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Microsoft Research is now in its fourth year of awarding Windows Azure cloud resources to the academic community. As of April 2014, over 200 research projects have started. In this paper we review the results of this effort to date. We also characterize the computational paradigms that work well in public cloud environments and those that are usually disappointing. We also discuss many of the barriers to successfully using commercial cloud platforms in research and ways these problems can be overcome.

Multi-cloud computing has established itself as a paradigm of choice for creating very large scale world wide distributed applications. Multi-cloud computing is the usage of multiple, independent cloud environments, which assumed no priori agreement between cloud providers or third party. However, these applications, designed for multi-cloud environments, have to face real challenges in term of design, architecture, and technology. The possibility of using multi-cloud faces the heterogeneity and complexity of cloud solutions. Thus, multi-cloud computing has to face several challenges such as portability, provisioning, elasticity, and high availability we have identified in this thesis. In this thesis, we propose soCloud both a model and a platform that tackle these four challenges. This model is based on the OASIS Service Component Architecture (SCA) standard to design distributed large scale applications for multi-cloud environments. A new language is proposed to effectively express the elasticity of multi-cloud applications through abstraction. The multi-cloud platform is designed to deploy and manage distributed applications across multi-clouds. The soCloud model is illustrated on three distributed applications deployed in multi- cloud environments. The soCloud platform has been implemented, deployed and experimented on top of ten existing cloud providers : Windows Azure, DELL KACE, Amazon EC2, CloudBees, OpenShift, dotCloud, Jelastic, Heroku, Appfog, and an Eucalyptus private cloud. These experiments are used to validate the novelty of the contributed solutions. With our contributions, we aim to provide a simple and effective way to design, deploy, run, and manage distributed applications for a multi-cloud environment by proposing a model and platform.; L'informatique multi-nuages s'est imposée comme un paradigme de choix pour créer des applications distribuées à large échelle s'exécutant à des emplacements géographiques ré- partis. L'informatique multi-nuages consiste en l'utilisation de multiples environnements de nuages indépendants qui ne nécessitent pas d'accord a priori entre les fournisseurs de nuage ou un tiers. Toutefois, ces applications conçues pour un environnement multi-nuages doivent faire face à de véritables défis en terme d'architecture, de modèle et de technologies. L'utilisation de l'informatique multi-nuages se heurte à l'hétérogénéité et à la complexité des offres de nuage. Ainsi, l'informatique multi-nuages doit faire face aux défis de la portabilité, de l'approvisionnement, de l'élasticité et de la haute disponibilité que nous identifions dans cette thèse. Dans ce travail de thèse, nous proposons un modèle d'applications nommé soCloud qui adresse ces quatre défis. C'est un modèle basé sur le standard SCA du consortium OASIS pour concevoir de manière simple et cohérente des applications distribuées à large échelle pour un environnement multi-nuages. Un nouveau langage dédié d'élasticité a été proposé pour exprimer efficacement l'élasticité d'applications multi-nuages par l'abstraction. Nous proposons aussi une plateforme multi-nuages soCloud conçue pour déployer, exécuter et gérer des applications réparties à travers plusieurs nuages. Le modèle d'applications soCloud a été utilisé pour la mise en œuvre de trois applications distribuées déployées dans un environnement multi-nuages. Quant à la plateforme soCloud, elle a été implantée, déployée et expérimentée sur dix nuages : Windows Azure, DELL KACE, Amazon EC2, CloudBees, OpenShift, dotCloud, Jelastic, Heroku, Appfog et Eucalyptus. Ces expériences sont utilisées pour valider la nouveauté des solutions approtées. Grâce à notre contribution, nous visons à offrir un moyen simple et efficace pour concevoir, déployer, exécuter et gérer des applications distribuées pour des environnements multi- nuages en proposant un modèle et une plateforme.

Software-as-a-Service (SaaS) often shares one single application instance among different tenants to reduce costs. However, sharing potentially leads to undesired influence from one tenant onto the performance observed by the others. This is a significant problem as performance is one of the major obstacles for cloud customers. The application does intentionally not manage hardware resources, and the operating system is not aware of application level entities like tenants which makes the performance control a challenge. In case the SaaS is hosted on a Platform-as-a-Service (PaaS), the SaaS developer usually wants to control performance-related issues according to individual needs, and available information is even more limited. Thus, it is difficult to control the performance of different tenants to keep them isolated. Existing work focuses on concrete methods to provide performance isolation in systems where the whole stack is under control. In this paper we present a concrete PaaS enhancement which enables application developers to realize isolation methods for their hosted SaaS application. In a case study we evaluated the applicability and effectiveness of the enhancement in different environments.

Monitoring activities over many different types of sensors are very challenging to support advanced services for Internet of Things (IoT) and its future. However, one of the major issues is the explosion of the amount of heterogeneous information that has to be stored and processed, thus causing the well known Big Data problem. Some Cloud strategies have been investigated to offer IoT-oriented services, but they do not specifically address solutions for Big Data management. In this paper, we present a two-layer architecture based on a hybrid storage system able to support a Platform as a Service (PaaS) federated Cloud scenario. The proposed architecture combines the benefits of both storage approaches. In particular, it allows us on one hand to extend SQL-like legacy systems, and on the other hand to manage Big Data through an XML-like, non-SQL distributed storage system according to a Cloud federation approach.

International audience; Collaboration of organizations in professional context has become ubiquitous. However, the security issues still exist. In this paper, we propose a decentralised hybrid framework for managing identity and access control for collaborative platforms as a service PaaS. We propose an approach based on federations that ensure the interoperability within the platform while preserving organizations authentication and authorization mechanisms.

Cloud computing promises scalable hosting by offering an elastic management of virtual machines which run on top of hardware data centers. This elastic management as a cornerstone of PaaS (Platform As A Service) has to deal with trade-offs between conflicting requirements such as cost and quality of service. Solving such trade-offs is a challenging problem. Indeed, most of PaaS providers consider only one optimization axis or ad-hoc multi-objective resolution techniques using domain specific heuristics. This paper aims at proposing a generic approach to build cloud optimization by combining modeling and search based paradigms. Our approach is two-fold: 1) To reason about a cloud environment, we use a Models@run.time approach to have an abstraction layer of a cloud configuration that supports monitoring capabilities and represents cloud intrinsic parameters like cost, load information, etc. 2) We use a search-based algorithm to navigate through cloud candidate configuration solutions in order to solve the Cloud Multi-objective Optimization Problem (CMOP). We validate our approach based on a case study that we define with our cloud provider partner EBRC as representative of a dynamic management problem of heterogeneous distributed cloud nodes. We implement a prototype of our PaaS supervision framework using Kevoree, a Models@run.time platform. The prototype shows the efficiency of our approach in terms of finding possible cloud configurations in reasonable time. The prototype is flexible since it enables an easy reconfiguration of the cloud customer optimization objectives.

Robotic applications are becoming ubiquitous. They are widely used in several areas (e.g., healthcare, disaster management, and manufacturing). However, their provisioning still faces several challenges such as cost and resource usage efficiency. Cloud computing is an emerging paradigm that may aid in tackling these challenges. It has three main facets: Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). This paper focuses on the IaaS aspects of robotic applications as cloud computing services. It proposes an architecture that enables cost efficiency through virtualization and dynamic task delegation to robots, including robots that might belong to other clouds. Overlays and RESTful Web services are used as cornerstones. A prototype is built using LEGO Mindstorms NXT as the robotic platform, and JXTA as the overlay middleware. Related work is reviewed, the functional entities and interfaces of the architecture are described, and the prototype architecture is presented along with the implemented scenario.

Platform-as-a-Service (PaaS) should support the design, deployment, execution, test and monitoring of native elastic systems constructed from elastic service units based on multi-dimensional elasticity requirements. In this paper, we discuss fundamental building blocks for enabling multi-dimensional elasticity programming of software-defined elastic systems. We describe CoMoT, a novel PaaS for elasticity in the cloud that is developed based on these fundamental building blocks.

Platform as a Service (PaaS) systems fully exploit the potential of elastic Cloud computing Infrastructure as a Service (IaaS) layer, by providing computational platforms for the developers characterized by a set of frameworks and runtimes. In these scenarios, the developers could focusing only on the implementation side of web applications without having to deal with configuration of the environment the web apps require for running properly. Services represent a central point of PaaS systems, providing external features for web applications such as SQL databases, messaging systems, and any kind of external software required by the developer. The monitoring of the availability and the performances of these Services plays an essential role in PaaS environments. The paper tackles above issues focusing on the real use case of the Cloud Foundry PaaS; collected results assess the effectiveness of the proposed monitoring function and confirm its feasibility and low overhead.

Following IT innovations, manual operations have been automated, improving the overall quality of life. This has been possible because an organic topology has been formed among many diverse smart devices grafted onto real life. To provide services to these smart devices, enterprises or users use the cloud. Cloud services are divided into infrastructure as a service (IaaS), platform as a service (PaaS) and software as a service (SaaS). SaaS is operated on PaaS, and PaaS is operated on IaaS. Since IaaS is the foundation of all services, algorithms for the efficient operation of virtualized resources are required. Among these algorithms, desktop resource virtualization is used for high resource availability when existing desktop PCs are unavailable. For this high resource availability, clustering for hierarchical structures is important. In addition, since many clustering algorithms show different percentages of the main resources depending on the desktop PC distribution rates and environments, selecting appropriate algorithms is very important. If diverse attempts are made to find algorithms suitable for the operating environments’ desktop resource virtualization, huge costs are incurred for the related power, time and labor. Therefore, in the present paper, a desktop resource virtualization clustering simulator (DRV-CS), a clustering simulator for selecting clusters of desktop virtualization clusters to be maintained sustainably, is proposed. The DRV-CS provides simulations, so that clustering algorithms can be selected and elements can be properly applied in different desktop PC environments through the DRV-CS.

The thesis is focused on the introduction to issue of cloud computing and cloud computing services. The main objective is to categorization of services in accordance to several parameters, which tends as crucial factors of choosing cloud computing services. The conclusion is achieved by analyzing various cloud computing services and subsequent synthesis of the most important parameters. The results of this thesis are the definitions of relevant categories common for the distributed models of service. According to these a potential consumer may choose from provided cloud computing services. Individual categories are divided by their technological or organizational characteristics. The categories are further defined from the infrastructure-as-a-service model view. The thesis is divided into a theoretical and a practical part. While the theoretical part describes basic terminology, characteristics and division of models, the practical part is defined by three sections. The first section contains the definitions of the most important categories with given parameters of distribution models. In the second section, categories from the infrastructure-as-a-service view are defined. In the last section, an analysis of globally accessible services focused on the infrastructure-as-a-service is provided.

In many scientific and engineering areas there are emerging software services available over the Web. The reason for deploying such services in the Cloud is either to reduce the operational costs or to support the peaks in their usage profiles. The algorithms employed in such services are usually result of a long term research and technology development work, so it is beneficial to reuse those critical application parts when developing new Cloud applications. This paper investigates the possibilities to introduce a Model Driven Architecture (MDA) for the Cloud computing domain, which would support composition, customization, flexibility, maintenance and reusability of Cloud application components in the particular case of scientific and engineering applications. The underlying middleware technology of choice is the mOSAIC Platform as a Service (PaaS) solution. This choice is motivated by the fact that in mOSAIC a Cloud application consists of loosely coupled components, which are either generic and provide for key resource types needed by an application (computation, storage, communication) or custom made, e.g. based on existing legacy software. The MDA approach is illustrated through the design and operation of an application for analysis of structures under static loading. It is shown that a relatively simple design can be used to address two application bottlenecks: the varying number of users and the computational complexity of the given problem. The design reduces the necessary application development efforts and the key components can be reused for similar applications.

A discussion of the protocols and methods in use for cloud computing including a definition of cloud computing.

This chapter covers the various cloud service models. The three main service models outlined by NIST are Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). We go over these three service models and a few of the newer service models that are starting to be become prominent, including Database as a Service (DbaaS), Desktop as a Service (DaaS), and Security as a Service.

For some time now, with the full support of cloud computing technologies, it has become possible for enterprises of all sizes to access new business opportunities, thus repositioning themselves in the global IT market. Advancements in cloud interoperability, with important developments of platform as a service (PaaS) and cloud management solutions, have enabled an increasing number of cloud services which, in turn, have led to additional requirements for integration at a superior level: the cloud governance. Moreover, current cloud migration patterns suggest that additional mechanisms in cloud services automation and management are required, in close relation with a fully automated support for the lifecycle of cloud services. This chapter discusses existing trends in cloud migration focusing on solutions which facilitate it, with an emphasis on cloud management and cloud governance, and the relationship between them.

The cloud offers several advantages, but until some of its risks are better understood many major players might hold back.

One of the hot topics in computer technology is software as a service, in which vendors host applications on the Internet and provide them via a browser to users, who perform and store their work online. Users thus don't have to worry about developing, hosting, updating, or maintaining applications or storing data. Several vendors have taken the SaaS concept a big step further and now offer platform as a service systems. PaaS systems are generally hosted, Web-based application-development platforms, providing end-to-end or, in some cases, partial environments for developing full programs online. They handle tasks from editing code to debugging, deployment, runtime, and management. In PaaS, the system's provider makes most of the choices that determine how the application infrastructure operates, such as the type of OS used, the APIs, the programming language, and the management capabilities. Users build their applications with the provider's on-demand tools and collaborative development environment.

The cloud computing paradigm promises increased flexibility and scalability. However, in private cloud environments this flexibility and scalability is constrained by the limited capacity. On the other hand, organizations are reluctant to migrate to public clouds because they lose control over their applications and data. The concept of a hybrid cloud tries to combine the benefits of private and public clouds, while also decreasing vendor lock-in. This paper presents PaaSHopper, a middleware platform for hybrid cloud applications that enables organizations to keep fine-grained control over the execution of their applications. Driven by policies, the middleware dynamically decides which requests and tasks are executed in a particular part of the hybrid cloud. We validated this work by means of a prototype on top of a hybrid cloud consisting of a local JBoss AS cluster, Google App Engine, and Red Hat OpenShift. ispartof: pages:2:1-2:1 ispartof: Proceedings of the 12th International Workshop on Adaptive and Reflective Middleware, ARM 2013 - Co-located with ACM/IFIP/USENIX 14th International Middleware Conference, Middleware 2013 pages:2:1-2:1 ispartof: International Workshop on Adaptive and Reflective Middleware location:Beijing, China date:9 Dec - 13 Dec 2013 status: published

Platform as a Service Clouds typically lack direct support for application state management, and traditional state management techniques like clustering are not applicable as PaaS platforms offer little support for changing the underlying platform configuration. In this paper we build upon our earlier work where we proposed a session-state management architecture for Cloud called ReLoC, that uses loosely-coupled services and platform agnostic scalable messaging technology to propagate and save session states. Here, we present an actual implementation of the ReLoC onto a PaaS platform and an empirical evaluation of the original hypotheses of scalability and resilience of the proposed application architecture. We also present the challenges faced in implementing ReLoC on Heroku. The results indicate that ReLoC indeed allows applications to scale well and mitigates failures in individual application instances while maintaining state and hiding such failures from the users. The results also indicate that the performance degradation due to use of ReLoC is minimal and it is thus a promising approach for resilient user state management on PaaS Clouds.

Recent progression in health informatics data analysis has been impeded due to lack of hospital resources and computation power. To remedy this, some researchers have proposed a cloud-based web service patient monitoring system capable of providing offsite collection, analysis, and dissemination of remote patient physiological data. Unfortunately, some of these cloud services are not effective without utilizing next-generation hardware management techniques. In order to make cloud based patient monitoring a reality, this paper shows how leveraging an underlying platform-as-a-service (PaaS) cloud model can provide integration with web service patient monitoring systems while providing high availability, scalability, and security.

Cloud computing has the potential to revolutionize the way systems are developed and marketed. The cloud has become an important research subject in software engineering nowadays. Among the many research gaps related to this new computing model is the lack of portability between cloud platforms, which generates the Data Lock-In. The Data Lock-In is the difficulty in migrating data and applications from a cloud platform to another. This work presents a model-driven approach for promoting cloud portability, in the context of PaaS (Platform as a Service). The initial results indicate that the use of MDE in cloud computing can facilitate cloud adoption, as well as the migration between the different platforms offered in the market.

In today's “era of Tera”, everything is possible in terms of storage and service. The long-held dream of computing as a utility has been achieved in the form of cloud computing. It has transformed the world where large part of IT industry is simplified by Platform as a Service, Software's are developed and rented more attractively in the form of Development as a Service, Software as a Service. It has shaped the IT industry with its Infrastructure as a Service. When all such services are provided to client on demand, security becomes a major concern. Since Cloud is a Data Centre there are conceivable chances of attacks on it. Cloud behaves like a group of interconnected systems since it is run on the backdrop through Distributed systems. Various attacks like DOS, DDOS, Malware Injection attack, Man-In-The-Middle attacks are possible. This paper discusses various Mining attacks that are possible on a Cloud and provides a solution by using a Secure Distributed approach. We use WEKA to predict the patterns in a single cloud and by using Cloud Data Distributor with a secure distributed approach we provide an effective solution that prevents such mining attacks on Cloud thus making the Cloud a secure platform for service and storage.

This paper introduces an architecture offering authorization as a service for smart grids environments founding on the two standards XACML and SAML. A software prototype is deployed with the Platform as a Service (PaaS) framework Appscale. Appscale is an open source implementation of Google's App Engine framework enabling the execution of applications in a cloud environment without the need to take care of the issues arising out of the distributed computing model. Evaluation of the prototype focuses on its scalability. Load tests are run against the system in various configurations with all distributed databases offered by Appscale. The recorded results are ranging from a very unstable behavior to the awaited scalability dependent on the number of nodes used for App-scale deployment.

Resource identification in massive deployed distributed systems, like the cloud environments, is a common problem when multiple types of resources need to be managed. This is the case of platform as a service (PaaS) where the platform offers different types resources that are deployed in heterogeneous systems. While most of the solutions on the market follow a predefined architecture using common naming services in a centralized manner this paper proposes a new approach based on a distributed naming and resource identification service. The proposed solution allows a client to consume or communicate with a resource without having to deal with resource location or discovery protocols.

Different PaaS (Platform as a Service) Clouds offer different set of capabilities and services and have different constraints on types of application that can be hosted on their platforms. Migrating existing enterprise applications to such platforms thus is non-trivial and needs a thorough assessment of the system to be migrated. In this paper, we present a novel approach for automated assessment of applications for migration to a target PaaS platform. We take an approach of systematically studying typical external technical services that different types of applications need in a traditional non-PaaS deployment and evaluate support for each of services in major PaaS environments. We have created rich sets of repositories each for technical capabilities and services used by typical enterprise applications as well as for the different technical services exposed for use by PaaS platforms along with their limitations and caveats. Using these repositories, our approach analyses the source code as well as the configuration files to recursively extract the services it requires and then tries to map them to a target PaaS platform. The approach results in a detailed report of the parts of the system that can migrate as-is, which need some changes, as well as those which can't be migrated at all due to the limitations of the chosen PaaS platform.

The Platform as a Service (PaaS) model promotes the development and deployment of applications on top of middleware solutions offered by the provider. Deploying an application in this model entails both the deployment of the application on top of the platform, but potentially also the deployment of the middleware components required by the application. Existing works enable the abstraction from the underlying infrastructure and allow for the creation of generic deployment plans for middleware components that automate the deployment of applications. In this paper we propose a middleware-oriented deployment approach that defines how the deployment of middleware components can be defined in a manner that allows to offer them as PaaS building blocks, and enable the automatic deployment of application components on them. We also present an evaluation of our proposal, together with the lessons learned during this activity.

Virtualization is one of the key elements of Infrastructure as a Service (IaaS), Cloud Computing (CC) offerings and private Clouds, and it is increasingly used in portions of the back-end of Platform as a Service (PaaS) and SaaS (Software as a Service) providers as well. This creates new targets for intrusion due to the complexity of access and difficulty in monitoring all interconnection points between systems, applications, and data sets. This raises many questions about the appropriate infrastructure, processes, and strategy for enacting detection and response to intrusion in a Cloud environment. This article discusses the security and the visibility issues of inter-VM traffic and solutions for it within a Cloud environment context, by proposing an approach relying on distributed intrusion detection technique and packet inspection.

Cloud Platform as a Service (PaaS) is a rapidly growing IT paradigm which enables software developers to deploy applications without the burden of software platform maintenance. Currently, the PaaS market is dominated by a few providers that promote incompatible standards. This introduces adoption barriers that prevent the interoperability between heterogeneous PaaS offerings, so software developers are not able to manage distributed applications spanning multiple public/private clouds. In this paper we present a multi-PaaS application management solution as a result of the Cloud4SOA European project that addresses these challenges. To clarify this approach a distributed deployment and cloud bursting scenarios are used.

Elasticity is a key characteristic of cloud platforms enabling resource to be acquired on-demand in response to time-varying workloads. We introduce a new elasticity management framework that takes as input commonly used reactive rule-based scaling strategies but offers in return proactive auto-scaling. The elasticity framework combines reactive and predictive auto-scaling techniques, and we discuss the specification and performance of these individual components. We present a case study, based on real datasets, to demonstrate that our framework is capable of making appropriate auto-scaling decisions that can improve resource utilization compared to that obtained from a purely reactive approach.

In the current cloud era, new cloud skills are required for IT specialists. Educational organizations such as universities need to provide an educational cloud for their students. We have constructed a private educational cloud based on the Ubuntu Enterprise Cloud. The most important feature of our cloud is super saturation, which is defined as allocating more logical resources than actual physical resources. A supersaturated cloud is able to run more than 10times the number of instances than a conventional cloud. Although there is a slight drop in performance, the cost decreases drastically. We propose a Platform as a Service(PaaS) on an Infrastructure as a Service (IaaS) (PoI) method to further improve the utilization of the educational cloud based on super saturation. In this paper, we compare two methods for creating PoI applications, Single Tenant PaaS and MultiTenant PaaS, where the former allows applications to be installed easily, whereas the latter achieves high convergence.

Cloud Computing model has enabled IT organizations to serve the users globally. It gives the services like Platform as a Service, Software as a Service and Infrastructure as a Service without users being much aware of the details in which the services are provided. As in File Access System Service the users are not aware of the locations of the files in Clouds. File access seems to them as a single coherent file system. Considering this aspect, this paper is concerned with an effective service and cost model for providing Cloud Computing service for writing and compiling source code remotely from any hand held device using the distributed service model. According to this model, for providing a service, the service provider may subsequently use the services of other service providers in the Cloud without the awareness of the client. The cost model effectively evaluates the cost which each client pays to each of its service providers for receiving the services. The model is expected to be mutually beneficial to the client and its service provider. The client is paying only for the service it receives and the service provider only provides the service that is requested by the client .The cost is evaluated based on the kind of service provided. The model is also expected to reduce software piracy to a considerable extent.

Cloud computing is a rapidly developing and excellent promising technology. It has aroused the concern of the computer society of whole world. Cloud computing is Internet-based computing, whereby shared information, resources, and software, are provided to terminals and portable devices on-demand, like the energy grid. Cloud computing is the product of the combination of grid computing, distributed computing, parallel computing, and ubiquitous computing. It aims to build and forecast sophisticated service environment with powerful computing capabilities through an array of relatively low-cost computing entity, and using the advanced deployment models like SaaS (Software as a Service), PaaS (Platform as a Service), IaaS (Infrastructure as a Service),HaaS (Hardware as a Service) to distribute the powerful computing capacity to end-users. This paper will explore the background and service models and also presents the existing research issues and implications in cloud computing such as security, reliability, privacy, and so on.

Cloud computing provides network based access to computing and data storage services on a pay per usage model. Cloud provides better utilization of resources and hence a reduced service access cost to individuals. Cloud services include software as a service, platform as a service, and infrastructure as a service. Cloud computing virtually and dynamically distributes the computing and data resources to a variety of users, based on their needs, with the use of virtualization technologies. As Cloud computing is a shared facility and is accessed remotely, it is vulnerable to various attacks including host and network based attacks (Brown 2012, and Grance 2009) and hence requires immediate attention. This paper identifies vulnerabilities responsible for well-known network based attacks on cloud and does a critical analysis on the security measures available in cloud environment. This paper focuses on a nonconventional technique for securing cloud network from malicious insiders and outsiders with the use of network profiling. With network profiling, a profile is created for each virtual machine (VM) in cloud that describes network behavior of each cloud user (an assigned VM). The behavior gathered is then used for determination (detection) of network attacks on cloud. The novelty of the approach lies in the early detection of network attacks with robustness and minimum complexity. The proposed technique can be deployed with minimal changes to existing cloud environment. An initial prototype implementation is verified and tested on private cloud with a fully functional implementation under progress Web of Science art. no. 364575

As one of the three service models of cloud computing, PaaS (Platform as a Service) has gained more and more popularity for its capabilities in optimizing development productivity and business agility. However, the traditional PaaS uses the dedicated infrastructure, which generally leads to the low infrastructure utilization rate. To solve the above problem, PaaS based on IaaS (PoI) emerged, in which IaaS (Infrastructure as a Service) is involved to provide PaaS the infrastructure, to decrease the response time of the infrastructure scale and to increase the utilization of the infrastructure. Because PoI has many characteristics, resource management mechanisms used in the traditional PaaS or IaaS could no longer adopted in PoI. In this paper, an adaptive resource management framework and the corresponding scale-up, scale-down algorithms are brought forward to guarantee the QoS of applications deployed in PaaS platform as well as to decrease the rental cost of VMs from IaaS providers. Experimental results show that the resource management mechanisms proposed in this paper can not only guarantee QoS of all applications, but also improve the utilization rate of the infrastructure, thus to make PoI possess the advantages of both PaaS and IaaS.

Initially intended to support elastic and long-running Web applications, cloud computing paradigm is currently associated with a large variety of services, from infrastructure to software. In this context, the portability of the applications, based on cloud services, even only of infrastructure type, has become a challenge. To overcome this situation, several recent research and development efforts are targeting new methods, tools, and standards to avoid the problems of vendor lock-in. One outcome of such efforts resulted in a special category of open-source platform (as a) services that can be modified by application developers according to their specific needs. Looking deeper into this category, the present chapter provides an analysis of the emerging open-source platform (as a) service and points toward one particular new solution, targeting application developers and sustaining the concept of elastic Web applications as well as of reusable open-source components.

In this paper, we propose a Platform-as-a-Service (PaaS) architecture to facilitate the process of large scale video analysis. The proposed platform provides a unified framework to integrate and configure various video analysis engines, which can then work collaboratively to accomplish video analysis tasks with an user-specified workflow. In addition, users can adaptively adjust the amount of computation resources for speeding up jobs without affecting the dispatched jobs. Finally, we show a real video analysis application which is built on top of the proposed platform to demonstrate its effectiveness.

Platform as a service model has certain obstacles, including data lock-in. It is expensive and time-consuming to move data to the alternative providers. This paper presents data storage options in platform as a service offers and identifies the most common data portability problems between various commercial providers of platform as a service. There are differences among their storage models, data types, remote APIs for data manipulation and query languages. Representing data models of platform as a service and data mappings by means of ontology can provide a common layer to achieve data portability among different cloud providers.

Customers of Platform as a Service providers are unable to evaluate the risk of their provider going bankrupt. Lacking this information, businesses are effectively putting their critical business services in jeopardy. In this paper, we present a method to evaluate the ecosystem health of eight different PaaS providers. The results of our research enable businesses and individuals to make an informed decision on what PaaS providers to do business with. Additionally, the PaaS providers themselves are given insight into the current state of their ecosystem compared to competitors.

Mestrado em Gestão de Sistemas de Informação O Modelo de Cloud Computing encontra-se, neste momento, em mutação acelerada e com relevante destaque, análise e implementação no campo dos sistemas de informação, assumindo relevância científica e empresarial. Esta investigação surgiu com o objetivo de responder a um conjunto encadeado de questões relativas a: Qual a utilização atual de serviços de public cloud computing nas seguradoras nacionais a operar em Portugal? Como avaliam os benefícios desse modelo de public cloud? Quais as intenções de utilização desses serviços no triénio de 2013 a 2015? E se essas indicações de utilização, a existirem, pressupõem um investimento da área de sistemas e tecnologias de informação? Neste sentido, este trabalho tem como finalidade caraterizar qual a realidade atual e indicações futuras das empresas seguradoras, face à utilização desses serviços e respetivos componentes. O instrumento utilizado nesta pesquisa foi um questionário de perguntas fechadas dirigido aos gestores responsáveis pelos sistemas e tecnologias de informação das seguradoras portuguesas. A análise dos dados foi obtida por uma estatística descritiva e os resultados indicam intenções de crescimento do nível de utilização dos serviços de public cloud computing, nas seguradoras em Portugal. The Model of Cloud Computing is presently in accelerated mutation and with relevant regard in what analysis and implementation in the area of information systems are concerned, assuming scientific and business importance. This study emerged with the goal of answering a series of questions concerning: what the current use of public cloud computing in national insurance companies operating in Portugal is; how they evaluate the benefits of this model of public cloud; what the intended use of these services in the 2013-2015 triennium is; and whether these indications for use, if any, require an investment in the area of systems and information technology. Thus, this study aims to characterize what the current reality and forward-looking statements of insurance companies are towards the use of these services and their components. The instrument used in this study was a questionnaire of closed questions to managers in charge of systems and information technologies of insurance companies. Data analysis was obtained by descriptive statistics and the results indicate intentions on the growth of the level of use of public cloud computing services in Portuguese insurance companies.

This study addresses the emerging phenomena of app stores for packaged software such as enterprise resource planning (ERP) and customer relationship management (CRM) systems. Through employing the technology of app stores, ERP and CRM vendors have been reported as shifting from delivering software as a service (SaaS) to platform as a service (PaaS). Through an in-depth case study of one ERP vendor's app store initiative, the study identifies and discusses instances of negotiated order of the ecosystem. The results show that the introduction of an app store for ERP brings with it the threat of restructuring both the incumbent business model and the power relationships nested in the ecosystem, thus spurring intensified instances of negotiated order. This is discussed in terms of different arenas of conflict for negotiated order.

Platform as a service (PaaS) solutions are changing the way how software is produced, distributed, consumed, and priced. Due to the wide variety of approaches to PaaS and the absence of a formula that represents the drivers of successful platforms, the goal of this paper is to identify developers' preferences on PaaS. An adaptive choice-based conjoint analysis has been performed and was completed by 103 participants. Based on the results, a prioritized list of developers' preferences for PaaS has been created. The results of the survey indicate that, third-party developers' preferences also depend on phase of the software lifecycle in which they are (Development, Distribution, and Operation).

In Chapter 9 you saw how to migrate MongoDB databases to two cloud platforms—MongoHQ and MongoLab. As their names suggest, these platforms are cloud-based, hosted database solutions dedicated to MongoDB, which means that the applications that use these databases must be hosted in another place. But if you don't have such a place, or you want to have the entire application (not just the database) in the cloud, you have to focus more on cloud computing platforms, like OpenShift from Red Hat. As quoted on the www.openshift.com web site, "OpenShift is Red Hat's free, auto-scaling Platform as a Service (PaaS) for applications. As an application platform in the cloud, OpenShift manages the stack so you can focus on your code."

The cloud platform-as-a-service (PaaS) model provides developers with the ability to deploy and manage their applications remotely in the cloud and pay only for actual usage hours. Currently, there is no standard API for PaaS deployment and management; each PaaS provider [e.g., Google AppEngine (GAE), OpenShift (OS), Cloud Foundry (CF), and Windows Azure] has its own proprietary APIs. This lack of standardisation adds a layer of complexity to application deployment and migration between heterogeneous PaaS platforms because of API incompatibility. A standard (generic) PaaS deployment API overcomes the previously mentioned PaaS API heterogeneity. A generic open-source API, namely the COAPS API, has been proposed to support deployment and management of applications on CF and OS PaaS platforms. This work implements COAPS deployment API to include the GAE PaaS. Whereas both CF and OS PaaS platforms use the same application packaging, deploying the same application on GAE requires application repackaging. We evaluated our work using a case study in which the same application is automatically deployed on CF and GAE.

In the present article foreign and domestic experience of integrating cloud computing into pedagogical process of higher educational establishments (H.E.E.) has been generalized. It has been stated that nowadays a lot of educational services are hosted in the cloud, e.g. infrastructure as a service (IaaS), platform as a service (PaaS) and software as a service (SaaS). The peculiarities of implementing cloud technologies by H.E.E. in Ukraine and abroad have been singled out; the products developed by the leading IT companies for using cloud computing in higher education system, such as Microsoft for Education, Google Apps for Education and Amazon AWS Educate have been reviewed. The examples of concrete types, methods and forms of learning and research work based on cloud services have been provided.

Cloud Computing [1,2] is a "utility computing model" (John McCarthy, 1961), that allows the purchase of virtualized hardware (Infrastructure as a Service, IaaS), software platforms (Platform as a Service, PaaS) or applications/functionality (Software as a Service, SaaS) in a pay-as-you-go manner, comparable to the metered purchase of electricity, gas or water. Seen in the past primarily as a means for organizations to increase their flexibility, cloud computing has begun to enter the consumer space by offering solutions to personal computing needs that are based on virtualization e.g. cloud storage. Accessing such cloud services with tablets and smartphones enables user and context aware cloud services resulting in a personal(ized) cloud. This personal cloud allows users to access data and services via their mobile devices which in turn allows time, location and device independent computing. This paper focusses on the infrastructure challenges of enabling the personal cloud and presents an evaluation of our consumer-centric cloud portal (C3P).