A Novel Approach for Elastic Query Processing in the Cloud

Cloud computing is a promising model of serviceoriented computing. One major advantage of cloud computing is its elasticity, i.e., the system's capability to supply and take away resources dynamically at runtime. For that, it's essential to design and implement a systematic and effective technique that takes complete advantage of the system's potential flexibility. This paper presents a non-invasive approach that monitors the performance of relational database management systems in cloud infrastructure, and dynamically makes choices to maximise the effectiveness of the provider's environment whereas still satisfying specified service level agreements" (SLAs)

Efficient adaptive query processing on large database systems available in the cloud environment

Tese de Doutoramento em InformáticaNowadays, many companies are migrating their applications and data to cloud service providers, mainly because of their ability to answer quickly to business requirements. Thereby, the performance is an important requirement for most customers when they wish to migrate their applications to the cloud. Therefore, in cloud environments, resources should be acquired and released automatically and quickly at runtime. Moreover, the users and service providers expect to get answers in time to ensure the service SLA (Service Level Agreement). Consequently, ensuring the QoS (Quality of Service) is a great challenge and it increases when we have large amounts of data to be manipulated in this environment. To resolve this kind of problems, several researches have been focused on shorter execution time using adaptive query processing and/or prediction of resources based on current system status. However, they present important limitations. For example, most of these works does not use monitoring during query execution and/or presents intrusive solutions, i.e. applied to the particular context. The aim of this thesis is the development of new solutions/strategies to efficient adaptive query processing on large databases available in a cloud environment. It must integrate adaptive re-optimization at query runtime and their costs are based on the SRT (Service Response Time – SLA QoS performance parameter). Finally, the proposed solution will be evaluated on large scale with large volume of data, machines and queries in a cloud computing infrastructure. Finally, this work also proposes a new model to estimate the SRT for different request types (database access requests). This model will allow the cloud service provider and its customers to establish an appropriate SLA relative to the expected performance of the services available in the cloud.Atualmente, muitas companhias têm migrado suas aplicações e dados para fornecedores de serviços em nuvem, pois um dos principais benefícios dessa tecnologia é a capacidade de responder rapidamente às necessidades do negócio. Assim, o desempenho é um dos mais importantes requisitos para a maioria dos clientes que desejam migrar suas aplicações para a nuvem. Em ambiente de nuvem, os recursos devem ser adquiridos e libertados automaticamente e rapidamente em tempo de execução. Além disso, os utilizadores e fornecedores de serviços esperam sempre garantir o contrato SLA (Acordo de Nível de Serviço). Consequentemente, garantir o QoS (Qualidade de Serviço) é um grande desafio, que se torna mais complexo quando existe uma grande quantidade de dados a serem manipulados neste ambiente. Para resolver estes tipos de problemas, diversas pesquisas têm sido realizadas focando o menor tempo de execução dos pedidos do utilizador na nuvem usando técnicas de processamento adaptativo de consultas e/ou utilizando técnicas de predição de recursos baseados no estado atual do sistema. Contudo, esses trabalhos apresentam limitações importantes. Por exemplo, a maioria desses trabalhos não utiliza monitorazação durante a execução da consulta e/ou apresenta soluções intrusivas, isto é, aplicadas a um contexto particular. Portanto, o objetivo desta tese consiste no desenvolvimento de uma nova solução/estratégia para o processamento eficiente (adaptativo) de consultas sobre grandes bases de dados disponíveis em ambiente de nuvem. Ela irá integrar técnicas de otimização adaptativas em tempo de execução da consulta e seus custos são baseados no SRT (Tempo de Resposta do Serviço – parâmetro QoS de desempenho do SLA). A solução proposta será avaliada em larga escala utilizando uma grande base de dados, máquinas e consultas em um ambiente real de computação na nuvem. Finalmente, este trabalho também propõe um novo modelo para estimar o SRT para diferentes tipos de pedidos (pedidos de acesso a banco de dados). Este modelo permitirá que um fornecedor de serviços em nuvem e seus clientes possam estabelecer um contrato SLA adequado, relativo ao desempenho esperado dos serviços disponíveis em nuvem

Service level agreement specification for IoT application workflow activity deployment, configuration and monitoring

PhD ThesisCurrently, we see the use of the Internet of Things (IoT) within various domains such as healthcare, smart homes, smart cars, smart-x applications, and smart cities. The number of applications based on IoT and cloud computing is projected to increase rapidly over the next few years. IoT-based services must meet the guaranteed levels of quality of service (QoS) to match users’ expectations. Ensuring QoS through specifying the QoS constraints using service level agreements (SLAs) is crucial. Also because of the potentially highly complex nature of multi-layered IoT applications, lifecycle management (deployment, dynamic reconfiguration, and monitoring) needs to be automated. To achieve this it is essential to be able to specify SLAs in a machine-readable format. currently available SLA specification languages are unable to accommodate the unique characteristics (interdependency of its multi-layers) of the IoT domain. Therefore, in this research, we propose a grammar for a syntactical structure of an SLA specification for IoT. The grammar is based on a proposed conceptual model that considers the main concepts that can be used to express the requirements for most common hardware and software components of an IoT application on an end-to-end basis. We follow the Goal Question Metric (GQM) approach to evaluate the generality and expressiveness of the proposed grammar by reviewing its concepts and their predefined lists of vocabularies against two use-cases with a number of participants whose research interests are mainly related to IoT. The results of the analysis show that the proposed grammar achieved 91.70% of its generality goal and 93.43% of its expressiveness goal. To enhance the process of specifying SLA terms, We then developed a toolkit for creating SLA specifications for IoT applications. The toolkit is used to simplify the process of capturing the requirements of IoT applications. We demonstrate the effectiveness of the toolkit using a remote health monitoring service (RHMS) use-case as well as applying a user experience measure to evaluate the tool by applying a questionnaire-oriented approach. We discussed the applicability of our tool by including it as a core component of two different applications: 1) a contextaware recommender system for IoT configuration across layers; and 2) a tool for automatically translating an SLA from JSON to a smart contract, deploying it on different peer nodes that represent the contractual parties. The smart contract is able to monitor the created SLA using Blockchain technology. These two applications are utilized within our proposed SLA management framework for IoT. Furthermore, we propose a greedy heuristic algorithm to decentralize workflow activities of an IoT application across Edge and Cloud resources to enhance response time, cost, energy consumption and network usage. We evaluated the efficiency of our proposed approach using iFogSim simulator. The performance analysis shows that the proposed algorithm minimized cost, execution time, networking, and Cloud energy consumption compared to Cloud-only and edge-ward placement approaches