a practical performance analysing of two real-time multiprocessor scheduling algorithms, namely, Largest Remaining Execution-Time and Local Time Domain (LRE-TL) and Unfair Semi-Greedy (USG). The analysis is intended to reflect the behindthe- scene time overhead incurred by optimal real-time algorithms such as LRE-TL. The overhead is known to be capable of dismissing the actual optimality of such algorithms in practical applications. Here, the time overhead is measured in terms of the number of scheduler invocations and the time required by the scheduling event handlers. In the implementation of the proposed analysis method, the CPU profiler of Oracle JavaTM VisualVM was used to monitor the executions of LRE-TL and USG. The profiler measured the number of invocations of the scheduling event handlers for each algorithm and the total time required for all the invocations. The results revealed that USG outperformed LRE-TL on both measures, indicating that optimal algorithms may prove to be non-optimal in practical applications.Keywords: Real-time; Multiprocessor; Schedulin

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

Real Time Event Management and Coordinating System

Analysis and prediction of real time event managing is very important and interesting as this helps experts in managing events , making decisions and working more efficiently . This thesis Event Managing And Coordinating system (RT-EMaCS) model is initially considered for proper managing of time and task, and resulted in funtioning in both system field as well as practical world. A EMaCS model can fit into any Java based platform such as laptops, desktops and any mobile device supporting Java, specially like android phones or tablets. The link between them can be done via Wi-Fi. In this thesis, the event organizers and the event coordinators communcate with better facilities in event management. It provides an easy, simple and better means of communication among one another. It prevents loss of time

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 scheduler for multiprocessor systems based on continuous control using timed continuous petri nets

This work exploits Timed Continuous Petri Nets (TCPN) to design and test a novel energy-efficient thermal-aware real-time global scheduler for a hard real-time (HRT) task set running on a multiprocessor system. The TCPN model encompasses both the system and task set, including thermal features. In previous work we calculated the share of each task that must be executed per time interval by solving off-line an Integer Programming Problem Problem (ILP). A subsequent on-line stage allocated jobs to processors. We now perform the allocation off-line too, including an allocation controller and an execution controller in the on-line stage. This adds robustness by ensuring that actual task allocation and execution honor the safe schedule provided off-line. Last, the on-line controllers allow the design of an improved soft RT aperiodic task manager. Also, ee experimentally prove that our scheduler yields fewer context switches and migrations on the HRT task set than RUN, a reference algorith

Reinforcement learning based multi core scheduling (RLBMCS) for real time systems

Embedded systems with multi core processors are increasingly popular because of the diversity of applications that can be run on it. In this work, a reinforcement learning based scheduling method is proposed to handle the real time tasks in multi core systems with effective CPU usage and lower response time. The priority of the tasks is varied dynamically to ensure fairness with reinforcement learning based priority assignment and Multi Core MultiLevel Feedback queue (MCMLFQ) to manage the task execution in multi core system

EDZL Scheduling for Large-Scale Cyber Service on Real-Time Cloud

[[sponsorship]]IEEE Computer Society Technical Committee on Business Informatics Systems[[conferencetype]]國際[[conferencedate]]20111212~20111214[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Irvine, US