A model-driven approach to broaden the detection of software performance antipatterns at runtime

Performance antipatterns document bad design patterns that have negative influence on system performance. In our previous work we formalized such antipatterns as logical predicates that predicate on four views: (i) the static view that captures the software elements (e.g. classes, components) and the static relationships among them; (ii) the dynamic view that represents the interaction (e.g. messages) that occurs between the software entities elements to provide the system functionalities; (iii) the deployment view that describes the hardware elements (e.g. processing nodes) and the mapping of the software entities onto the hardware platform; (iv) the performance view that collects specific performance indices. In this paper we present a lightweight infrastructure that is able to detect performance antipatterns at runtime through monitoring. The proposed approach precalculates such predicates and identifies antipatterns whose static, dynamic and deployment sub-predicates are validated by the current system configuration and brings at runtime the verification of performance sub-predicates. The proposed infrastructure leverages model-driven techniques to generate probes for monitoring the performance sub-predicates and detecting antipatterns at runtime.Comment: In Proceedings FESCA 2014, arXiv:1404.043

Integrating an agent-based wireless sensor network within an existing multi-agent condition monitoring system

The use of wireless sensor networks for condition monitoring is gaining ground across all sectors of industry, and while their use for power engineering applications has yet been limited, they represent a viable platform for next-generation substation condition monitoring systems. For engineers to fully benefit from this new approach to condition monitoring, new sensor data must be incorporated into a single integrated system. This paper proposes the integration of an agent-based wireless sensor network with an existing agent-based condition monitoring system. It demonstrates that multi-agent systems can be extended down to the sensor level while considering the reduced energy availability of low-power embedded devices. A novel agent-based approach to data translation is presented, which is demonstrated through two case studies: a lab-based temperature and vibration monitoring system, and a proposal to integrate a wireless sensor network to an existing technology demonstrator deployed in a substation in the UK

Analysis of SLA compliance in the cloud: An automated, model-based approach

Service Level Agreements (SLA) are commonly used to specify the quality attributes between cloud service providers and the customers. A violation of SLAs can result in high penalties. To allow the analysis of SLA compliance before the services are deployed, we describe in this paper an approach for SLA-aware deployment of services on the cloud, and illustrate its workflow by means of a case study. The approach is based on formal models combined with static analysis tools and generated runtime monitors. As such, it fits well within a methodology combining software development with information technology operations (DevOps)

Sistema de teste auto-adaptativo baseado em modelo para SOA dinâmico

Orientadores: Eliane Martins, Andrea CeccarelliDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Arquitetura orientada a serviços (SOA) é um padrão de design popular para implemen- tação de serviços web devido à interoperabilidade, escalabilidade e reuso de soluções de software que promove. Os serviços que usam essa arquitetura precisam operar em um am- biente altamente dinâmico, entretanto quanto mais a complexidade desses serviços cresce menos os métodos tradicionais de validação se mostram viáveis. Aplicações baseadas em arquitetura orientada a serviços podem evoluir e mudar du- rante a execução. Por conta disso testes offline não asseguram completamente o compor- tamento correto de um sistema em tempo de execução. Por essa razão, a necessidade de tecnicas diferentes para validar o comportamento adequado de uma aplicação SOA durante o seu ciclo de vida são necessárias, por isso testes online executados durante o funcionamento serão usados nesse projeto. O objetivo do projeto é de aplicar técnicas de testes baseados em modelos para gerar e executar casos de testes relevantes em aplicações SOA durante seu tempo de execu- ção. Para alcançar esse objetivo uma estrura de teste online autoadaptativa baseada em modelos foi idealizada. Testes baseados em modelos podem ser gerados de maneira offline ou online. Nos testes offline, os casos de teste são gerados antes do sistema entrar em execução. Já nos testes online, os casos de teste são gerados e aplicados concomitantemente, e as saídas produzidas pela aplicação em teste definem o próximo passo a ser realizado. Quando uma evolução é detectada em um serviço monitorado uma atualização no modelo da aplicação alvo é executada, seguido pela geração e execução de casos de testes online. Mais precisamente, quatro componentes foram integrados em um circuito autoadap- tativo: um serviço de monitoramento, um serviço de criação de modelos, um serviço de geração de casos de teste baseado em modelos e um serviço de teste. As caracteristicas da estrutura de teste foram testadas em três cenários que foram executados em uma aplicação SOA orquestrada por BPEL, chamada jSeduite. Este trabalho é um esforço para entender as restrições e limitações de teste de soft- ware para aplicações SOA, e apresenta análises e soluções para alguns dos problemas encontrados durante a pesquisaAbstract: Service Oriented Architecture (SOA) is a popular design pattern to build web services be- cause of the interoperability, scalability, and reuse of software solutions that it promotes. The services using this architecture need to operate in a highly dynamic environment, but as the complexity of these services grows, traditional validation processes become less feasible. SOA applications can evolve and change during their execution, and offline tests do not completely assure the correct behavior of the system during its execution. There- fore there is a need of techniques to validate the proper behaviour of SOA applications during the SOA lifecycle. Because of that, in this project online testing will be used. The project goal is to employ model-based testing techniques to generate and execute relevant test cases to SOA applications during runtime. In order to achieve this goal a self-adaptive model-based online testing framework was designed. Tests based on models can be generated offline and online. Offline test are generated before the system execution. Online tests are generated and performed concomitantly, and the output produced by the application under test defines the next step to be performed. when our solution detects that a monitored service evolves, the model of the target service is updated, and online test case generation and execution is performed. More specifically, four components were integrated in a self-adaptive loop: a mon- itoring service, a model generator service, a model based testing service and a testing platform. The testing framework had its features tested in three scenarios that were performed in a SOA application orchestrated by BPEL, called jSeduite. This work is an effort to understand the constraints and limitations of the software testing on SOA applications, and present analysis and solutions to some of the problems found during the researchMestradoCiência da ComputaçãoMestre em Ciência da ComputaçãoCAPE

Automatic Resource Allocation for High Availability Cloud Services

AbstractThis paper proposes an approach to support cloud brokers finding optimal configurations in the deployment of dependability and security sensitive cloud applications. The approach is based on model-driven principles and uses both UML and Bayesian Networks to capture, analyse and optimise cloud deployment configurations. While the paper is most focused on the initial allocation phase, the approach is extensible to the operational phases of the life-cycle. In such a way, a continuous improvement of cloud applications may be realised by monitoring, enforcing and re-negotiating cloud resources following detected anomalies and failures

SLA-Oriented Resource Provisioning for Cloud Computing: Challenges, Architecture, and Solutions

Cloud computing systems promise to offer subscription-oriented, enterprise-quality computing services to users worldwide. With the increased demand for delivering services to a large number of users, they need to offer differentiated services to users and meet their quality expectations. Existing resource management systems in data centers are yet to support Service Level Agreement (SLA)-oriented resource allocation, and thus need to be enhanced to realize cloud computing and utility computing. In addition, no work has been done to collectively incorporate customer-driven service management, computational risk management, and autonomic resource management into a market-based resource management system to target the rapidly changing enterprise requirements of Cloud computing. This paper presents vision, challenges, and architectural elements of SLA-oriented resource management. The proposed architecture supports integration of marketbased provisioning policies and virtualisation technologies for flexible allocation of resources to applications. The performance results obtained from our working prototype system shows the feasibility and effectiveness of SLA-based resource provisioning in Clouds.Comment: 10 pages, 7 figures, Conference Keynote Paper: 2011 IEEE International Conference on Cloud and Service Computing (CSC 2011, IEEE Press, USA), Hong Kong, China, December 12-14, 201

Software-Defined Cloud Computing: Architectural Elements and Open Challenges

The variety of existing cloud services creates a challenge for service providers to enforce reasonable Software Level Agreements (SLA) stating the Quality of Service (QoS) and penalties in case QoS is not achieved. To avoid such penalties at the same time that the infrastructure operates with minimum energy and resource wastage, constant monitoring and adaptation of the infrastructure is needed. We refer to Software-Defined Cloud Computing, or simply Software-Defined Clouds (SDC), as an approach for automating the process of optimal cloud configuration by extending virtualization concept to all resources in a data center. An SDC enables easy reconfiguration and adaptation of physical resources in a cloud infrastructure, to better accommodate the demand on QoS through a software that can describe and manage various aspects comprising the cloud environment. In this paper, we present an architecture for SDCs on data centers with emphasis on mobile cloud applications. We present an evaluation, showcasing the potential of SDC in two use cases-QoS-aware bandwidth allocation and bandwidth-aware, energy-efficient VM placement-and discuss the research challenges and opportunities in this emerging area.Comment: Keynote Paper, 3rd International Conference on Advances in Computing, Communications and Informatics (ICACCI 2014), September 24-27, 2014, Delhi, Indi