Service Level Agreements-Driven Management of Distributed Applications in Cloud Computing Environments

Cloud Computing enables provisioning and distribution of highly scalable services in a reliable, on-demand and sustainable manner. However, objectives of managing enterprise distributed applications in cloud environments under Service Level Agreement (SLA) constraints lead to challenges for maintaining optimal resource control. Furthermore, conflicting objectives in management of cloud infrastructure and distributed applications might lead to violations of SLAs and inefficient use of hardware and software resources. This dissertation focusses on how SLAs can be used as an input to the cloud management system, increasing the efficiency of allocating resources, as well as that of infrastructure scaling. First, we present an extended SLA semantic model for modelling complex service-dependencies in distributed applications, and for enabling automated cloud infrastructure management operations. Second, we describe a multi-objective VM allocation algorithm for optimised resource allocation in infrastructure clouds. Third, we describe a method of discovering relations between the performance indicators of services belonging to distributed applications and then using these relations for building scaling rules that a CMS can use for automated management of VMs. Fourth, we introduce two novel VM-scaling algorithms, which optimally scale systems composed of VMs, based on given SLA performance constraints. All presented research works were implemented and tested using enterprise distributed applications.

Service level agreements-driven management of distributed applications in cloud computing environments

Advancements in cloud computing have enabled the proliferation of distributed applications, which require management and control of multiple services. However, without an efficient mechanism for scaling services in response to changing workload conditions, such as number of connected users, application performance might suffer, leading to violations of Service Level Agreements (SLA) and possible inefficient use of hardware resources. Combining dynamic application requirements with the increased use of virtualised computing resources creates a challenging resource Management context for application and cloud-infrastructure owners. In such complex environments, business entities use SLAs as a means for specifying quantitative and qualitative requirements of services. There are several challenges in running distributed enterprise applications in cloud environments, ranging from the instantiation of service VMs in the correct order using an adequate quantity of computing resources, to adapting the number of running services in response to varying external loads, such as number of users. The application owner is interested in finding the optimum amount of computing and network resources to use for ensuring that the performance requirements of all her/his applications are met. She/he is also interested in appropriately scaling the distributed services so that application performance guarantees are maintained even under dynamic workload conditions. Similarly, the infrastructure Providers are interested in optimally provisioning the virtual resources onto the available physical infrastructure so that her/his operational costs are minimized, while maximizing the performance of tenants’ applications. Motivated by the complexities associated with the management and scaling of distributed applications, while satisfying multiple objectives (related to both consumers and providers of cloud resources), this thesis proposes a cloud resource management platform able to dynamically provision and coordinate the various lifecycle actions on both virtual and physical cloud resources using semantically enriched SLAs. The system focuses on dynamic sizing (scaling) of virtual infrastructures composed of virtual machines (VM) bounded application services. We describe several algorithms for adapting the number of VMs allocated to the distributed application in response to changing workload conditions, based on SLA-defined performance guarantees. We also present a framework for dynamic composition of scaling rules for distributed service, which used benchmark-generated application Monitoring traces. We show how these scaling rules can be combined and included into semantic SLAs for controlling allocation of services. We also provide a detailed description of the multi-objective infrastructure resource allocation problem and various approaches to satisfying this problem. We present a resource management system based on a genetic algorithm, which performs allocation of virtual resources, while considering the optimization of multiple criteria. We prove that our approach significantly outperforms reactive VM-scaling algorithms as well as heuristic-based VM-allocation approaches.

Cloud Computing Service for Managing Large Medical Image Data-Sets Using Balanced Collaborative Agents

Managing large medical image collections is an increasingly demanding important issue in many hospitals and other medical settings. A huge amount of this information is daily generated, which requires robust and agile systems. In this paper we present a distributed multi-agent system capable of managing very large medical image datasets. In this approach, agents extract low-level information from images and store them in a data structure implemented in a relational database. The data structure can also store semantic information related to images and particular regions. A distinctive aspect of our work is that a single image can be divided so that the resultant sub-images can be stored and managed separately by different agents to improve performance in data accessing and processing. The system also offers the possibility of applying some region-based operations and filters on images, facilitating image classification. These operations can be performed directly on data structures in the database.

Cloud Computing en salud: Sistema para Administrar Imagenes Biomedicas

En el campo de la biomedicina se genera una inmensa cantidad de imágenes diariamente. Para administrarlas es necesaria la creación de sistemas informáticos robustos y ágiles, que necesitan gran cantidad de recursos computacionales. El presente artículo presenta un servicio de cloud computing capaz de manejar grandes colecciones de imágenes biomédicas. Gracias a este servicio organizaciones y usuarios podrían administrar sus imágenes biomédicas sin necesidad de poseer grandes recursos informáticos. El servicio usa un sistema distribuido multi agente donde las imágenes son procesadas y se extraen y almacenan en una estructura de datos las regiones que contiene junto con sus características. Una característica novedosa del sistema es que una misma imagen puede ser dividida, y las sub-imágenes resultantes pueden ser almacenadas por separado por distintos agentes. Esta característica ayuda a mejorar el rendimiento del sistema a la hora de buscar y recuperar las imágenes almacenadas.

Reliability issues related to the usage of Cloud Computing in Critical Infrastructures

The use of cloud computing is extending to all kind of systems, including the ones that are part of Critical Infrastructures, and measuring the reliability is becoming more difficult. Computing is becoming the 5th utility, in part thanks to the use of cloud services. Cloud computing is used now by all types of systems and organizations, including critical infrastructure, creating hidden inter-dependencies on both public and private cloud models. This paper investigates the use of cloud computing by critical infrastructure systems, the reliability and continuity of services risks associated with their use by critical systems. Some examples are presented of their use by different critical industries, and even when the use of cloud computing by such systems is not widely extended, there is a future risk that this paper presents. The concepts of macro and micro dependability and the model we introduce are useful for inter-dependency definition and for analyzing the resilience of systems that depend on other systems, specifically in the cloud model.

Algunos retos de la protección de datos en la sociedad del conocimiento. Especial detenimiento en la computación en la nube (cloud computing).

Los continuos avances tecnológicos están trayendo consigo nuevas formas de almacenar, tratar y comunicar datos personales. Es necesario repensar el derecho fundamental a la protección de datos, y arbitrar mecanismos para adaptarlo a las nuevas formas de tratamiento. a nivel europeo se está trabajando en una nueva propuesta de regulación que consideramos, en general, muy apropiada para afrontar los nuevos retos en esta materia. para ejemplificar todo esto, en el presente estudio se plantea de forma detallada el caso de la computación en nube, sus principales características y algunas preocupaciones acerca de los riesgos potenciales que su utilización trae consigo. Abstract: Rapid technological developments are bringing new ways to store, process and communicate personal data. We need to rethink the fundamental right to data protection and adapt it to new forms of treatment. there is a new «european» proposal for a regulation on the protection of individuals with regard to the processing of personal data, well suited to meet the new challenges. this study offers one example of this: the cloud computing, its main characteristics and some concerns about the potential risks that its use entails.

The new cloud computing paradigm: the way to IT seen as a utility

In the present competitive environment, companies are wondering how to reduce their IT costs while increasing their efficiency and agility to react when changes in the business processes are required. Cloud Computing is the latest paradigm to optimize the use of IT resources considering ?everything as a service? and receiving these services from the Cloud (Internet) instead of owning and managing hardware and software assets. The benefits from the model are clear. However, there are also concerns and issues to be solved before Cloud Computing spreads across the different industries. This model will allow a pay-per-use model for the IT services and many benefits like cost savings, agility to react when business demands changes and simplicity because there will not be any infrastructure to operate and administrate. It will be comparable to the well known utilities like electricity, water or gas companies. However, this paper underlines several risk factors of the model. Leading technology companies should research on solutions to minimize the risks described in this article. Keywords - Cloud Computing, Utility Computing, Elastic Computing, Enterprise Agility

Accessing advanced computational resources in Africa through Cloud Computing

Low resources in many African locations do not allow many African scientists and physicians to access the latest advances in technology. This deficiency hinders the daily life of African professionals that often cannot afford, for instance, the cost of internet fees or software licenses. The AFRICA BUILD project, funded by the European Commission and formed by four European and four African institutions, intends to provide advanced computational tools to African institutions in order to solve current technological limitations. In the context of AFRICA BUILD we have carried out, a series of experiments to test the feasibility of using Cloud Computing technologies in two different locations in Africa: Egypt and Burundi. The project aims to create a virtual platform to provide access to a wide range of biomedical informatics and learning resources to professionals and researchers in Africa.

Building sustainable capacity for health research in africa through cloud computing applications

Access to information and continuous education represent critical factors for physicians and researchers over the world. For African professionals, this situation is even more problematic due to the frequently difficult access to technological infrastructures and basic information. Both education and information technologies (e.g., including hardware, software or networking) are expensive and unaffordable for many African professionals. Thus, the use of e-learning and an open approach to information exchange and software use have been already proposed to improve medical informatics issues in Africa. In this context, the AFRICA BUILD project, supported by the European Commission, aims to develop a virtual platform to provide access to a wide range of biomedical informatics and learning resources to professionals and researchers in Africa. A consortium of four African and four European partners work together in this initiative. In this framework, we have developed a prototype of a cloud-computing infrastructure to demonstrate, as a proof of concept, the feasibility of this approach. We have conducted the experiment in two different locations in Africa: Burundi and Egypt. As shown in this paper, technologies such as cloud computing and the use of open source medical software for a large range of case present significant challenges and opportunities for developing countries, such as many in Africa.

El cloud computing en la pyme española

Las últimas previsiones de mercado el cloud computing pronostican un crecimiento anual del 30%, ya que cada vez más personas adoptan la tecnología más avanzada para almacenar información en un espacio virtual. Sin embargo, el cloud computing no es sólo un sistema de almacenamiento de datos, sino que también se puede utilizar para ejecutar software y aplicaciones de forma remota, sin estar atado a un único ordenador. Para una pequeña empresa, la externalización de TI a la nube reduce la necesidad de contratar personas con habilidades especializadas y libera a los directores para que puedan concentrarse en el negocio. En el segundo capítulo analizamos el estado del arte del cloud computing, para lo cual en primer lugar definimos qué es cloud, así como cuáles son sus ventajas e inconvenientes. Presentamos los diferentes modelos de cloud computing, y cuáles son sus principales proveedores actualmente. Para finalizar esbozamos unas pinceladas del siempre complejo marco regulatorio del cloud computing en España. En el Capítulo 3 presentamos la situación de las pequeñas y medianas empresas dentro del ecosistema empresarial español, basándonos en los datos proporcionados por el Instituto Nacional de Estadística del año 2013. A continuación, en el Capítulo 4, analizamos la penetración del Cloud Computing en España, desde el punto de vista que tienen las pequeñas empresas de las tecnologías cloud, así como del uso que estas hacen del mismo. Para este capítulo hemos utilizado el informe realizado por Deloitte para el Ministerio de Industria, Energía y Turismo. En el capítulo 5 veremos un caso real de solución software as a service, desarrollado por mi empresa. Se trata de una aplicación de gestión de activos inmobiliarios, que enfocaremos hacia las pequeñas inmobiliarias. Para ello analizaremos la tipología de Pyme hacia la que queremos dirigir el producto viendo en detalle el sector de las actividades inmobiliarias, así como describiremos qué tipo de aplicación es y su funcionalidad (de modo muy resumido consiste en la gestión del ciclo de venta de todos los inmuebles de una agencia inmobiliaria, desde que el cliente solicita una visita, hasta que se lleva a cabo la firma de las escrituras). Posicionaremos el producto en precio y haremos una comparativa entre otras soluciones tanto cloud como on-premise para comparar su ventaja competitiva en precio. A continuación describiremos cómo pensamos hacer la comunicación del producto, mediante la publicación de la aplicación en el App Exchange de Salesforce, ferias inmobiliarias, etc y describiremos los servicios de valor añadido que ofrecemos. Por último estableceremos las previsiones económicas a tres años de las ventas del producto. Por último en el Capítulo 6 concluiremos el proyecto con una serie de reflexiones sobre los retos y las oportunidades a las que se enfrentan las Pymes actualmente, en lo que se refiere a la implantación de sistemas en la nube, y más concretamente los retos y oportunidades que pueden tener las Pymes el sector inmobiliario con las soluciones cloud.

The educational learning lifecycle and the cloud computing

Currently, student dropout rates are a matter of concern among universities. Many research studies, aimed at discovering the causes, have been carried out. However, few solutions, that could serve all students and related problems, have been proposed so far. One such problem is caused by the lack of the "knowledge chain educational links" that occurs when students move onto higher studies without mastering their basic studies. Most regulated studies imparted at universities are designed so that some basic subjects serve as support for other, more complicated, subjects, thus forming a complicated knowledge network. When a link in this chain fails, student frustration occurs as it prevents him from fully understanding the following educational links. In this proposal we try to mitigate these disasters that stem, for the most part, the student?s frustration beyond his college stay. On one hand, we make a dissertation on the student?s learning process, which we divide into a series of phases that amount to what we call the "learning lifecycle." Also, we analyze at what stage the action by the stakeholders involved in this scenario: teachers and students; is most important. On the other hand, we consider that Information and Communication Technologies ICT, such as Cloud Computing, can help develop new ways, allowing for the teaching of higher education, while easing and facilitating the student?s learning process. But, methods and processes need to be defined as to direct the use of such technologies; in the teaching process in general, and within higher education in particular; in order to achieve optimum results. Our methodology integrates, as another actor, the ICT into the "Learning Lifecycle". We stimulate students to stop being merely spectators of their own education, and encourage them to take an active part in their training process. To do this, we offer a set of useful tools to determine not only academic failure causes, (for self assessment), but also to remedy these failures (with corrective actions); "discovered the causes it is easier to determine solutions?. We believe this study will be useful for both students and teachers. Students learn from their own experience and improve their learning process, while obtaining all of the "knowledge chain educational links? required in their studies. We stand by the motto "Studying to learn instead of studying to pass". Teachers will also be benefited by detecting where and how to strengthen their teaching proposals. All of this will also result in decreasing dropout rates.

Server power modeling for run-time energy optimization of cloud computing facilities

As advanced Cloud services are becoming mainstream, the contribution of data centers in the overall power consumption of modern cities is growing dramatically. The average consumption of a single data center is equivalent to the energy consumption of 25.000 households. Modeling the power consumption for these infrastructures is crucial to anticipate the effects of aggressive optimization policies, but accurate and fast power modeling is a complex challenge for high-end servers not yet satisfied by analytical approaches. This work proposes an automatic method, based on Multi-Objective Particle Swarm Optimization, for the identification of power models of enterprise servers in Cloud data centers. Our approach, as opposed to previous procedures, does not only consider the workload consolidation for deriving the power model, but also incorporates other non traditional factors like the static power consumption and its dependence with temperature. Our experimental results shows that we reach slightly better models than classical approaches, but simul- taneously simplifying the power model structure and thus the numbers of sensors needed, which is very promising for a short-term energy prediction. This work, validated with real Cloud applications, broadens the possibilities to derive efficient energy saving techniques for Cloud facilities.

GovCloud: the usage of cloud computing in public organizations

It has been shown that cloud computing brings cost benefits and promotes efficiency in the operations of the organizations, no matter what their type or size. However, few public organizations are benefiting from this new paradigm shift in the way the organizations consume and manage computational resources. The objective of this thesis is to analyze both internal and external factors that may influence the adoption of cloud computing by public organizations and propose possible strategies that can assist these organizations in their path to cloud usage. In order to achieve this objective, a SWOT analysis has been conducted, detecting internal factors (strengths and weaknesses) and external factors (opportunities and threats) that can influence the adoption of a governmental cloud. With the application of a TOWS matrix, by combining the internal and external factors, a list of possible strategies have been formulated to be used as a guide to decision-making related to the transition to a cloud environment.

Flexible Framework for Real-Time Embedded Systems Based on Mobile Cloud Computing Paradigm

The development of applications as well as the services for mobile systems faces a varied range of devices with very heterogeneous capabilities whose response times are difficult to predict. The research described in this work aims to respond to this issue by developing a computational model that formalizes the problem and that defines adjusting computing methods. The described proposal combines imprecise computing strategies with cloud computing paradigms in order to provide flexible implementation frameworks for embedded or mobile devices. As a result, the imprecise computation scheduling method on the workload of the embedded system is the solution to move computing to the cloud according to the priority and response time of the tasks to be executed and hereby be able to meet productivity and quality of desired services. A technique to estimate network delays and to schedule more accurately tasks is illustrated in this paper. An application example in which this technique is experimented in running contexts with heterogeneous work loading for checking the validity of the proposed model is described.