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Time Sensitive Networking (TSN) is a standard that extends Ethernet, providing deterministic guarantees to internal communications. The standard is finding use in many different fields such as modern cars whose networks are getting increasingly complex. One problem with TSN is the NP-hard problem of scheduling network flows, the process in which schedules are made to ensure that network flows demanding real-time guarantees have their requirements met.The goal of thesis is to implement two different scheduling algorithms. The evaluation of the implementations measure how they perform in regards to finding possible schedules and for how much time they take with an increasing number of network flows to schedule. The algorithms approaches to scheduling are then discussed and judged in comparison with the results. This thesis implements two different algorithms, a fine-grained algorithm and a coarse-grained algorithm. The difference between the algorithms lie in how fine-grained their scheduling is. Where the fine-grained algorithm adopts the lowest resolution permissible, the coarse-grained algorithm achieves the highest resolution possible in the schedule. The results show that the coarse-grained algorithm becomes unacceptably slow because of its fine-grained scheduling. In a scenario where algorithms 1 and 2 work with the same flows, the coarse-grained algorithm is 42x slower than the fine-grained algorithm in the worst case.The conclusion is that the finest possible scheduling is not a feasible approach because of it taking too much time to execute for a very small amount of flows. / Time Sensitive Networking (TSN) är en standard som utökar Ethernet genom att lägga till deterministiska garantier till intern kommunikation. Standarden har börjat användas inom fält såsom moderna bilar vars nätverk blir allt mer komplexa. Ett problem med TSN är det NP-hard svåra problemet med att schemalägga nätverksflöden, processen i vilket scheman uträknas för att garantera att nätverksflöden som kräver realtidsgarantier får sina krav uppfyllda. Uppsatsens mål är att implementera två olika schemaläggningsalgoritmer. Evalueringstesterna mäter algoritmernas förmåga att finna möjliga scheman för olika mängder av nätverksflöden och hur lång tid det tar.Algoritmernas tillvägagångssätt för schemaläggning jämförs och bedöms därefter.Denna uppsats implementerar två olika algorithmer, en finkorning algorithm och en grovkornig algoritm. Namnen kommer från finkornigheten i algoritmernas schemaläggning. Den finkorniga algoritmen schemalägger med finkornighet och den grovkorniga algoritmen schemalägger med grovkornighet. Resultatet från testerna och evalueringen visar att när algoritmerna schemalägger samma flöden tar den grovkorniga algoritmen som värst 42 gånger mer tid att slutföra sina beräkningar. Slutsatsen är att finkorning schemaläggning är inte applicerbar då det tar för lång tid att utföra för en väldigt liten mängd flöden.

Edge computing is a distributed computing paradigm where computing resources are located physically closer to the data source compared to the traditional cloud computing paradigm. Edge computing enables computation offloading from resource-constrained devices to more powerful servers in the edge and cloud. To offer edge and cloud support to real-time industrial applications, the communication to the servers and the server-side computation needs to be predictable. However, the predictability of offloading cannot be guaranteed in an environment where multiple devices are competing for the same edge and cloud resources due to potential server-side scheduling conflicts. To the best or our knowledge, no offloading scheme has been proposed that provides a highly predictable real-time task scheduling in the face of multiple devices offloading to a set of heterogeneous edge/cloud servers. Hence, this thesis approaches the problem of predictable offloading in real-time environments by proposing a centralized server time reservation system to schedule the offloading of real-time tasks to edge and cloud servers. Our reservation system allows end-devices to request external execution time in advance for real-time tasks that will be generated in the future, therefore when such a task is created, it already has a designated offloading server that guarantees its timely execution. Furthermore, this centralized reservation system is capable of optimizing the reservation scheduling strategy with the goal of minimizing energy consumption of edge servers while meeting the stringent deadline constraints of real-time applications. / Edge computing är ett distribuerat datorparadigm där datorresurser är fysiskt placerade närmare datakällan jämfört med det traditionella molnberäkningsparadigmet. Edge computing möjliggör beräkningsavlastning från resursbegränsade enheter till mer kraftfulla servrar i kanten och molnet. För att erbjuda kant- och molnstöd till industriella tillämpningar i realtid måste kommunikationen till servrarna och beräkningen på serversidan vara förutsägbar. Förutsägbarheten av avlastning kan dock inte garanteras i en miljö där flera enheter konkurrerar om samma kant- och molnresurser på grund av potentiella schemaläggningskonflikter på serversidan. Så vitt vi vet har inget avlastningsschema föreslagits som ger en mycket förutsägbar uppgiftsschemaläggning i realtid inför flera enheter som laddas av till en uppsättning heterogena edge-/molnservrar. Därför närmar sig denna avhandling problemet med förutsägbar avlastning i realtidsmiljöer genom att föreslå ett centraliserat servertidsreservationssystem för att schemalägga avlastningen av realtidsuppgifter till edge- och molnservrar. Vårt reservationssystem tillåter slutenheter att begära extern exekveringstid i förväg för realtidsuppgifter som kommer att genereras i framtiden, därför när en sådan uppgift skapas har den redan en utsedd avlastningsserver som garanterar att den utförs i tid. Dessutom kan detta centraliserade bokningssystem optimera bokningsschemaläggningsstrategin med målet att minimera energiförbrukningen för edge-servrar samtidigt som de stränga deadline-begränsningarna för realtidsapplikationer uppfylls.

A Computação em Nuvem é um paradigma de computação distribuída que vem sendo utilizado extensivamente em vários campos de interesse nos últimos anos, desde aplicações web comuns até a aplicações de alta-performance computacional. O modelo de pagamento pelo uso e a isonomia dos métodos de acesso transformaram o ambiente de Computação em Nuvem em uma alternativa extremamente popular e atrativa tanto para universidades como para empresas privadas. Entre os modelos de implantação adotados atualmente destaca-se o de nuvem em comunidade, onde várias entidades que possuem interesses em comum constroem, mantém e compartilham a mesma infraestrutura de serviços em nuvem. O modelo computacional em nuvem também pode ser atrativo para aplicações que tenham como requisito o processamento em tempo real, principalmente pela capacidade de manipulação de grandes volumes de dados e pela propriedade de elasticidade, que é a inserção ou remoção de recursos computacionais dinamicamente de acordo com a demanda. Nesta tese, são identificados os requisitos para a construção de um ambiente em nuvem em comunidade para aplicações de tempo real. A partir destes requisitos e de uma revisão bibliográfica baseada em nuvem e sistemas distribuídos de tempo real, é desenvolvida a proposta de uma arquitetura de nuvem em comunidade de tempo real. Um estudo de caso de compra e venda de ações em bolsa de valores é apresentado como uma aplicação viável para este modelo, sendo que um algoritmo de escalonamento de tempo real para este ambiente é proposto. Por fim, é desenvolvido nesta tese um simulador cujo objetivo é demonstrar em termos quantitativos quais as melhorias de desempenho atingidas com esta arquitetura. / Cloud Computing is a distributed computing paradigm which is being extensively applied to many fields of interest in the last few years, ranging from ordinary web applications to highperformance computing. The pay-per-use model and ubiquitous access methods have made Cloud Computing an interesting and popular alternative for both enterprises and universities. Among the deployment models adopted, one of the most prominent is the community cloud, where several entities who share similar interests build, maintain and use the same infrastructure of cloud services. The cloud computing paradigm can be attractive to applications whose requirements are the processing in real-time too, mainly because of its capacity of handling huge amounts of data as for the property of elasticity, which is the dynamic and automatic insertion or removal of computing resources on-demand. In this thesis, the requirements of a community cloud for real-time applications are identified. Based on these requirements and on a bibliographical review of the research fields of real-time distributed systems and real-time clouds, it is developed a proposal for a real-time community cloud architecture. A case study of a trading real-time application at a stock exchange is presented as a feasible application for this model. Also, a real-time scheduling algorithm is proposed for this environment. A simulator is built in order to demonstrate the quantitative improvements this architecture brings.

A Computação em Nuvem é um paradigma de computação distribuída que vem sendo utilizado extensivamente em vários campos de interesse nos últimos anos, desde aplicações web comuns até a aplicações de alta-performance computacional. O modelo de pagamento pelo uso e a isonomia dos métodos de acesso transformaram o ambiente de Computação em Nuvem em uma alternativa extremamente popular e atrativa tanto para universidades como para empresas privadas. Entre os modelos de implantação adotados atualmente destaca-se o de nuvem em comunidade, onde várias entidades que possuem interesses em comum constroem, mantém e compartilham a mesma infraestrutura de serviços em nuvem. O modelo computacional em nuvem também pode ser atrativo para aplicações que tenham como requisito o processamento em tempo real, principalmente pela capacidade de manipulação de grandes volumes de dados e pela propriedade de elasticidade, que é a inserção ou remoção de recursos computacionais dinamicamente de acordo com a demanda. Nesta tese, são identificados os requisitos para a construção de um ambiente em nuvem em comunidade para aplicações de tempo real. A partir destes requisitos e de uma revisão bibliográfica baseada em nuvem e sistemas distribuídos de tempo real, é desenvolvida a proposta de uma arquitetura de nuvem em comunidade de tempo real. Um estudo de caso de compra e venda de ações em bolsa de valores é apresentado como uma aplicação viável para este modelo, sendo que um algoritmo de escalonamento de tempo real para este ambiente é proposto. Por fim, é desenvolvido nesta tese um simulador cujo objetivo é demonstrar em termos quantitativos quais as melhorias de desempenho atingidas com esta arquitetura. / Cloud Computing is a distributed computing paradigm which is being extensively applied to many fields of interest in the last few years, ranging from ordinary web applications to highperformance computing. The pay-per-use model and ubiquitous access methods have made Cloud Computing an interesting and popular alternative for both enterprises and universities. Among the deployment models adopted, one of the most prominent is the community cloud, where several entities who share similar interests build, maintain and use the same infrastructure of cloud services. The cloud computing paradigm can be attractive to applications whose requirements are the processing in real-time too, mainly because of its capacity of handling huge amounts of data as for the property of elasticity, which is the dynamic and automatic insertion or removal of computing resources on-demand. In this thesis, the requirements of a community cloud for real-time applications are identified. Based on these requirements and on a bibliographical review of the research fields of real-time distributed systems and real-time clouds, it is developed a proposal for a real-time community cloud architecture. A case study of a trading real-time application at a stock exchange is presented as a feasible application for this model. Also, a real-time scheduling algorithm is proposed for this environment. A simulator is built in order to demonstrate the quantitative improvements this architecture brings.

[Truncated abstract] The accelerating pace of convergence of communications from disparate application types onto common packet networks has made quality of service an increasingly important and problematic issue. Applications of different classes have diverse service requirements at distinct levels of importance. Also, these applications offer traffic to the network with widely variant characteristics. Yet a common network is expected at all times to meet the individual communication requirements of each flow from all of these application types. One group of applications that has particularly critical service requirements is the class of real-time applications, such as packet telephony. They require both the reproduction of a specified timing sequence at the destination, and nearly instantaneous interaction between the users at the endpoints. The associated delay limits (in terms of upper bound and variation) must be consistently met; at every point where these are violated, the network transfer becomes worthless, as the data cannot be used at all. In contrast, other types of applications may suffer appreciable deterioration in quality of service as a result of slower transfer, but the goal of the transfer can still largely be met. The goal of this thesis is to evaluate the potential effectiveness of a class of packet scheduling algorithms in meeting the specific service requirements of real-time applications in a converged network environment. Since the proposal of Weighted Fair Queueing, there have been several schedulers suggested to be capable of meeting the divergent service requirements of both real-time and other data applications. ... This simulation study also sheds light on false assumptions that can be made about the isolation produced by start-time and finish-time schedulers based on the deterministic bounds obtained. The key contributions of this work are as follows. We clearly show how the definition of the virtual time function affects both delay bounds and delay distributions for a real-time flow in a converged network, and how optimality is achieved. Despite apparent indications to the contrary from delay bounds, the simulation analysis demonstrates that start-time rate-based schedulers possess useful characteristics for real-time flows that the traditional finish-time schedulers do not. Finally, it is shown that all the virtual time rate-based schedulers considered can produce isolation problems over multiple hops in networks with high loading. It becomes apparent that the benchmark First-Come-First-Served scheduler, with spacing and call admission control at the network ingresses, is a preferred arrangement for real-time flows (although lower priority levels would also need to be implemented for dealing with other data flows).

The Quality of Service (QoS) routing approach is gaining an increasing interest in the Internet community due to the new emerging Internet applications such as real-time multimedia applications. These applications require better levels of quality of services than those supported by best effort networks. Therefore providing such services is crucial to many real time and multimedia applications which have strict quality of service requirements regarding bandwidth and timeliness of delivery. QoS routing is a major component in any QoS architecture and thus has been studied extensively in the literature. Scalability is considered one of the major issues in designing efficient QoS routing algorithms due to the high cost of QoS routing both in terms of computational effort and communication overhead. Localized quality of service routing is a promising approach to overcome the scalability problem of the conventional quality of service routing approach. The localized quality of service approach eliminates the communication overhead because it does not need the global network state information. The main aim of this thesis is to contribute towards the localised routing area by proposing and developing some new models and algorithms. Toward this goal we make the following major contributions. First, a scalable and efficient QoS routing algorithm based on a localised approach to QoS routing has been developed and evaluated. Second, we have developed a path selection technique that can be used with existing localized QoS routing algorithms to enhance their scalability and performance. Third, a scalable and efficient hierarchical QoS routing algorithm based on a localised approach to QoS routing has been developed and evaluated.

L'étude des Systèmes Contrôlés en Réseaux (SCR) repose sur l'identification des exigences de fonctionnement de l'application appelées Qualité de Contrôle (QdC) et sur l'évaluation de la Qualité de Service (QdS) offerte par le réseau. Les travaux sur les SCR se repartissent selon deux approches : la commande en réseau et la commande de réseau. Cette thèse se positionne sur la deuxième approche avec une recherche axée sur la modélisation des mécanismes d'ordonnancement implémentés dans les équipements réseau et notamment dans les commutateurs Ethernet qui sont de plus en plus utilisés dans les applications industrielles. Ce travail de recherche étudie plus particulièrement comme paramètre de QdS, les délais qui engendrent des perturbations sur le système commandé. Cette thèse propose deux modèles de classification de service reposant sur des ordonnanceurs WRR (Weighted Round Robin). La première modélisation suit une approche constructive en utilisant la théorie du calcul réseau. La seconde s'appuie sur une phase d'identification à partir de simulations numériques et de la logique floue. Dans les deux cas, le but est d'offrir une bande passante suffisante pour le trafic contraint temporellement tout en maximisant la bande passante dédiée aux autres trafics pour éviter des effets famine. L'approche calcul réseau permet de configurer le réseau hors-ligne pour répondre à des contraintes temporelles strictes du SCR. La solution basée sur la logique floue autorise une commande dynamique de l'ordonnanceur pour ajuster en ligne le réseau en fonction des variations du trafic. Elle ne peut s'appliquer qu'à des SCR ayant des contraintes de temps souples / The study of the Networked Control Systems (NCS) is based both on the identification of the application functioning requirements called Quality of Control (QoC) and on the evaluation of the Quality of Service (QoS) offered by the network. The studies on the NCS are classified according to two approaches: the control over network and the control of network. This thesis addresses the second approach and models the scheduling mechanisms implemented in the Ethernet switches that are more and more used in the industrial applications. The specific QoS parameter studied in this thesis is the delay disturbing the controlled system. This thesis proposes two models of classification of service based on WRR (Weighted Round Robin) schedulers. The first modeling follows a constructive approach by using the network calculus theory. The second is based on an identification step from numerical simulations and from the fuzzy logic. In the two cases, the purpose is both to offer enough bandwidth for the time constrained traffic and to maximize the bandwidth dedicated to the others traffics to avoid famine effects. The network calculus approach is used to configure off-line the network in respecting the NCS strict time constraints. The solution based on the fuzzy logic enables a dynamic control of the scheduler in order to tune on-line the network according to the traffic variations. This latter can be applied only to NCS with soft time constraints

<p>The problem of estimating an adequate level of detail for an object for a specific view is one of the important problems in computer 3d-graphics and is especially important in real-time applications. The well-known continuous level-of-detail technique, Real-time Optimally Adapting Meshes (ROAM), has been employed with success for almost 10 years but has at present, due to rapid development of graphics hardware, been found to be inadequate. Compared to many other level-of-detail techniques it cannot benefit from the higher triangle throughput available on graphics cards of today.</p><p>This thesis will describe the implementation of the new version of ROAM (informally known as ROAM 2.0) for the purpose of massive planetary data visualization. It will show how the problems of the old technique can be bridged to be able to adapt to newer graphics card while still benefiting from the advantages of ROAM. The resulting implementation that is presented here is specialized on spherical objects and handles both texture and geometry data of arbitrary large sizes in an efficient way.</p>