A framework and tool to manage Cloud Computing service quality

Cloud Computing has generated considerable interest in both companies specialized in Information and Communication Technology and business context in general. The Sourcing Capability Maturity Model for service (e-SCM) is a capability model for offshore outsourcing services between clients and providers that offers appropriate strategies to enhance Cloud Computing implementation. It intends to achieve the required quality of service and develop an effective working relationship between clients and providers. Moreover, quality evaluation framework is a framework to control the quality of any product and/or process. It offers a tool support that can generate software artifacts to manage any type of product and service efficiently and effectively. Thus, the aim of this paper was to make this framework and tool support available to manage Cloud Computing service quality between clients and providers by means of e-SCM.Ministerio de Ciencia e Innovación TIN2013-46928-C3-3-RJunta de Andalucía TIC-578

Transparent Access to Scientific and Commercial Clouds from the Kepler Workflow Engine

his paper describes the architecture for transparently using several different Cloud Resources from with the graphical Kepler Worklfow environment. This architecture was proven to work by implementing and using it in practice within the FP7 EUFORIA project. The clouds supported are the Open Source cloud OpenNEbula (ONE) environment and the commercial Amazon Elastic Compute Cloud (EC2). Subsequently, these clouds are compared regarding their cost-effectiveness, which covers a performance examination but also the comparison of the commercial against a scientific cloud provider

A Distributed Security Model for Cloud Computing

Security in Cloud Computing is an ongoing concern and so security mechanisms play an important role. While mechanisms for security in the Cloud exist, new vulnerabilities for Cloud is an ongoing issue. For this, we contend that a need for a new type of security mechanism and model is required. Therefore, we propose a conceptual, high-level view of a distributed security model for Cloud Computing. This paper is part of an ongoing longitudinal study in which the model is outlined and discusses how the proposed security model is distributed among Cloud servers. The distributed security model presents multiple sacrificial targets in an attack and consequently eliminates any single point of failure

Cloud computing for energy management in smart grid - an application survey

The smart grid is the emerging energy system wherein the application of information technology, tools and techniques that make the grid run more efficiently. It possesses demand response capacity to help balance electrical consumption with supply. The challenges and opportunities of emerging and future smart grids can be addressed by cloud computing. To focus on these requirements, we provide an in-depth survey on different cloud computing applications for energy management in the smart grid architecture. In this survey, we present an outline of the current state of research on smart grid development. We also propose a model of cloud based economic power dispatch for smart grid

Haptic robot-environment interaction for self-supervised learning in ground mobility

Dissertação para obtenção do Grau de Mestre em Engenharia Eletrotécnica e de ComputadoresThis dissertation presents a system for haptic interaction and self-supervised learning mechanisms to ascertain navigation affordances from depth cues. A simple pan-tilt telescopic arm and a structured light sensor, both fitted to the robot’s body frame, provide the required haptic and depth sensory feedback. The system aims at incrementally develop the ability to assess the cost of navigating in natural environments. For this purpose the robot learns a mapping between the appearance of objects, given sensory data provided by the sensor, and their bendability, perceived by the pan-tilt telescopic arm. The object descriptor, representing the object in memory and used for comparisons with other objects, is rich for a robust comparison and simple enough to allow for fast computations. The output of the memory learning mechanism allied with the haptic interaction point evaluation prioritize interaction points to increase the confidence on the interaction and correctly identifying obstacles, reducing the risk of the robot getting stuck or damaged. If the system concludes that the object is traversable, the environment change detection system allows the robot to overcome it. A set of field trials show the ability of the robot to progressively learn which elements of environment are traversable

EDGE-CoT: next generation cloud computing and its impact on business

Purpose – The main objective of this paper is to analyze the potential impact of future cloud computing trends on business, from the perspective of specialists in the area. Design/ methodology/ approach - Qualitative approach that includes literature review and nine semi-structured interviews with proclaimed influencers and global thought leaders in cloud computing, highlighting Jeff Barr, Vice President of Amazon Web Services. Findings -5G networks will enable the emergence of the Edge-CoT architecture, that will consequently drive the increased application of Artificial Intelligence/ Machine Learning (AI/ML) and Robotics. The combination of Edge-CoT, Robotics and AI/ML triggers the development of Smart Cities and Industry 4.0. Simultaneously, Cloud alone will benefit of increased connectivity and will be the preferred business architecture comparing to EdgeCoT. New industries and businesses will result from the Edge-CoT, and the existing companies will benefit mainly from an improved customer experience. Major business challenges triggered by Edge-CoT include workforce re-skilling, promotion of the agile approach and a cultural shift towards risk-taking. Research limitations/implications - The research study was limited to the analysis of a selected set of cloud computing trends. Moreover, the data collection process was limited to 9 cloud experts, hindering a possible generalization. Originality/value – This study uses a qualitative approach to listen to market experts and cross with the theoretical findings to date, consequently bringing theory and practice closer together.Objetivo - O objetivo deste estudo consiste em analisar o potencial impacto das tendências futuras de cloud computing na gestão das empresas, a partir da visão de especialistas da área. Metodologia- Abordagem qualitativa que engloba revisão de literatura e nove entrevistas semiestruturadas com proclamados influencers e lideres globais em cloud computing, destacando-se Jeff Barr, o Vice-presidente da Amazon Web Services. Resultado - As redes 5G possibilitarão o surgimento da arquitetura Edge-CoT, que consequentemente impulsionará o aumento da aplicação de Inteligência Artificial (AI) e robótica. A combinação de Edge-CoT, Robótica e AI desencadeia o desenvolvimento de Smart Cities e Industry 4.0. Simultaneamente, a Cloud sozinha beneficiará do aumento da conectividade e será a arquitetura preferida comparativamente a Edge-CoT. Novos setores e negócios resultarão do Edge-CoT, e as empresas existentes beneficiarão principalmente de uma melhor experiência do cliente. Os principais desafios organizacionais desencadeados pelo Edge-CoT incluem a requalificação da força de trabalho, a adoção da abordagem agile e uma mudança cultural que estimule experimentos tecnológicos. Restrição da pesquisa - O processo de recolha de dados foi limitado a 9 especialistas em cloud computing, dificultando assim uma possível generalização. Originalidade/ Valor - Este estudo utiliza uma abordagem qualitativa para ouvir os especialistas do mercado e cruzar com os resultados teóricos até o momento, aproximando assim a teoria da prática

Sistemas organizativos para la asignación dinámica de recursos computacionales en entornos distribuidos

[ES]Cloud Computing, el conocido paradigma computacional, está emergiendo en los últimos años con gran fuerza. Este paradigma incluye un novedoso modelo de comercialización basado en el pago por uso que ha cambiado radicalmente el modelo de negocio en Internet, lo que ha permitido que las empresas y usuarios individuales puedan alquilar los recursos computacionales que necesitan en cada momento. Este nuevo modelo computacional también ha derivado en que el modelo de producción de estos recursos computacionales evolucione hasta una aproximación cercana al modelo de producción just-in-time, en el que sólo se consumen los recursos necesarios para la producción de los servicios en función de la demanda existente en cada momento, hablándose dentro de este ámbito de elasticidad en los servicios ofertados. Para que esto sea posible, no cabe duda, que una gran cantidad de tecnologías subyacentes han tenido que madurar para dar como resultado un nicho tecnológico con la capacidad para variar los recursos asociados a cada servicio en función de la demanda. Sin embargo, pese a los indudables avances que se han producido a nivel tecnológico, todavía hoy existe una gran capacidad de mejora de estos sistemas. En este sentido, en el marco de esta tesis doctoral se propone el uso de los sistemas multiagente y, especialmente, aquellos basados en modelos organizativos para el control y monitorización de un sistema Cloud Computing. Gracias a esta aproximación, una de las primeras en este campo de investigación, será posible incluir en las plataformas Cloud de nueva generación características derivadas de la Inteligencia Artificial, como son la autonomía, la proactividad y, también, la capacidad de aprendizaje. Para ello se propone un modelo único en su concepción, que permite dotar a la organización de agentes inteligentes con capacidades auto-adaptativas en tiempo de ejecución para entornos abiertos, altamente dinámicos en los que, además, existe un cierto grado de incertidumbre. Así gracias a este modelo, el sistema es capaz de variar los recursos computacionales asociados a cada servicio producido en función de la demanda existe por parte de los usuarios, mediante la auto-adaptación dinámica del propio sistema en su conjunto