Multiprocessor real-time scheduling considering concurrency and urgency

It has been widely studied how to schedule real-time tasks on multiprocessor platforms. Several studies find optimal scheduling policies for implicit deadline task systems, but it is hard to understand how each policy utilizes the two important aspects of scheduling real-time tasks on multiprocessors:inter-job concurrency and job urgency. In this paper, we introduce a new scheduling policy that considers these two properties. We prove that the policy is optimal for the special case when the execution time of all tasks are equally one and deadlines are implicit, and observe that the policy is a new concept in that it is not an instance of Pfair or ERfair. It remains open to find a schedulability condition for general task systems under our scheduling policy.

Dimensioning and worst-case analysis of cluster-tree sensor networks

Modeling the fundamental performance limits of Wireless Sensor Networks (WSNs) is of paramount importance to understand their behavior under the worst-case conditions and to make the appropriate design choices. This is particular relevant for time-sensitive WSN applications, where the timing behavior of the network protocols (message transmission must respect deadlines) impacts on the correct operation of these applications. In that direction this paper contributes with a methodology based on Network Calculus, which enables quick and efficient worst-case dimensioning of static or even dynamically changing cluster-tree WSNs where the data sink can either be static or mobile. We propose closed-form recurrent expressions for computing the worst-case end-to-end delays, buffering and bandwidth requirements across any source-destination path in a cluster-tree WSN. We show how to apply our methodology to the case of IEEE 802.15.4/ZigBee cluster-tree WSNs. Finally, we demonstrate the validity and analyze the accuracy of our methodology through a comprehensive experimental study using commercially available technology, namely TelosB motes running TinyOS.

Online robust optimization framework for QoS guarantees in distributed soft real-time systems

In distributed soft real-time systems, maximizing the aggregate quality-of-service (QoS) is a typical system-wide goal, and addressing the problem through distributed optimization is challenging. Subtasks are subject to unpredictable failures in many practical environments, and this makes the problem much harder. In this paper, we present a robust optimization framework for maximizing the aggregate QoS in the presence of random failures. We introduce the notion of K-failure to bound the effect of random failures on schedulability. Using this notion we define the concept of K-robustness that quantifies the degree of robustness on QoS guarantee in a probabilistic sense. The parameter K helps to tradeoff achievable QoS versus robustness. The proposed robust framework produces optimal solutions through distributed computations on the basis of Lagrangian duality, and we present some implementation techniques. Our simulation results show that the proposed framework can probabilistically guarantee sub-optimal QoS which remains feasible even in the presence of random failures.

The utilization bound of uniprocessor preemptive slack-monotonic scheduling is 50%

Consider the problem of scheduling a set of sporadically arriving implicit-deadline tasks to meet deadlines on a uniprocessor. Static-priority scheduling is considered using the slack-monotonic priority-assignment scheme. We prove that its utilization bound is 50%.

Dynamic QoS adaptation of inter- dependent task sets in cooperative embedded systems

Due to the growing complexity and dynamism of many embedded application domains (including consumer electronics, robotics, automotive and telecommunications), it is increasingly difficult to react to load variations and adapt the system's performance in a controlled fashion within an useful and bounded time. This is particularly noticeable when intending to benefit from the full potential of an open distributed cooperating environment, where service characteristics are not known beforehand and tasks may exhibit unrestricted QoS inter-dependencies. This paper proposes a novel anytime adaptive QoS control policy in which the online search for the best set of QoS levels is combined with each user's personal preferences on their services' adaptation behaviour. Extensive simulations demonstrate that the proposed anytime algorithms are able to quickly find a good initial solution and effectively optimise the rate at which the quality of the current solution improves as the algorithms are given more time to run, with a minimum overhead when compared against their traditional versions.

A framework for the response time analysis of fixed-priority tasks with stochastic inter-arrival times

Real-time scheduling usually considers worst-case values for the parameters of task (or message stream) sets, in order to provide safe schedulability tests for hard real-time systems. However, worst-case conditions introduce a level of pessimism that is often inadequate for a certain class of (soft) real-time systems. In this paper we provide an approach for computing the stochastic response time of tasks where tasks have inter-arrival times described by discrete probabilistic distribution functions, instead of minimum inter-arrival (MIT) values.

Conforto Térmico em Meio Hospitalar: o caso do Serviço de Esterilização.

Os hospitais constituem locais de trabalho bastante peculiares, concebidos quase exclusivamente em função das necessidades dos utentes, proporcionando aos seus trabalhadores condições laborais precárias. Os parâmetros especificados na legislação nacional respeitantes ao ambiente térmico, cingem-se aos valores de temperatura, humidade e velocidade do ar recomendados pelo DL nº 243/86 de 20 de Agosto e DL nº 79/2006 de 4 de Abril,respectivamente. Para além da conformidade legal dos parâmetros térmicos, este trabalho teve como objectivo determinar índices de conforto térmico, sensações e preferências, a partir de um estudo de campo efectuado no Serviço de Esterilização duma Unidade Hospitalar do Porto, durante os meses de Julho e Agosto de 2010. A determinação e interpretação analítica do conforto térmico, foi efectuada com base nos pressupostos das normas ISO 7726:1998, ISO 8996:2004 e ISO 7730:2005. Complementarmente aplicou-se um questionário para aferir as variáveis subjectivas, baseado na norma ISO 10551:1995. Verificou-se que os valores de humidade do ar obtidos durante a semana se enquadraram na gama de valores recomendados (50 a 70%). No que se refere à temperatura, os valores encontrados foram superiores ao recomendado (18 a 22ºC). No que respeita à velocidade do ar os valores obtidos ultrapassaram em certas ocasiões os 0,2 m/s recomendados. Relativamente aos índices de conforto, o PMV e o PPD ultrapassaram em alguns períodos da semana a gama recomendada de -0,5 a +0,5 e <10%, respectivamente. A aplicação do questionário permitiu verificar que no início do turno (44,7%) dos trabalhadores se sentia "confortável". Relativamente às preferências térmicas, no mesmo período a maioria dos trabalhadores questionados (39,7%) preferiam que o ambiente mantivesse as mesmas condições. No final do turno as sensações e preferências térmicas foram similares. Concluiu-se que eventualmente os índices PMV/PPD poderão ser inadequados para aferir a sensações de conforto em ambiente hospitalar.

A genetic algorithm for project scheduling with multi-modes and renewable resources

This paper presents a genetic algorithm-based approach for project scheduling with multi-modes and renewable resources. In this problem activities of the project may be executed in more than one operating mode and renewable resource constraints are imposed. The objective function is the minimization of the project completion time. The idea of this approach is integrating a genetic algorithm with a schedule generation scheme. This study also proposes applying a local search procedure trying to yield a better solution when the genetic algorithm and the schedule generation scheme obtain a solution. The experimental results show that this algorithm is an effective method for solving this problem.

Project scheduling using a competitive genetic algorithm

- The resource constrained project scheduling problem (RCPSP) is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. During the last couple of years many heuristic procedures have been developed for this problem, but still these procedures often fail in finding near-optimal solutions. This paper proposes a genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities and delay times of the activities are defined by the genetic algorithm. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm

A comparative analysis of fault injection methods via enhanced on-chip debug infrastructures

On-chip debug (OCD) features are frequently available in modern microprocessors. Their contribution to shorten the time-to-market justifies the industry investment in this area, where a number of competing or complementary proposals are available or under development, e.g. NEXUS, CJTAG, IJTAG. The controllability and observability features provided by OCD infrastructures provide a valuable toolbox that can be used well beyond the debugging arena, improving the return on investment rate by diluting its cost across a wider spectrum of application areas. This paper discusses the use of OCD features for validating fault tolerant architectures, and in particular the efficiency of various fault injection methods provided by enhanced OCD infrastructures. The reference data for our comparative study was captured on a workbench comprising the 32-bit Freescale MPC-565 microprocessor, an iSYSTEM IC3000 debugger (iTracePro version) and the Winidea 2005 debugging package. All enhanced OCD infrastructures were implemented in VHDL and the results were obtained by simulation within the same fault injection environment. The focus of this paper is on the comparative analysis of the experimental results obtained for various OCD configurations and debugging scenarios.

A genetic algorithm for the job shop scheduling with a new local search using Monte Carlo method

This paper presents a methodology for applying scheduling algorithms using Monte Carlo simulation. The methodology is based on a decision support system (DSS). The proposed methodology combines a genetic algorithm with a new local search using Monte Carlo Method. The methodology is applied to the job shop scheduling problem (JSSP). The JSSP is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. The methodology is tested on a set of standard instances taken from the literature and compared with others. The computation results validate the effectiveness of the proposed methodology. The DSS developed can be utilized in a common industrial or construction environment.

Using NEXUS compliant debuggers for real time fault injection on microprocessors

As electronic devices get smaller and more complex, dependability assurance is becoming fundamental for many mission critical computer based systems. This paper presents a case study on the possibility of using the on-chip debug infrastructures present in most current microprocessors to execute real time fault injection campaigns. The proposed methodology is based on a debugger customized for fault injection and designed for maximum flexibility, and consists of injecting bit-flip type faults on memory elements without modifying or halting the target application. The debugger design is easily portable and applicable to different architectures, providing a flexible and efficient mechanism for verifying and validating fault tolerant components.

Using the TRAILER tool for managing informal learning in academic and professional contexts: the learner perspective

Informal Learning plays an important role in everyone's life and yet we often are unaware of it. The need to keep track of the knowledge acquired through informal learning is increasing as its sources become increasingly diverse. This paper presents a study on a tool developed to help keeping track of learners' informal learning, both within academic and professional contexts, This tool, developed within the European Commission funded TRAILER project, will further integrate the improvements suggested by users during the piloting phase. The two studied contexts were similar regarding the importance and perception of Informal Learning, but differed concerning tool usage. The overall idea of managing one's informal learning was well accepted and welcomed, which validated the emerging need for a tool with this purpose.

An optimization approach for the job shop scheduling problem

This paper presents an optimization approach for the job shop scheduling problem (JSSP). The JSSP is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. The proposed approach is based on a genetic algorithm technique. The scheduling rules such as SPT and MWKR are integrated into the process of genetic evolution. The chromosome representation of the problem is based on random keys. The schedules are constructed using a priority rule in which the priorities and delay times of the operations are defined by the genetic algorithm. Schedules are constructed using a procedure that generates parameterized active schedules. After a schedule is obtained a local search heuristic is applied to improve the solution. The approach is tested on a set of standard instances taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed approach.

Monitorização da satisfação profissional num ACES do Grande Porto

Este é um estudo de investigação realizado mediante pesquisa, de carácter exploratório-descritivo, cuja finalidade é verificar a satisfação dos profissionais que integram o ACES (Agrupamento de Centros de Saúde) do Serviço Nacional de Saúde. Com o Decreto-lei n.º 28/2008, de 22 de Fevereiro, são introduzidas alterações significativas das quais se destaca uma nova forma de gestão em saúde, considerando-se a componente humana (profissionais de saúde) como a melhor forma de incrementar o acesso dos cidadãos à prestação e serviço dos cuidados de saúde. Cabe ao conselho clínico do ACES a verificação do grau de satisfação dos profissionais (alínea g), art. 26.º, do DL 28/2008, de 22 de Fevereiro) face às mudanças nos serviços de saúde é ainda prematuro para os serviços dedicarem algum do seu tempo a está questão pelo que a investigadora pretende monitorizar a satisfação dos profissionais face a está reorganização que poderá servir de ferramenta para futuros planeamentos e gestão.