QC 20100621

Thesis (Ph.D.) - Carleton University, 2007. / Includes bibliographical references (p. 229-243). Also available in electronic format on the Internet.

With the resource constrained nature of mobile devices and the resource abundant offerings of the cloud, several promising optimisation techniques have been proposed by the green computing research community. Prominent techniques and unique methods have been developed to offload resource/computation intensive tasks from mobile devices to the cloud. Most of the existing offloading techniques can only be applied to legacy mobile applications as they are motivated by existing systems. Consequently, they are realised with custom runtimes which incur overhead on the application. Moreover, existing approaches which can be applied to the software development phase, are difficult to implement (based on manual process) and also fall short of overall (mobile to cloud) efficiency in software qualityattributes or awareness of full-tier (mobile to cloud) implications. To address the above issues, the thesis proposes a model-driven architecturefor integration of software quality with green optimisation in Mobile Cloud Applications (MCAs), abbreviated as Mango architecture. The core aim of the architecture is to present an approach which easily integrates software quality attributes (SQAs) with the green optimisation objective of Mobile Cloud Computing (MCC). Also, as MCA is an application domain which spans through the mobile and cloud tiers; the Mango architecture, therefore, takesinto account the specification of SQAs across the mobile and cloud tiers, for overall efficiency. Furthermore, as a model-driven architecture, models can be built for computation intensive tasks and their SQAs, which in turn drives the development – for development efficiency. Thus, a modelling framework (called Mosaic) and a full-tier test framework (called Beftigre) were proposed to automate the architecture derivation and demonstrate the efficiency of Mango approach. By use of real world scenarios/applications, Mango has been demonstrated to enhance the MCA development process while achieving overall efficiency in terms of SQAs (including mobile performance and energy usage compared to existing counterparts).

Submitted by Nayara Passos (nayara.passos@ufpe.br) on 2015-03-10T13:51:24Z No. of bitstreams: 2 DISSERTAÇÃO Jean Carlos de Carvalho Melo.pdf: 1961390 bytes, checksum: d66fd564809f98e0c5bd50687923f9e0 (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) / Made available in DSpace on 2015-03-10T13:51:24Z (GMT). No. of bitstreams: 2 DISSERTAÇÃO Jean Carlos de Carvalho Melo.pdf: 1961390 bytes, checksum: d66fd564809f98e0c5bd50687923f9e0 (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Previous issue date: 2014 / INES, CNPq / Diante do ambiente complexo e dinâmico encontrado nas empresas atualmente, o sistema tradicional de Workflow não está sendo flexível suficiente para modelar Processos de Negócio. Nesse contexto, surgiram os Processos Flexíveis que tem por principal objetivo suprir a necessidade de modelar processos menos estáticos. Processo declarativo é um tipo de processo flexível que permite os participantes decidirem a ordem em que as atividades são executadas através de regras de negócio. As regras de negócio determinam as restrições e obrigações que devem ser satisfeitas durante a execução. Tais regras descrevem o que deve ou não deve ser feito durante a execução do processo, mas não definem como. Os métodos e ferramentas atualmente disponíveis para modelar e executar processos declarativos apresentam várias limitações que prejudicam a sua utilização para este fim. Em particular, a abordagem que emprega lógica temporal linear (LTL) sofre do problema de explosão de estados a medida que o tamanho do modelo do processo cresce. Embora mecanismos eficientes em relação a memória terem surgido, eles não são capazes de adequadamente garantir a conclusão correta do processo, uma vez que permitem o usuário alcançar estados proibidos ou que causem deadlock. Além disso, as implementações atuais de ferramentas para execução de processos declarativos se concentram apenas em atividades manuais. Comunicação automática com aplicações externas para troca de dados e reutilização de funcionalidade não é suportado. Essas oportunidades de automação poderiam ser melhor exploradas por uma engine declarativa que se integra com tecnologias SOC existentes. Este trabalho propõe uma nova engine de regras baseada em grafo, chamado de REFlex. Tal engine não compartilha os problemas apresentados pelas abordagens disponíveis, sendo mais adequada para modelar processos de negócio declarativos. Além disso, REFlex preenche a lacuna entre os processos declarativos e SOC. O orquestrador REFlex é um orquestrador de serviços declarativo, eficiente e dependente de dados. Ele permite que os participantes chamem serviços externos para executar tarefas automatizadas. Diferente dos trabalhos relacionados, o algoritmo de REFlex não depende da geração de todos os estados alcançáveis, o que o torna adequado para modelar processos de negócios grandes e complexos. Além disso, REFlex suporta regras de negócio dependentes de dados, o que proporciona sensibilidade ao contexto. / Declarative business process modeling is a flexible approach to business process management in which participants can decide the order in which activities are performed. Business rules are employed to determine restrictions and obligations that must be satisfied during execution time. Such business rules describe what must or must not be done during the process execution, but do not prescribe how. In this way, complex control-flows are simplified and participants have more flexibility to handle unpredicted situations. The methods and tools currently available to model and execute declarative processes present several limitations that impair their use to this application. In particular, the well-known approach that employs Linear Temporal Logic (LTL) has the drawback of the state space explosion as the size of the process model grows. Although approaches proposing memory efficient methods have been proposed in the literature, they are not able to properly guarantee the correct termination of the process, since they allow the user to reach deadlock states. Moreover, current implementations of declarative business process engines focus only on manual activities. Automatic communication with external applications to exchange data and reuse functionality is barely supported. Such automation opportunities could be better exploited by a declarative engine that integrates with existing SOC technologies. This work proposes a novel graph-based rule engine called REFlex that does not share the problems presented by other engines, being better suited to model declarative business processes than the techniques currently in use. Additionally, such engine fills this gap between declarative processes and SOC. The REFlex orchestrator is an efficient, data-aware declarative web services orchestrator. It enables participants to call external web services to perform automated tasks. Different from related work, the REFlex algorithm does not depend on the generation of all reachable states, which makes it well suited to model large and complex business processes. Moreover, REFlex is capable of modeling data-dependent business rules, which provides unprecedented context awareness and modeling power to the declarative paradigm.

<p>Pervasive cameras are generating videos at an unprecedented pace, making videos the new frontier of big data. As the processors, e.g., CPU/GPU, become increasingly powerful, the cloud and edge nodes can generate useful insights from colossal video data. However, as the research in computer vision (CV) develops vigorously, the system area has been a blind spot in CV research. With colossal video data generated from cameras every day and limited compute resource budgets, how to design software systems to generate insights from video data efficiently?</p><p><br></p><p>Designing cost-efficient video analytics software systems is challenged by the expensive computation of vision operators, the colossal data volume, and the precious wireless bandwidth of surveillance cameras. To address above challenges, three software systems are proposed in this thesis. For the first system, we present VStore, a data store that supports fast, resource-efficient analytics over large archival videos. VStore manages video ingestion, storage, retrieval, and consumption and controls video formats through backward derivation of configuration: in the opposite direction along the video data path, VStore passes the video quantity and quality expected by analytics backward to retrieval, to storage, and to ingestion. VStore derives an optimal set of video formats, optimizes for different resources in a progressive manner, and runs queries as fast as 362x of video realtime. For the second system, we present a camera/cloud runtime called DIVA that supports querying cold videos distributed on low-cost wireless cameras. DIVA is built upon a novel zero-streaming paradigm: to save wireless bandwidth, when capturing video frames, a camera builds sparse yet accurate landmark frames without uploading any video data; when executing a query, a camera processes frames in multiple passes with increasingly more expensive operators. On diverse queries over 15 videos, DIVA runs at more than 100x realtime and outperforms competitive alternatives remarkably. For the third system, we present Clique, a practical object re-identification (ReID) engine that builds upon two unconventional techniques. First, Clique assesses target occurrences by clustering unreliable object features extracted by ReID algorithms, with each cluster representing the general impression of a distinct object to be matched against the input. Second, to search across camera videos, Clique samples cameras to maximize the spatiotemporal coverage and incrementally adds cameras for processing on demand. Through evaluation on 25 hours of traffic videos from 25 cameras, Clique reaches a high recall at 5 of 0.87 across 70 queries and runs at 830x of video realtime in achieving high accuracy.</p>

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Software systems are frequently designed using abstractions that make software verification tractable. Specifically, by choosing meaningful, formal abstractions for interfaces and then designing according to those interfaces, one can verify entire systems according to behavioral predicates. While impractical for systems in general, framework-based software architectures are a type of system for which formal analysis can be beneficial and practical over the life of the system. We present a method to formally analyze behavioral properties of framework-based software with higher-order logic and then demonstrate its utility for a significant, modern system.

Laws and regulation affect software development, as they frequently demand changes in software’ requirements to protect individuals and businesses regarding security, privacy, governance, sustainability and more. Legal requirements can dictate new requirements or constrain existing ones. The problem of software compliance is howto ensure that the software complies with the norms that the legislation imposes. The problem is particularly challenging because it combines difficultsteps: 1)analyze legal documents, 2) extract requirements from those documents, 3) identify conflicting requirements with those already implemented in software and 4) ensure that software remains compliant even with the changes. Compliance is a continuous process: laws, software and the context within which software system operates changes continuously. The works dealing with the compliance problem focus only on one or two subjects: analyze legal documents or extract requirements or identify conflicts or changes. This thesis deals with all the problems at the same time; the idea is to extract requirements from legal text, compare them with the software requirement, resolve the possible conflicts that may arise, continuously leading with the changes on environment, laws and requirements. For this, this work proposes a framework that is composed of a compliance process and continuous monitoring of environmental changes. The framework deals with different types of laws (security, privacy, transparency, health care) that are represented in explicit norms. The compliance process supports the identification, extraction, comparison and conflict resolution to help software compliance, by producing a compliant set of requirements. The compliance process is based on the semantic annotation and goal model. The semantic annotation helps to extract requirements from thelaw, using patterns. The goal model is used to help the comparison between requirement and to represent requirements in a formal and consistent requirement specification. The process is tool supported; some tools were reused (Desiree and NomosT) to further each step. It was necessary to adapt the tools for the context of the compliance process, creating a guideline, patterns, and heuristics. The continuous monitoring is concerned about the changes that affect the software compliance and has 7 the mechanism to ensure that even with those changes the software will regain compliance. The compliance monitor is basedon agents and Non Functional Requirements. The agents are represented using in i*, the idea is to showthe collaboration between the agents to ensure the continuous compliance. The requirement specification of how each agent should behave was also generated using Business Process Modeling Notation and Desiree language. The Non Functional Requirements catalogue is used to help to define operalizations for the software awareness. The framework validation was made in two parts: first, the compliance process and after all the framework proposed. For the compliance process, the effort and correctness were measured comparing the use of the proposed process andan ad-hoc method. For the entire framework, the example of monitoring the changes in the environment when an automated car is crossing the border between Washington and Canada was used. The study shows that context has a strong influence on the software requirements, and nonconformity problems may incur penalties. The contribution of this work is the Eunomia framework that has a process and goal model perspective with emphasis on monitoring that helps to deal with the compliance challenge. The framework equips the requirements engineering team with a systematic method. Eunomia framework is a tool-supported and systematic process which can be reused to reduce the time effort and to improve the quality of the requirement specification that helps to create a compliant software requirement specification that is compliant over the time.

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