Scheduling in virtual infrastructure

For the execution of the scientific applications, different methods have been proposed to dynamically provide execution environments for such applications that hide the complexity of underlying distributed and heterogeneous infrastructures. Recently virtualization has emerged as a promising technology to provide such environments. Virtualization is a technology that abstracts away the details of physical hardware and provides virtualized resources for high-level scientific applications. Virtualization offers a cost-effective and flexible way to use and manage computing resources. Such an abstraction is appealing in Grid computing and Cloud computing for better matching jobs (applications) to computational resources. This work applies the virtualization concept to the Condor dynamic resource management system by using Condor Virtual Universe to harvest the existing virtual computing resources to their maximum utility. It allows existing computing resources to be dynamically provisioned at run-time by users based on application requirements instead of statically at design-time thereby lay the basis for efficient use of the available resources, thus providing way for the efficient use of the available resources.

Phylogenetic Code in the Cloud - Can it Meet the Expectations?

Cloud computing has recently become very popular, and several bioinformatics applications exist already in that domain. The aim of this article is to analyse a current cloud system with respect to usability, benchmark its performance and compare its user friendliness with a conventional cluster job submission system. Given the current hype on the theme, user expectations are rather high, but current results show that neither the price/performance ratio nor the usage model is very satisfactory for large-scale embarrassingly parallel applications. However, for small to medium scale applications that require CPU time at certain peak times the cloud is a suitable alternative.

Designing business models of cloud platforms

Cloud computing and its three facets (Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS)) are terms that denote new developments in the software industry. In particular, PaaS solutions, also referred to as cloud platforms, are changing the way software is being produced, distributed, consumed, and priced. Software vendors have started considering cloud platforms as a strategic option but are battling to redefine their offerings to embrace PaaS. In contrast to SaaS and IaaS, PaaS allows for value co-creation with partners to develop complementary components and applications. It thus requires multisided business models that bring together two or more distinct customer segments. Understanding how to design PaaS business models to establish a flourishing ecosystem is crucial for software vendors. This doctoral thesis aims to address this issue in three interrelated research parts. First, based on case study research, the thesis provides a deeper understanding of current PaaS business models and their evolution. Second, it analyses and simulates consumers' preferences regarding PaaS business models, using a conjoint approach to find out what determines the choice of cloud platforms. Finally, building on the previous research outcomes, the third part introduces a design theory for the emerging class of PaaS business models, which is grounded on an extensive action design research study with a large European software vendor. Understanding PaaS business models from a market as well as a consumer perspective will, together with the design theory, inform and guide decision makers in their business model innovation plans. It also closes gaps in the research related to PaaS business model design and more generally related to platform business models.

@neurIST infrastructure for advanced disease management through integration of heterogeneous data, computing, and complex processing services

The increasing volume of data describing humandisease processes and the growing complexity of understanding, managing, and sharing such data presents a huge challenge for clinicians and medical researchers. This paper presents the@neurIST system, which provides an infrastructure for biomedical research while aiding clinical care, by bringing together heterogeneous data and complex processing and computing services. Although @neurIST targets the investigation and treatment of cerebral aneurysms, the system’s architecture is generic enough that it could be adapted to the treatment of other diseases.Innovations in @neurIST include confining the patient data pertaining to aneurysms inside a single environment that offers cliniciansthe tools to analyze and interpret patient data and make use of knowledge-based guidance in planning their treatment. Medicalresearchers gain access to a critical mass of aneurysm related data due to the system’s ability to federate distributed informationsources. A semantically mediated grid infrastructure ensures that both clinicians and researchers are able to seamlessly access andwork on data that is distributed across multiple sites in a secure way in addition to providing computing resources on demand forperforming computationally intensive simulations for treatment planning and research.

Estudi de cloud cumputing i desenvolupament d'un gestor de currículums en eyeOS

El Cloud Computing o computació en el núvol és un conjunt de tecnologies que busca tenir tots els nostres arxius i informació a Internet sense dependre de tenir la capacitat suficient per emmagatzemar informació, tan sols d'oferir-nos el servei que volem en el moment que necessitem. En aquest projecte es detalla l'estudi de les diferents solucions cloud a nivell personal necessàries pel nostre dia a dia amb l'objectiu d'obtenir una eina que ens permeti posteriorment desenvolupar una petita aplicació per a gestionar els nostres currículums vitae.

A Confluence of Risks: Control and Compliance in the World of Unstructured Data, Big Data and the Cloud

The emergence of powerful new technologies, the existence of large quantities of data, and increasing demands for the extraction of added value from these technologies and data have created a number of significant challenges for those charged with both corporate and information technology management. The possibilities are great, the expectations high, and the risks significant. Organisations seeking to employ cloud technologies and exploit the value of the data to which they have access, be this in the form of "Big Data" available from different external sources or data held within the organisation, in structured or unstructured formats, need to understand the risks involved in such activities. Data owners have responsibilities towards the subjects of the data and must also, frequently, demonstrate that they are in compliance with current standards, laws and regulations. This thesis sets out to explore the nature of the technologies that organisations might utilise, identify the most pertinent constraints and risks, and propose a framework for the management of data from discovery to external hosting that will allow the most significant risks to be managed through the definition, implementation, and performance of appropriate internal control activities.

Estado del arte en soluciones de virtualización : Sistemas gestores de Cloud: OpenNebula

En el presente proyecto se ha abordado la tarea de acercar las tecnologías existentes de plataformas de gestión de infraestructuras ofrecidas en la nube (Cloud Management Platform, aka CMP) al mundo empresarial. En concreto, se ha desplegado una solución de explotación de infraestructuras privadas en la nube (IaaS) enfocada a la gestión de un datacenter virtualizado, utilizando para ello soluciones completamente basadas en software libre, en concreto, OpenNebula.

Estado del arte en soluciones de virtualización/sistemas gestores cloud : OpenStack

Los servicios cloud se utilizan cada vez más en todo tipo de entornos, y la tendencia no hará sino acentuarse en los próximos años. Amazon AWS es líder de servicios IaaS y todos pretenden imitarles con éxito. OpenStack es una de las soluciones OpenSource con más apoyo de la comunidad y de sponsors de renombre. El presente proyecto introduce la arquitectura OpenStack y desarrolla un proyecto real de explotación IaaS basado en ésta.

Cloud Corporatiu

Detall d'una implementació d'un sistema de computació al núvol a baixa escala i a nivell corporatiu.

Web-sovellus Google App Engine alustalle

App Engine on lyhenne englanninkielisistä termeistä application, sovellus ja engine, moottori. Kyseessä on Google, Inc. -konsernin toteuttama kaupallinen palvelu, joka noudattaa pilvimallin tietojenkäsittelyn periaatteita ja mahdollistaa asiakkaan oman sovelluskehityksen. Järjestelmään on mahdollista ohjelmoida itse ideoitu palvelu Internet - verkon välityksellä käytettäväksi, joko yksityisesti tai julkisesti. Kyse on siis hajautetusta palvelinjärjestelmästä, jonka tarjoaa dynaamisesti kuormitukseen sopeutuvan sovellusalustan, jossa asiakas ei vuokraa virtuaalikoneita. Myös järjestelmän tarjoama tallennuskapasiteetti on saatavilla joustavasti. Itse kandidaatintyössä syvennytään yksityiskohtaisemmin sovelluksen toteuttamiseen palvelussa, rajoitteisiin ja soveltuvuuteen. Alussa käydään läpi pilvikäsite, joista monilla tietokoneiden käyttäjillä on epäselvä käsitys. Erilaisia kokonaisuuksia voidaan luoda erittäin monella tavalla, joista rajaamme käsittelyn kohteeksi toteuttamiskelpoiset yleiset ratkaisut.

When to Utilize Software as a Service

Cloud computing enables on-demand network access to shared resources (e.g., computation, networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort. Cloud computing refers to both the applications delivered as services over the Internet and the hardware and system software in the data centers. Software as a service (SaaS) is part of cloud computing. It is one of the cloud service models. SaaS is software deployed as a hosted service and accessed over the Internet. In SaaS, the consumer uses the provider‘s applications running in the cloud. SaaS separates the possession and ownership of software from its use. The applications can be accessed from any device through a thin client interface. A typical SaaS application is used with a web browser based on monthly pricing. In this thesis, the characteristics of cloud computing and SaaS are presented. Also, a few implementation platforms for SaaS are discussed. Then, four different SaaS implementation cases and one transformation case are deliberated. The pros and cons of SaaS are studied. This is done based on literature references and analysis of the SaaS implementations and the transformation case. The analysis is done both from the customer‘s and service provider‘s point of view. In addition, the pros and cons of on-premises software are listed. The purpose of this thesis is to find when SaaS should be utilized and when it is better to choose a traditional on-premises software. The qualities of SaaS bring many benefits both for the customer as well as the provider. A customer should utilize SaaS when it provides cost savings, ease, and scalability over on-premises software. SaaS is reasonable when the customer does not need tailoring, but he only needs a simple, general-purpose service, and the application supports customer‘s core business. A provider should utilize SaaS when it offers cost savings, scalability, faster development, and wider customer base over on-premises software. It is wise to choose SaaS when the application is cheap, aimed at mass market, needs frequent updating, needs high performance computing, needs storing large amounts of data, or there is some other direct value from the cloud infrastructure.

SaaS and Public Cloud from Custom Application Provider’s Perspective

The main objective of this master’s thesis is to provide a comprehensive view to cloud computing and SaaS, and analyze how well CADM, a unit of Capgemini Finland Ltd., would fit to the cloud-based SaaS business. Another objective for this thesis is to investigate how public clouds would fit for CADM as a delivery model, if they would provide SaaS applications to their customers. This master’s thesis is executed by investigating characteristics of cloud computing and SaaS especially from application provider point of view. This is done by exploring what kinds of researches and analysis there have been done regarding these two phenomena during past few years. Then CADM’s current business model and operations are analyzed from SaaS’s and public cloud’s perspective. This analyzing part is conducted by using SWOT analysis which is widely used analytical tool when observing company’s strategic position and when figuring out possibilities how to improve company’s operations. The conducted analysis and observations reveals that CADM should pursue SaaS business as it could provide remarkable advantages and strengthen their position in current markets. However, pure SaaS model would not be the optimal solution for CADM because they do not have own product which could be transformed to SaaS model, and they lack of Infrastructure Management ability. Also public cloud would not be the most suitable delivery model for them if providing SaaS services. The main observation of this thesis is that CADM should adopt the SaaS model via Capgemini Immediate offering.

Enterprise applications migration to the cloud: risks and opportunities

Millions of enterprises move their applications to a cloud every year. According to Forrester Research “the global cloud computing market will grow from a $40.7 billion in 2011 to $241 billion in 2020”. Due to increased interests and demand broad range of providers and solutions have appeared in the market. It is vital to be able to predict possible problems correctly and to classify and mitigate risks associated with the migration process. The study will show the main criteria that should be taken into consideration while making decision of moving enterprise applications to the cloud and choosing appropriate vendor. The main goal of the research is to identify main problems during the migration to a cloud and propose a solution for their prevention and mitigation of consequences in case of occurrence. The research provides an overview of existing cloud solutions and deployment models for enterprise applications. It identifies decision drivers of an applications migration to a cloud and potential risks and benefits associated with this. Finally, the best practices for the successful enterprise-to-cloud migration based on the case studies analysis are formulated.

Cloud service purchase behavior

This study aims to open up some typical models of organizational buying behavior. As the cloud computing and cloud services seem to be the today´s hype, the study seeks to further facilitate the understanding of organizational buying behavior regarding cloud services by interviewing a decision maker of this field in the purchaser´s side and also for comparison a cloud service provider´s representative from the vendor´s side.

Empirical study on the adoption, use and effects of cloud-based testing

Cloud computing is a practically relevant paradigm in computing today. Testing is one of the distinct areas where cloud computing can be applied. This study addressed the applicability of cloud computing for testing within organizational and strategic contexts. The study focused on issues related to the adoption, use and effects of cloudbased testing. The study applied empirical research methods. The data was collected through interviews with practitioners from 30 organizations and was analysed using the grounded theory method. The research process consisted of four phases. The first phase studied the definitions and perceptions related to cloud-based testing. The second phase observed cloud-based testing in real-life practice. The third phase analysed quality in the context of cloud application development. The fourth phase studied the applicability of cloud computing in the gaming industry. The results showed that cloud computing is relevant and applicable for testing and application development, as well as other areas, e.g., game development. The research identified the benefits, challenges, requirements and effects of cloud-based testing; and formulated a roadmap and strategy for adopting cloud-based testing. The study also explored quality issues in cloud application development. As a special case, the research included a study on applicability of cloud computing in game development. The results can be used by companies to enhance the processes for managing cloudbased testing, evaluating practical cloud-based testing work and assessing the appropriateness of cloud-based testing for specific testing needs.