A día de hoy es prácticamente imposible encontrar una gran institución que no disponga de un parque de ordenadores considerable, debido al alto nivel de informatización de la sociedad actual. El enorme potencial que representan estos miles de ordenadores atrae poderosamente la atención en los ámbitos científicos e industriales, generando opciones viables para su aprovechamiento. Las universidades, instituciones que históricamente se han mantenido a la vanguardia en la investigación e innovación científica, representan un caso especialmente bien posicionado a la hora de generar tanto los recursos informáticos como la necesidad de su uso.El poder de cómputo existente en los laboratorios y aulas de estudio universitarias, agrupaciones naturales de recursos informáticos, crea grandes oportunidades para la computación paralela, animándonos a buscar opciones viables para su aprovechamiento. Como resultado de este interés, nuestro grupo ha creado un entorno de planificación, enfocado hacia los clusters no dedicados. La constante y rápida evolución de los componentes, tanto a nivel de la arquitectura de la CPU como del sistema operativo, así como de las aplicaciones ejecutadas, hace que tengamos que adaptar nuestras propuestas. Nuestra propuesta consiste en crear una Máquina Virtual con doble funcionalidad, ejecutar la carga local de usuario y aprovechar los períodos de inactividad de nodos a efectos de poder usarlos para ejecutar carga paralela. Tanto el tipo de las aplicaciones como las características del hardware del escenario objetivo, y en el momento actual ambas han evolucionado. Nuevos tipos de aplicaciones paralelas con requerimientos periódicos de CPU son cada día más comunes en el mundo científico e industrial. Este tipo de aplicaciones pueden requerir un tiempo de retorno (turnaround) específico o una Calidad de Servicio (Quality of Service, QoS) determinada. Para nuestro caso particular, reviste especial importancia el conocimiento que poseemos de los usuarios locales, debido a que nuestro entorno está diseñado para trabajar en clusters no dedicados. Un usuario local puede estar visualizando un vídeo almacenado en su ordenador, lo cual implica necesidades de CPU periódicas y un mayor uso de memoria. La aparición de nuevos tipos de aplicaciones, como vídeo bajo demanda ó realidad virtual, que se caracterizan por la necesidad de cumplir sus deadlines, presentando requerimientos periódicos de recursos. Este tipo de aplicaciones, donde la pérdida de deadlines no se considera un fallo severo, han sido denominadas en la literatura aplicaciones soft-real time (SRT) periódicas.Esta interesante evolución de las necesidades de los usuarios no es el único digno de atención. El crecimiento en la capacidad de cómputo de los procesadores en los últimos años se ha visto frenado a causa de las barreras físicas del espacio y la velocidad de las señales, obligando a los fabricantes de procesadores a explorar otras vías de crecimiento. Desde hace ya algún tiempo el paralelismo de las aplicaciones se ha convertido en una de las grandes apuestas. Hoy en día los procesadores de dos núcleos son la mínima configuración que encontraremos en un ordenador, y se prevé que el número de núcleos continuará creciendo en los próximos años.Los clusters no dedicados ofrecen un gran potencial de un uso, debido a que los recursos materiales ya están disponibles y el cálculo paralelo se realiza simultáneamente con el del usuario local. Imaginando el escenario actual en los clusters no dedicados, encontramos nuevas aplicaciones de escritorio y paralelas, así como plataformas hardware más potentes y complejas. En esta situación investigar el problema y realizar propuestas relacionadas con la planificación de los diferentes tipos de aplicaciones en clusters no dedicados, considerando las plataformas multicore, supone un nuevo reto a asumir por los investigadores y conforma el núcleo de este trabajo. / Today it is virtually impossible to find an institution that does not have a considerable amount of computers, due to the high level of computerization of society. The enormous potential of these large number of computers attract a lot of attention in science and industry, generating viable options for their use. The universities, institutions that historically have remained at the forefront of research and scientific innovation, represent a case particularly well positioned in generating both, computing resources and the need to use. The computational power present in laboratories and university study rooms, natural groupings of information resources, creating great opportunities for parallel computing, encouraging us to seek viable options for their use. As a result of this interest, our group has created a parallel scheduling environment, focused on non-dedicated clusters. The constant and fast evolution of the components, both at the architecture of the CPU and the operating system and applications executed, forces us to adapt our proposals. Our proposal is to create a Virtual Machine with dual functionality, run the local load user and take advantage of downtime for the purposes of nodes it can be used to run parallel load. At present both, applications and hardware specifications of the target scenario, have evolved. New types of parallel applications with periodic CPU requirements are becoming more common in science and industry. Such applications may require a return time (turnaround) or a specific QoS (Quality of Service). Since our framework is designed to work in non-dedicated clusters, having knowledge of the local users behavior is of particular importance. A local user may be viewing a video stored on your computer, which involves periodic CPU requirements and increased use of memory. The emerging new types of applications, such as video on demand or virtual reality are a fact. This new types of applications are characterized by the need to meet their deadlines, presenting periodic resource requirements. This type of application, where the loss of deadlines is not considered a severe failure, has been named in the literature uses soft-real time (SRT) at regular intervals. This exciting evolution of user needs is not the only one worthy of attention. The growth in computing power of processors in recent years has been hampered because of the physical barriers of space and speed of the signals, forcing chip makers to explore other avenues of growth. For some time the parallelism of the applications has become one of the biggest bets. Today's dual-core processors are the minimum configuration of any computer, and it is expected that the number of nuclei continue to grow in the coming years. The non-dedicated clusters offer great potential for use, because the computational resources are already available, and parallel computing is performed simultaneously with the local user. Figuring out the current scenario in the non-dedicated clusters, we find new desktop applications, parallel and more powerful and complex hardware platforms. In this situation, research lines related to the planning of the different types of applications in non dedicated clusters, considering multi-core platforms, is a new challenge to be assumed by researchers and constitute the core of this work.

International Telemetering Conference Proceedings / October 23-26, 2000 / Town & Country Hotel and Conference Center, San Diego, California / Since its debut, the Linux operating system has garnered much attention in the software development community. This paper discusses the open source operating system, Linux, and it’s application as the operating system powering a commercial off-the-shelf telemetry processing system. The paper begins by discussing what are the real-time requirements of the operating system in a telemetry processing system. A discussion to the Linux system is then presented. Soft real-time features of Linux are discussed which allow it to meet the telemetry processing requirements. Linux is compared with the more traditional operating system products and points are made as to why open source software is just as capable, if not preferable, of handling mission critical applications. The paper also presents the authors’ view of future of Linux and open source software in the telemetry marketplace. The paper concludes with a summary of products available for Linux that support telemetry processing and the data acquisition environment.

The focus of this dissertation is adaptive CPU-budget allocation for periodic soft-real-time applications. The presented algorithms are developed in the context of a power-management framework. First, the prediction-based bandwidth scheduler (PBS) is developed. This algorithm is designed to adapt CPU-budget allocations at a faster rate than previous adaptive algorithms. Simulation results are presented to demonstrate that this approach allows for a faster response to under allocations than previous algorithms. A second algorithm is presented called Two-Stage Prediction (TSP) that improves on the PBS algorithm. Specifically, a more sophisticated algorithm is used to predict execution times and a stronger guarantee is provided on the timeliness of jobs. Implementation details and experimental results are presented for both the PBS and TSP algorithms. An abstraction is presented called virtual instruction count (VIC) to allow for more efficient budget allocation in power-managed systems. Power management decisions affect job-execution times. VIC is an abstract measure of computation that allows budget allocations to be made independent of power-management decisions. Implementation details and experimental results are presented for a VIC-based budget mechanism. Finally, a power-management framework is presented called the linear adaptive models based system (LAMbS). LAMbS is designed to minimize power consumption while honoring budget allocations specified in terms of VIC.

[pt] Nesse trabalho comparamos o uso da programação reativa estruturada com o uso do ReactiveX no desenvolvimento de aplicações reativas soft real time. Apresentamos implementações de aplicações em Lua que demonstram o uso desses modelos em diferentes situações, destacando as vantagens de cada um. Consideramos também o seu uso combinado em uma mesma aplicação. Além disso, implementamos um módulo que permite utilizar a programação reativa estruturada em Lua e utilizamos o módulo RxLua que implementa o modelo ReactiveX. / [en] In this work we compare the use of structured reactive programming and ReactiveX in the development of reactive soft real time applications. We present application implementations using Lua that demonstrate the use of these models in multiple situations, pointing the advantages of using each one. Another consideration is combining both models in a single application. We also developed a module that allows the use of structured reactive programming in Lua and used the RxLua module which implements the ReactiveX model.

In recent years, Internet and IP technologies have made inroads into almost every commu- nication market ranging from best-effort services such as email and Web, to soft real-time applications such as VoIP, IPTV, and video. However, providing a transport service over IP that meets the timeliness and availability requirements of soft real-time applications has turned out to be a complex task. Although network solutions such as IntServ, DiffServ, MPLS, and VRRP have been suggested, these solutions many times fail to provide a trans- port service for soft real-time applications end to end. Additionally, they have so far only been modestly deployed. In light of this, this thesis considers transport protocols for soft real-time applications. Part I of the thesis focuses on the design and analysis of transport protocols for soft real- time multimedia applications with lax deadlines such as image-intensive Web applications. Many of these applications do not need a completely reliable transport service, and to this end Part I studies so-called partially reliable transport protocols, i.e., transport protocols that enable applications to explicitly trade reliability for improved timeliness. Specifically, Part I investigates the feasibility of designing retransmission-based, partially reliable transport protocols that are congestion aware and fair to competing traffic. Two transport protocols are presented in Part I, PRTP and PRTP-ECN, which are both extensions to TCP for partial reliability. Simulations and theoretical analysis suggest that these transport protocols could give a substantial improvement in throughput and jitter as compared to TCP. Additionally, the simulations indicate that PRTP-ECN is TCP friendly and fair against competing congestion- aware traffic such as TCP flows. Part I also presents a taxonomy for retransmission-based, partially reliable transport protocols. Part II of the thesis considers the Stream Control Transmission Protocol (SCTP), which was developed by the IETF to transfer telephony signaling traffic over IP. The main focus of Part II is on evaluating the SCTP failover mechanism. Through extensive experiments, it is suggested that in order to meet the availability requirements of telephony signaling, SCTP has to be configured much more aggressively than is currently recommended by IETF. Fur- thermore, ways to improve the transport service provided by SCTP, especially with regards to the failover mechanism, are suggested. Part II also studies the effects of Head-of-Line Blocking (HoLB) on SCTP transmission delays. HoLB occurs when packets in one flow block packets in another, independent, flow. The study suggests that the short-term effects of HoLB could be substantial, but that the long-term effects are marginal.

<p>In the past 10 years, the bandwidths and processing capabilities of the networks have increased dramatically. The number of real-time applications using these networks has also increased. The large number of real-time packets might, in a switched multi-hop network, lead to unpredictable traffic patterns. This is not a problem when the traffic intensity is low, but if the same network is used by a large number of users simultaneously, the overall performance of the network degrades. In fact, unpredictable delays in the delivery of the message can adversely affect the execution of the tasks dependent on these messages, even if we take into account the soft real-time performance.</p><p>In this paper, we investigate the effect of traffic shapers on soft real-time performance. We will consider a switched multi-hop network with FCFS queues. We will implement two versions of the network simulator. One version will be without traffic shaper and the other version will use a traffic shaper. By comparing the results (for average delay, deadline miss ratio etc.) from both the versions, we will try to conclude if it is really beneficial to use traffic shapers for soft real-time performance. Leaky bucket and token bucket algorithms are the most popular ones for traffic shaper implementation. We will consider leaky bucket algorithm for our analysis. We analyse different versions of the leaky bucket and present the trade-off’s involved.</p>

In the past 10 years, the bandwidths and processing capabilities of the networks have increased dramatically. The number of real-time applications using these networks has also increased. The large number of real-time packets might, in a switched multi-hop network, lead to unpredictable traffic patterns. This is not a problem when the traffic intensity is low, but if the same network is used by a large number of users simultaneously, the overall performance of the network degrades. In fact, unpredictable delays in the delivery of the message can adversely affect the execution of the tasks dependent on these messages, even if we take into account the soft real-time performance. In this paper, we investigate the effect of traffic shapers on soft real-time performance. We will consider a switched multi-hop network with FCFS queues. We will implement two versions of the network simulator. One version will be without traffic shaper and the other version will use a traffic shaper. By comparing the results (for average delay, deadline miss ratio etc.) from both the versions, we will try to conclude if it is really beneficial to use traffic shapers for soft real-time performance. Leaky bucket and token bucket algorithms are the most popular ones for traffic shaper implementation. We will consider leaky bucket algorithm for our analysis. We analyse different versions of the leaky bucket and present the trade-off’s involved.

This document is a master’s thesis analyzing an automated fuel pump management system. In the first chapters we take a general overview of the system and the main problems that we will be facing during the planning and design phases of the project. Later we propose and analyze possible solutions for these problems. Technical system information is revealed in the later chapters. Functional and non functional requirements are discussed along with the main UML diagrams. The research phase of the thesis provides detailed system analysis and software quality reports which later are used to create proposed changes to the system. These changes are analyzed, designed and coded in the final - experimental part of the thesis. The main proposal is to convert the system architecture from flow driven to event driven. This change helps to solve several uncovered architectural problems as well as improve the general quality of the system. These changes are tested and analyzed in the experimental chapter of the thesis and finally the conclusions are made. The main conclusion is that the proposed architectural changes were chosen correctly. This is also supported by the experimental data.

Hard real-time systems in robotics, space and military missions, and control devices are specified with stringent and critical time constraints. On the other hand, soft real-time applications arising from multimedia, telecommunications, Internet web services, and games are specified with more lenient constraints. Real-time systems can also be distinguished in terms of their implementation into preemptive and non-preemptive systems. In preemptive systems, tasks are often preempted by higher priority tasks. Non-preemptive systems are gaining interest for implementing soft-real applications on multithreaded platforms. In this dissertation, I propose a new algorithm that uses a two-level scheduling strategy for scheduling non-preemptive soft real-time tasks. Our goal is to improve the success ratios of the well-known earliest deadline first (EDF) approach when the load on the system is very high and to improve the overall performance in both underloaded and overloaded conditions. Our approach, known as group-EDF (gEDF), is based on dynamic grouping of tasks with deadlines that are very close to each other, and using a shortest job first (SJF) technique to schedule tasks within the group. I believe that grouping tasks dynamically with similar deadlines and utilizing secondary criteria, such as minimizing the total execution time can lead to new and more efficient real-time scheduling algorithms. I present results comparing gEDF with other real-time algorithms including, EDF, best-effort, and guarantee scheme, by using randomly generated tasks with varying execution times, release times, deadlines and tolerances to missing deadlines, under varying workloads. Furthermore, I implemented the gEDF algorithm in the Linux kernel and evaluated gEDF for scheduling real applications.

This research presents a hybrid algorithm that combines List Scheduling (LS) with a Genetic Algorithm (GA) for constructing non-preemptive schedules for soft real-time parallel applications represented as directed acyclic graphs (DAGs). The execution time requirements of the applications' tasks are assumed to be stochastic and are represented as probability distribution functions. The performance in terms of schedule lengths for three different genetic representation schemes are evaluated and compared for a number of different DAGs. The approaches presented in this research produce shorter schedules than HLFET, a popular LS approach for all of the sample problems. Of the three genetic representation schemes investigated, PosCT, the technique that allows the GA to learn which tasks to delay in order to allow other tasks to complete produced the shortest schedules for a majority of the sample DAGs.