Architecture for Analysis of Streaming Data

While several attempts have been made to construct a scalable and flexible architecture for analysis of streaming data, no general model to tackle this task exists. Thus, our goal is to build a scalable and maintainable architecture for performing analytics on streaming data. To reach this goal, we introduce a 7-layered architecture consisting of microservices and publish-subscribe software. Our study shows that this architecture yields a good balance between scalability and maintainability due to high cohesion and low coupling of the solution, as well as asynchronous communication between the layers. This architecture can help practitioners to improve their analytic solutions. It is also of interest to academics, as it is a building block for a general architecture for processing streaming data

Cloud Storage and Bioinformatics in a private cloud deployment: Lessons for Data Intensive research

This paper describes service portability for a private cloud deployment, including a detailed case study about Cloud Storage and bioinformatics services developed as part of the Cloud Computing Adoption Framework (CCAF). Our Cloud Storage design and deployment is based on Storage Area Network (SAN) technologies, details of which include functionalities, technical implementation, architecture and user support. Experiments for data services (backup automation, data recovery and data migration) are performed and results confirm backup automation is completed swiftly and is reliable for data-intensive research. The data recovery result confirms that execution time is in proportion to quantity of recovered data, but the failure rate increases in an exponential manner. The data migration result confirms execution time is in proportion to disk volume of migrated data, but again the failure rate increases in an exponential manner. In addition, benefits of CCAF are illustrated using several bioinformatics examples such as tumour modelling, brain imaging, insulin molecules and simulations for medical training. Our Cloud Storage solution described here offers cost reduction, time-saving and user friendliness

Recovery And Migration Of Application Logic From Legacy Systems

Future Internet technologies necessitate dramatic changes in system design, deliveryand usage patterns. For many legacy applications it means that their furtherdevelopment and transition to the Internet becomes problematic or evenimpossible due to the obsolescence of technologies they use. Replacement ofthe old system with the new one, built from scratch, is usually economicallyunacceptable. Therefore, there is a call for methods and tools supportingthe automated migration of legacy systems into a new paradigm. This paperproposes a tool supported method for recovery and migration of applicationlogic information from legacy systems. The information extracted from a legacyapplication is stored in the form of precise requirement-level models enablingautomated transformation into a new system structure in a model-driven way.Evaluation of the approach is based on a case study legacy system

Cloud provider independence using DevOps methodologies with Infrastructure-as-Code

On choosing cloud computing infrastructure for IT needs there is a risk of becoming dependent and locked-in on a specific cloud provider from which it becomes difficult to switch should an entity decide to move all of the infrastructure resources into a different provider. There’s widespread information available on how to migrate existing infrastructure to the cloud notwithstanding common cloud solutions and providers don't have any clear path or framework for supporting their tenants to migrate off the cloud into another provider or cloud infrastructure with similar service levels should they decide to do so. Under these circumstances it becomes difficult to switch from cloud provider not just because of the technical complexity of recreating the entire infrastructure from scratch and moving related data but also because of the cost it may involve. One possible solution is to evaluate the use of Infrastructure-as-Code languages for defining infrastructure (“Infrastructure-as-Code”) combined with DevOps methodologies and technologies to create a mechanism that helps streamline the migration process between different cloud infrastructure especially if taken into account from the beginning of a project. A well-structured DevOps methodology combined with Infrastructure-as-Code may allow a more integrated control on cloud resources as those can be defined and controlled with specific languages and be submitted to automation processes. Such definitions must take into account what is currently available to support those operations under the chosen cloud infrastructure APIs, always seeking to guarantee the tenant an higher degree of control over its infrastructure and higher level of preparation of the necessary steps for the recreation or migration of such infrastructure should the need arise, somehow integrating cloud resources as part of a development model. The objective of this dissertation is to create a conceptual reference framework that can identify different forms for migration of IT infrastructure while always contemplating a higher provider independence by resorting to such mechanisms, as well as identify possible constraints or obstacles under this approach. Such a framework can be referenced from the beginning of a development project if foreseeable changes in infrastructure or provider are a possibility in the future, taking into account what the API’s provide in order to make such transitions easier.Ao optar-se por infraestruturas de computação em nuvem para soluções de TI existe um risco associado de se ficar dependente de um fornecedor de serviço específico, do qual se torna difícil mudar caso se decida posteriormente movimentar toda essa infraestrutura para um outro fornecedor. Encontra-se disponível extensa documentação sobre como migrar infraestrutura já  existente para modelos de computação em nuvem, de qualquer modo as soluções e os fornecedores de serviço não dispõem de formas ou metodologias claras que suportem os seus clientes em migrações para fora da nuvem, seja para outro fornecedor ou infraestrutura com semelhantes tipos de serviço, caso assim o desejem. Nestas circunstâncias torna-se difícil mudar de fornecedor de serviço não apenas pela complexidade técnica associada à criação de toda a infraestrutura de raiz e movimentação de todos os dados associados a esta mas também devido aos custos que envolve uma operação deste tipo. Uma possível solução é avaliar a utilização de linguagens para definição de infraestrutura como código (“Infrastructure-as-Code”) em conjunção com metodologias e tecnologias “DevOps” de forma a criar um mecanismo que permita flexibilizar um processo de migração entre diferentes infraestruturas de computação em nuvem, especialmente se for contemplado desde o início de um projecto. Uma metodologia “DevOps” devidamente estruturada quando combinada com definição de infraestrutura como código pode permitir um controlo mais integrado de recursos na nuvem uma vez que estes podem ser definidos e controlados através de linguagens específicas e submetidos a processos de automação. Tais definições terão de ter em consideração o que existe disponível para suportar as necessárias operações através das “API’s” das infraestruturas de computação em nuvem, procurando sempre garantir ao utilizador um elevado grau de controlo sobre a sua infraestrutura e um maior nível de preparação dos passos necessários para recriação ou migração da infraestrutura caso essa necessidade surja, integrando de certa forma os recursos de computação em nuvem como parte do modelo de desenvolvimento. Esta dissertação tem como objetivo a criação de um modelo de referência conceptual que identifique formas de migração de infraestruturas de computação procurando ao mesmo tempo uma maior independência do fornecedor de serviço com recurso a tais mecanismos, assim como identificar possíveis constrangimentos ou impedimentos nesta aproximação. Tal modelo poderá ser referenciado desde o início de um projecto de desenvolvimento caso seja necessário contemplar uma possível necessidade futura de alterações ao nível da infraestrutura ou de fornecedor, com base no que as “API’s” disponibilizam, de modo a facilitar essa operação.info:eu-repo/semantics/publishedVersio

COEL: A Web-based Chemistry Simulation Framework

The chemical reaction network (CRN) is a widely used formalism to describe macroscopic behavior of chemical systems. Available tools for CRN modelling and simulation require local access, installation, and often involve local file storage, which is susceptible to loss, lacks searchable structure, and does not support concurrency. Furthermore, simulations are often single-threaded, and user interfaces are non-trivial to use. Therefore there are significant hurdles to conducting efficient and collaborative chemical research. In this paper, we introduce a new enterprise chemistry simulation framework, COEL, which addresses these issues. COEL is the first web-based framework of its kind. A visually pleasing and intuitive user interface, simulations that run on a large computational grid, reliable database storage, and transactional services make COEL ideal for collaborative research and education. COEL's most prominent features include ODE-based simulations of chemical reaction networks and multicompartment reaction networks, with rich options for user interactions with those networks. COEL provides DNA-strand displacement transformations and visualization (and is to our knowledge the first CRN framework to do so), GA optimization of rate constants, expression validation, an application-wide plotting engine, and SBML/Octave/Matlab export. We also present an overview of the underlying software and technologies employed and describe the main architectural decisions driving our development. COEL is available at http://coel-sim.org for selected research teams only. We plan to provide a part of COEL's functionality to the general public in the near future.Comment: 23 pages, 12 figures, 1 tabl