Arquitetura baseada em multiagentes georreferenciados para Sistemas de Vigilância

Desde sempre houve uma preocupação das pessoas com a segurança, quer com a sua vida, quer com a dos seus bens. Esta preocupação, levou a que ao longo do tempo fossem desenvolvidos sistemas de vigilância que ajudam a aler-tar para eventuais perigos. Estes sistemas têm vindo a evoluir ao longo do tem-po, no entanto, ainda existem aspetos em que podem ser melhorados, tais co-mo: a Cooperação entre humanos e os dispositivos de vigilância; a Descentrali-zação dos Sistemas; a Fusão da informação sensorial; ou a Reconfiguração e Di-namismo dos sistemas. Tendo em conta estas lacunas, neste trabalho é proposta uma arquitetura de Sistemas Inteligentes de Vigilância baseada em agentes de Software georre-ferenciados, com vista a aumentar a cooperação entre humanos e sensores. Esta arquitetura pretende melhorar o desempenho global dos sistemas de vigilância atuais utilizando a localização dos recursos humanos e a localização dos even-tos, para melhorar os tempos de resposta a eventos. Com base na arquitetura proposta, foi desenvolvido um sistema que per-mitiu testar a solução proposta. Os resultados obtidos através dos vários testes efetuados, permitiram comprovar que, entre outras melhorias, a arquitetura proposta permite uma redução nos tempos de resposta aos eventos

Runtime Management of Multiprocessor Systems for Fault Tolerance, Energy Efficiency and Load Balancing

Efficiency of modern multiprocessor systems is hurt by unpredictable events: aging causes permanent faults that disable components; application spawnings and terminations taking place at arbitrary times, affect energy proportionality, causing energy waste; load imbalances reduce resource utilization, penalizing performance. This thesis demonstrates how runtime management can mitigate the negative effects of unpredictable events, making decisions guided by a combination of static information known in advance and parameters that only become known at runtime. We propose techniques for three different objectives: graceful degradation of aging-prone systems; energy efficiency of heterogeneous adaptive systems; and load balancing by means of work stealing. Managing aging-prone systems for graceful efficiency degradation, is based on a high-level system description that encapsulates hardware reconfigurability and workload flexibility and allows to quantify system efficiency and use it as an objective function. Different custom heuristics, as well as simulated annealing and a genetic algorithm are proposed to optimize this objective function as a response to component failures. Custom heuristics are one to two orders of magnitude faster, provide better efficiency for the first 20% of system lifetime and are less than 13% worse than a genetic algorithm at the end of this lifetime. Custom heuristics occasionally fail to satisfy reconfiguration cost constraints. As all algorithms\u27 execution time scales well with respect to system size, a genetic algorithm can be used as backup in these cases. Managing heterogeneous multiprocessors capable of Dynamic Voltage and Frequency Scaling is based on a model that accurately predicts performance and power: performance is predicted by combining static, application-specific profiling information and dynamic, runtime performance monitoring data; power is predicted using the aforementioned performance estimations and a set of platform-specific, static parameters, determined only once and used for every application mix. Three runtime heuristics are proposed, that make use of this model to perform partial search of the configuration space, evaluating a small set of configurations and selecting the best one. When best-effort performance is adequate, the proposed approach achieves 3% higher energy efficiency compared to the powersave governor and 2x better compared to the interactive and ondemand governors. When individual applications\u27 performance requirements are considered, the proposed approach is able to satisfy them, giving away 18% of system\u27s energy efficiency compared to the powersave, which however misses the performance targets by 23%; at the same time, the proposed approach maintains an efficiency advantage of about 55% compared to the other governors, which also satisfy the requirements. Lastly, to improve load balancing of multiprocessors, a partial and approximate view of the current load distribution among system cores is proposed, which consists of lightweight data structures and is maintained by each core through cheap operations. A runtime algorithm is developed, using this view whenever a core becomes idle, to perform victim core selection for work stealing, also considering system topology and memory hierarchy. Among 12 diverse imbalanced workloads, the proposed approach achieves better performance than random, hierarchical and local stealing for six workloads. Furthermore, it is at most 8% slower among the other six workloads, while competing strategies incur a penalty of at least 89% on some workload

Contribution à l'ordonnancement post-pronostic de plates-formes hétérogènes et distribuées : approches discrète et continue.

This thesis addresses the problem of maximizing the production horizon of a heterogeneousdistributed platform composed of parallel machines and which has to provide a global productionservice. Each machine is supposed to be able to provide several throughputs corresponding todifferent operating conditions. It is assumed that using a machine with degraded performancescompared to nominal ones allows to extend its useful life before maintenance. The study fallswithin the decisional step of PHM (Prognostics and Health Management), in which a prognosticsphase allows to determine remaining useful lives of machines. The optimization problem consistsin determining the set of machines to use at each time and a running profile for each of them so asto maximize the production horizon before maintenance. Machines running profiles are definedon the basis of two models. First one depicts the behavior of machines used with a discretenumber of performances. For this case, the problem complexity is first studied considering manyvariants of the optimization problem. Several optimal and sub-optimal resolution methods areproposed to deal with the scheduling problem. Several sub-optimal resolution methods are thenproposed for the second model, which applies to machines whose throughput rate can varycontinuously between two bounds. These research works allow to determine the time beforefailure of a system on the basis of its components remaining useful lives.Cette thèse propose une approche originale d’ordonnancement de la production de plates-formesde machines hétérogènes et distribuées, utilisées en parallèle pour fournir un service globalcommun. L’originalité de la contribution réside dans la proposition de modifier les conditionsopératoires des machines au cours de leur utilisation. Il est supposé qu’utiliser une machine avecdes performances dégradées par rapport à un fonctionnement nominal permet d’allonger sa duréede vie avant maintenance. L’étude s’inscrit dans la partie décisionnelle du PHM (Prognostics andHealth Management), au sein duquel une étape de pronostic permet de déterminer les durées devie résiduelles des machines. Le problème d’optimisation consiste à déterminer à chaque instantl’ensemble des machines à utiliser et un profil de fonctionnement pour chacune d’entre ellesde manière à maximiser l’horizon de production de la plate-forme avant maintenance. Deuxmodèles sont proposés pour la définition des profils de fonctionnement. Le premier traduit lecomportement à l’usure de machines pouvant fournir un nombre discret de performances. Pource cas, la complexité de plusieurs variantes du problème d’optimisation est étudiée et plusieursméthodes de résolution optimales et sous-optimales sont proposées pour traiter le problèmed’ordonnancement. Plusieurs méthodes de résolution sous-optimales sont ensuite proposées pourle second modèle, qui s’applique à des machines dont le débit peut varier de manière continueentre deux bornes. Ces travaux permettent de déterminer la durée maximale d’utilisation avantdéfaillance d’un système à partir des durées de vie résiduelles des équipements qui le composent