Search

In Cloud computing deployments, specifically in the Infrastructure-as-a-Service (IaaS) model, networking is one of the core enabling facilities provided for the users. The IaaS approach ensures significant flexibility and manageability, since the networking resources and topologies are entirely under users’ control. In this context, considerable efforts have been devoted to promoting the Cloud paradigm as a suitable solution for managing IoT environments. Deep and genuine integration between the two ecosystems, Cloud and IoT, may only be attainable at the IaaS level. In light of extending the IoT domain capabilities’ with Cloud-based mechanisms akin to the IaaS Cloud model, network virtualization is a fundamental enabler of infrastructure-oriented IoT deployments. Indeed, an IoT deployment without networking resilience and adaptability makes it unsuitable to meet user-level demands and services’ requirements. Such a limitation makes the IoT-based services adopted in very specific and statically defined scenarios, thus leading to limited plurality and diversity of use cases. This article presents a Cloud-based approach for network virtualization in an IoT context using the de-facto standard IaaS middleware, OpenStack, and its networking subsystem, Neutron. OpenStack is being extended to enable the instantiation of virtual/overlay networks between Cloud-based instances (e.g., virtual machines, containers, and bare metal servers) and/or geographically distributed IoT nodes deployed at the network edge.

Current IaaS (Infrastructure as a Service) cloud service may not satisfy communication QoS (Quality of Service) requirements of delay-sensitive network applications, if there is a significant physical distance between a server of the network application (NetApp server) at a data center and its network application clients (NetApp clients). In order to improve communication QoS of NetApp clients, we propose Server Migration Service (SMS) in this paper. SMS allowsNetApp servers to migrate among different locations in the network (1) to optimally locate themselves in relation to NetApp clients and mitigate the QoS degradation caused by location-related factors (i.e., propagation delays on network links) and (2) to optimally distribute traffic load over routers and processing load over (physical) computers and decrease the energy consumption. We develop a mixed-integer programming model that determines when and to which locations NetApp servers migrate to minimize the total operating cost of SMS, i.e., the sum of the monetary penalty incurred due to QoS violation and energy cost incurred due to energy consumption, while preventing NetApp servers from excessively migrating and adversely impacting QoS of the non-SMS service that share the resource of the substrate network with SMS. Simulation results show that the model developed in this paper achieves up to 42% lower total operating cost of SMS compared to the model that only minimizes the monetary penalty of SMS without considering the energy cost of SMS.

Cloud computing is a community-focused environ-ment that relies on sharing informations, storage, provider, programs & different vital computing sources.In modern-day generation of cloud computing era very helpful for centralized the all-agricultural related statistics financialinstitution (Soil&associated, weather, research,Crop, Farmers, Agriculture advertising and marketing, fertilizers and pesti- cide statistics) inside the cloud. Lots of cloud computing companies have emerged up and there is a large boom within the usage of this provider.. Google, Microsoft, IBM and Amazon have began imparting cloud computing services. The future development of agriculture de- pends how the new technologies consisting of cloud computing are followed with a focal point on farmer wishes. The use of this technologies should help a farmer in terms of accessibility. Latest technological development has through a drastic change in every field and agriculture is no other practices to it. Cloud computing generation impacted sincerely onagriculture area and related services they offer for customers on this paper, also talk Computing model, characteristics, deployment model, cloud agro model, cloud advantages and assignment of cloud computing in agriculture field.

Recommendation systems only provide more specific recommendations to users. They do not consider giving a justification for the recommendation. However, the justification for the recommendation allows the user to make the decision whether or not to accept the recommendation. It also improves user satisfaction and the relevance of the recommended item. However, the IAAS recommendation system that uses advisories to make recommendations does not provide a justification for the recommendations. That is why in this article, our task consists for helping IAAS users to justify their recommendations. For this, we conducted a related work on architectures and approaches for justifying recommendations in order to identify an architecture and approach suitable for the context of IAAS. From the analysis in this article, we note that neither of these approaches uses the notices (IAAS mechanism) to justify their recommendations. Therefore, existing architectures cannot be used in the context of IAAS. That is why,we have developed a new IAAS architecture that deals separately with item filtration and justification extraction that accompanied the item during recommendation generation (Figure 7). And we haveimproved the reviews by adding users’ reviews on the items. The user’s notices include the Documentary Unit (DU), the user Group (G), the Justification (J) and the weight (a); noted A=(DU,G,J,a).

A complex and important task in the cloud resource management is the efficient allocation of virtual machines (VMs), or containers, in physical machines (PMs). The evaluation of VM placement techniques in real-world clouds can be tedious, complex and time-consuming. This situation has motivated an increasing use of cloud simulators that facilitate this type of evaluations. However, most of the reported VM placement techniques based on simulations have been evaluated taking into account one specific cloud resource (e.g., CPU), whereas values often unrealistic are assumed for other resources (e.g., RAM, awaiting times, application workloads, etc.). This situation generates uncertainty, discouraging their implementations in real-world clouds. This paper introduces CloudBench, a methodology to facilitate the evaluation and deployment of VM placement strategies in private clouds. CloudBench considers the integration of a cloud simulator with a real-world private cloud. Two main tools were developed to support this methodology, a specialized multi-resource cloud simulator (CloudBalanSim), which is in charge of evaluating VM placement techniques, and a distributed resource manager (Balancer), which deploys and tests in a real-world private cloud the best VM placement configurations that satisfied user requirements defined in the simulator. Both tools generate feedback information, from the evaluation scenarios and their obtained results, which is used as a learning asset to carry out intelligent and faster evaluations. The experiments implemented with the CloudBench methodology showed encouraging results as a new strategy to evaluate and deploy VM placement algorithms in the cloud. This work was partially funded by the Spanish Ministry of Economy, Industry and Competitiveness under the Grant TIN2016-79637-P “Towards Unifcation of HPC and Big Data Paradigms” and by the Mexican Council of Science and Technology (CONACYT) through a Ph.D. Grant (No. 212677).

El objetivo de este proyecto es crear una aplicación web que permita la gestión de máquinas virtuales en el IaaS de la Universidad de La Laguna. En específico, diseñar el frontend de esta con una interfaz sencilla y funcional. El IaaS de la ULL es un servicio proporcionado a la comunidad universitaria como soporte para la docencia, de forma que tanto profesores como alumnos pueden acceder a ella. Se utiliza la plataforma oVirt para albergar esta funcionalidad. Actualmente, el IaaS se ha estado utilizando como se nombró anteriormente, principalmente para la docencia. Sin embargo, no solo se reduce a eso, sino que también llega a ser usado por los profesores, para sus investigaciones, o el personal de administración y servicios de la universidad, para cualquier prueba que necesiten. Además, es útil para aulas de ordenadores, ya que los alumnos no se ven condicionados por el hardware de los equipos físicos, que normalmente son menos potentes y están más desfasados que los de la nube. Se desarrollará una aplicación web Single Page Application (SPA), basada en el stack MEVN (MongoDB, Express, Vue.js, Node.js) con un diseño centrado en Mobile First, aunque también dispondrá de una versión web. The goal of this project is to create a web application that allows the management of virtual machines in the IaaS of the University of La Laguna. Specifically, the design and implementation of the frontend of this application with a simple and functional interface. The IaaS of the ULL is a service provided to the university community as a support for teaching, so that both teachers and students can access it. The oVirt platform is used to host this functionality. Currently, IaaS has been used as named above, primarily for teaching. However, it is not only reduced to that, but it also comes to be used by the professors, for their research, or the administration and services staff of the university, for any test they need. In addition, it is useful for computer classrooms, since students are not conditioned by the hardware of the physical equipment, which is usually less powerful and more outdated than those in the cloud. A Single Page Application (SPA) web application will be developed, based on the MEVN stack (MongoDB, Express, Vue.js, Node.js) with a design focused on Mobile First, although it will also have a web version.

We introduce the novel technical results of the enhanced logging system for customer virtual machines (VMs) in an Infrastructure as a Service (IaaS) cloud. The main contribution is that the enhanced system can work with a better system's accuracy and speed, with the simplicity of the design and implementation. We measure the accuracy of the unenhanced logging system, then find a quick solution to enhance the system based on the results of the measurement. To measure and enhance the unenhanced system, we increase the main memory and CPU cores of the VMs then collect the accuracy results from each increment configuration. We analyze the results and propose to use the taskset tool to enhance the accuracy of the system. Found three main findings include: firstly, the accuracy of the enhanced system is about 20% on maximum better than the unenhanced one; the enhanced system accuracy becomes 100%; lastly, the enhanced system can detect a file with the smaller file size as almost 12% smaller. The findings can be a basis to design the logging systems in an IaaS cloud, to decrease hardware and energy investment. To the best of our knowledge, the contribution and findings are not in the literature.

Failure Prediction has long known to be a challenging problem. With the evolving trend of technology and growing complexity of high-performance cloud data centre infrastructure, focusing on failure becomes very vital particularly when designing systems for the next generation. The traditional runtime fault-tolerance (FT) techniques such as data replication and periodic check-pointing are not very effective to handle the current state of the art emerging computing systems. This has necessitated the urgent need for a robust system with an in-depth understanding of system and component failures as well as the ability to predict accurate potential future system failures. In this paper, we studied data in-production-faults recorded within a five years period from the National Energy Research Scientific computing centre (NERSC). Using the data collected from the Computer Failure Data Repository (CFDR), we developed an effective failure prediction model focusing on high-performance cloud data centre infrastructure. Using the Auto-Regressive Moving Average(ARMA), our model was able to predict potential future failures in the system. Our results also show a failure prediction accuracy of 95%, which is good. We thus believe that our strategy is practical and can be adapted to use in existing real-time systems.

Cloud Computing strives to be dynamic as a service oriented architecture. The services in the SoA are rendered in terms of private, public and in many other commercial domain aspects. These services should be secured and thus are very vital to the cloud infrastructure. In order, to secure and maintain resilience in the cloud, it not only has to have the ability to identify the known threats but also to new challenges that target the infrastructure of a cloud. In this paper, we introduce and discuss a detection method of malwares from the VM logs and corresponding VM snapshots are classified into attacked and non-attacked VM snapshots. As snapshots are always taken to be a backup in the backup servers, especially during the night hours, this approach could reduce the overhead of the backup server with a self-healing capability of the VMs in the local cloud infrastructure. A machine learning approach at the hypervisor level is projected, the features being gathered from the API calls of VM instances in the IaaS level of cloud service. Our proposed scheme can have a high detection accuracy of about 93% while having the capability to classify and detect different types of malwares with respect to the VM snapshots. Finally the paper exhibits an algorithm using snapshots to detect and thus to self-heal using the monitoring components of a particular VM instances applied to cloud scenarios. The self-healing approach with machine learning algorithms can determine new threats with some prior knowledge of its functionality.

Bacteria of the Acinetobacter calcoaceticus - Acinetobacter baumannii (ACB) complex are a frequent cause of the so-called Healthcare-Associated Infections (HAI). During the COVID-19 pandemic, caused by the SARS-CoV-2 virus, coinfections and increased bacterial resistance to antibiotics have been observed. Thus, the present study verified the occurrence and profile of resistance to carbapenems (in the year 2020) and polymyxin B (from October 2020 to March 2021) in bacteria of the ACB complex during the SARS-CoV-2 pandemic in the Hospital School (HE) of the Federal University of Pelotas (UFPel/EBSERH). Two methodologies were applied, the identification and evaluation of bacterial susceptibility by automation (BD Phoenix™), and the evaluation of resistance to polymyxin B using the microdilution panel (CIM POLYMIXIN B, Laborclin). Eighty-one isolates belonging to the ACB complex were identified, 69.1% (56) of the species A. baumannii, and 30.9% (25) of other species of the ACB complex. An increase in resistance to carbapenems from 75% in 2019 to 94.3% in 2020 was observed. Among the bacteria of the ACB complex resistant to carbapenems, 4 of them were resistant to polymyxin B. The bacteria of the ACB complex resistant to carbapenems were more frequent in the COVID-19 ICU, representing 44.9% in relation to other units. These resistant isolates were obtained from tracheal aspirate and blood samples. The data obtained reveal an increase in resistance to carbapenems, in addition to a higher incidence of positive tracheal aspirate for bacteria of the ACB complex in patients diagnosed with COVID-19, which may be related to Pneumonia Associated with Mechanical Ventilation (VAP). Las bacterias del complejo Acinetobacter calcoaceticus - Acinetobacter baumannii (ACB) son una causa frecuente de las llamadas Infecciones Asociadas a la Atención de la Salud (IAAS). Durante la pandemia de COVID-19, causada por el virus SARS-CoV-2, se han observado coinfecciones y una mayor resistencia bacteriana a los antibióticos. Así, el presente estudio verificó la ocurrencia y perfil de resistencia a carbapenémicos (en el año 2020) y polimixina B (de octubre de 2020 a marzo de 2021) en bacterias del complejo ACB durante la pandemia SARS-CoV-2 en el Hospital Escuela (HE) de la Universidad Federal de Pelotas (UFPel/EBSERH). Se aplicaron dos metodologías, la identificación y evaluación de la susceptibilidad bacteriana por automatización (BD Phoenix™), y la evaluación de la resistencia a la polimixina B mediante el panel de microdilución (CIM POLYMIXIN B, Laborclin). Se identificaron 81 bacterias pertenecientes al complejo ACB, 69,1% (56) de la especie A. baumannii y 30,9% (25) de otras especies del complejo ACB. Se observó un aumento de la resistencia a los carbapenémicos del 75% en 2019 al 94,3% en 2020. Entre las bacterias del complejo ACB resistentes a los carbapenémicos, 4 de ellas eran resistentes a la polimixina B. Las bacterias del complejo ACB resistentes a los carbapenémicos eran más frecuentes en la UCI COVID-19, representando el 44,9% en relación a otras unidades. Las bacterias resistentes se obtuvieron de aspirado traqueal y muestras de sangre. Los datos obtenidos revelan un aumento de la resistencia a los carbapenémicos, además de una mayor incidencia de aspirado traqueal positivos para bacterias del complejo ACB en pacientes diagnosticados de COVID-19, lo que puede estar relacionado con Neumonía Asociada a Ventilación Mecánica (NAV). Bactérias do complexo Acinetobacter calcoaceticus - Acinetobacter baumannii (ACB) são causa frequente das chamadas Infecções Relacionadas à Assistência à Saúde (IRAS). Durante a pandemia de COVID-19, causada pelo vírus SARS-CoV-2, coinfecções e aumento da resistência bacteriana aos antibióticos têm sido observados. Assim, o presente estudo verificou a ocorrência e perfil de resistência aos carbapenêmicos (no ano de 2020) e a polimixina B (de outubro de 2020 a março de 2021) em bactérias do complexo ACB, durante a pandemia de SARS-CoV-2, no Hospital Escola (HE) da Universidade Federal de Pelotas (UFPel/EBSERH). Duas metodologias foram aplicadas, a de identificação e avaliação da suscetibilidade bacteriana por automação (BD Phoenix™), e avaliação da resistência a polimixina B utilizando painel de microdiluição (CIM POLIMIXINA B, Laborclin). Oitenta e um isolados pertencentes ao complexo ACB foram identificados, sendo 69,1% (56) da espécie A. baumannii e 30,9% (25) de outras espécies do complexo ACB. Foi observado um aumento da resistência aos carbapenêmicos de 75% em 2019, para 94,3% em 2020. Dentre as bactérias do complexo ACB resistentes aos carbapenêmicos, 4 delas foram resistentes também a polimixina B. As bactérias do complexo ACB resistentes aos carbapenêmicos foram mais frequentes na UTI COVID-19, representando 44,9% em relação as outras unidades. Esses isolados resistentes foram obtidos de amostras de aspirado traqueal e sangue. Os dados obtidos revelam um aumento da resistência aos carbapenêmicos, além de uma maior frequência de bactérias do complexo ACB obtidas de aspirado traqueal de pacientes diagnosticados com COVID-19, o que pode estar relacionado a quadros de Pneumonia Associada a Ventilação Mecânica (PAVM).

In Infrastructure-as-a-Service (IaaS) clouds, the development process of a ready-to-use and reliable infrastructure might be a complex task due to the interconnected and dependent services that are deployed (and operated later on) in a concurrent way on virtual machines. Different timing conditions may change the overall initialisation method, which can lead to abnormal behaviour or failure in the non-deterministic environment. The overall motivation of our research is to improve the reliability of cloud-based infrastructures with minimal user interactions and significantly accelerate the time-consuming debugging process. This paper focuses on the behaviour of cloud-based infrastructures during their deployment phase and introduces the adaption of a replay, and active control enriched debugging technique, called macrostep, in the field of cloud orchestration in order to provide support for developers troubleshooting deployment-related errors. The fundamental macrostep mechanisms, including the generation of collective breakpoint sets as well as the traversal method for such consistent global states, have been combined with the Occopus cloud orchestrator and the Neo4J graph database. The paper describes the novel approach, the design choices as well as the implementation of the experimental debugger tool with a use case for validation purposes by providing some preliminary numerical results.

International audience; In the field of cloud computing, Infrastructure as a Service (IaaS) provides virtualized on-demand computing resources on a pay-per-use model. IaaS Cloud differ from traditional mutualized infrastructures in that the resources can be dynamically claimed and released, and the real hardware infrastructure is unknown to its users. These properties drastically changes the way resource pro-visioning and job scheduling can be addressed by the user because i) the large number of jobs and resources to handle becomes rapidly overwhelming for human operators, and ii) the real performances of the platform should be inferred from observations to make robust scheduling decisions. In order to optimize the resources usage by the client, we advocate the need for brokers on the client-side. This article presents our work based on Schlouder, a broker of IaaS cloud resources able to provision and schedule independent jobs or static work-flows according to strategies chosen by the client. Further, we advocate that simulation can be a precious auxiliary to help the user to choose between provi-sioning strategies. Schlouder brings a unique feature which is to predict through simulation the makespan and cost of executions under various strategies. The contribution of this work is twofold. First, it presents the broker, available as an open source project, in which new provisioning strategies can be plugged in by third parties. The effectiveness of the tool is demonstrated through experiments involving actual applications and platforms. Second, we show that simulation produces accurate predictions making this feature a helpful means for the user to choose the appropriate strategy.

Cloud computing is regarded as massively extensible, an on-demand configurable resources computing model. It approaches the cloud infrastructure in a distributed rather than dedicated infrastructure where users can have full access to the extensible, reliable resources. Data generated by IoT attached objects is high, cloud is a key to store the incalculable data generated by these attached devices and it is the forward stepped towards the green computing, it removes the setups and installation steps as the cloud user accessing the hardware resources co-exist on different platform in distributed way. Cloud computing environment furnished a great flexibility and availability of computing resources at a very lower cost. This arriving technology opens a new era of e-services in different disciplines. In this paper, we seen cloud computing with its applications, most common Cloud Service Provider such as Google, Microsoft, Amazon, HP, and Sales force and we present innovative applications for cloud computing in Enterprise Resource Planning.

“The interesting thing about cloud computing is that we’ve redefined cloud computing to include everything that we already do.” - Larry Ellison Cloud computing is an emerging field that is expected to change the entire information technology processes and IT market in the future. It is changing how we develop, deploy, and use the information technology and the infrastructure that it runs on. Cloud Computing can be defined as Internet-based computing in which virtually shared servers that are data centers provide software, platform, infrastructure, policies and many resources. Clouds can be classified in various types: Public, Private, Hybrid and Virtual Private. In this paper we will understand the Different Classifications of Clouds – IaaS, PaaS, SaaS – Public, Private, Community, Hybrid and also match Cloud Providers to Our Needs – Amazon, Google, Microsoft.

The Cloud offers enhanced flexibility in the management of resources for any kind of application while it promises the reduction of its cost as well as its infinite scalability. In this way, due to these advantages, there is a recent move towards migrating business processes (BPs) in the Cloud. Such a move is currently performed in a manual manner and only in the context of one Cloud. However, a multi- & cross-Cloud configuration of a BP can be beneficial as it can allow exploiting the best possible offers from multiple Clouds and enable to avoid the lock-in effect by also having the ability to deploy different instances of the BP in different Clouds close to the locations of BP customers. In this respect, this article presents a novel architecture of an environment which realises the vision of multi-Cloud BP provisioning. This environment involves innovative components which support the cross-level orchestration of cloud services as well as the cross-level monitoring and adaptation of BPs. It also relies on a certain language called CAMEL which has been extended to support the adaptive provisioning of multi-Cloud BPs.

This work reports on the development details and results of an experimental setup for the localization of the attendants of a music festival. The application had to be reporting in real-time the asymmetric crowd density based on the Received Signal Strength Indicator (RSSI) between the attendants’ smartphones and an experimental installation of 24 WiFi access points. The impermanent nature of the application led to the implementation of a cloud-based solution, called “STRAND”. STRAND is based on Node.js components, which communicate through websockets, collect, process and exchange data and continuously report the produced information to the end-user. To cope with the near real-time requirements, and the volatility of the crowd concentration density, STRAND horizontally scales the trilateration component, i.e. the component that estimates the user location based on distance measurements. STRAND was tested during the festival days in July 2018 and the results show a system that copes with very high loads and achieves the temporal and accuracy requirements the were set.

Cloud technology is rapidly substituting classic computing solutions, and challenges the community with new problems. In this paper we focus on controllers for cloud application elasticity, and propose a novel solution for self-adaptive cloud controllers based on Kriging models. Cloud controllers are application specific schedulers that allocate resources to applications running in the cloud, aiming to meet the quality of service requirements while optimizing the execution costs. General-purpose cloud resource schedulers provide sub-optimal solutions to the problem with respect to application-specific solutions that we call cloud controllers. In this paper we discuss a general way to design self-adaptive cloud controllers based on Kriging models. We present Kriging models, and show how they can be used for building efficient controllers thanks to their unique characteristics. We report experimental data that confirm the suitability of Kriging models to support efficient cloud control and open the way to the development of a new generation of cloud controllers.

Exploiting resources belonging to multiple cloud providers in an efficient way is still an open issue for distributed computing. Scheduling algorithms based on heuristic, probabilistic, queue theory, or complex soft computing methods are suitable to tackle the heterogeneity and dynamism present in cloud federations. Nevertheless, the available brokering tools are focused on the deployment of services on-demand. The systems able to accomplish high-throughput calculations, such as the pilot-job systems, do not support the inclusion of these algorithms due to their lack of adaptability. The recent implementation of cloud drivers for the GWpilot framework allows developers to profit from its flexibility, compatibility and scheduling features. Moreover, the framework allows the personalised characterisation of cloud resources that those algorithms require, overcoming their lack of trustworthiness in the information provided by the cloud services. In this work, a simple model together with a methodology to couple scheduling software with GWpilot is presented. To demonstrate the suitability of the approach, a legacy self-scheduler specialised on reliable executions in dynamic environments has been stacked and tested on the EGI FedCloud infrastructure with the Nagano legacy application

The Cloud computing paradigm has revolutionised the computer science horizon during the past decade and has enabled the emergence of computing as the fifth utility. It has captured significant attention of academia, industries, and government bodies. Now, it has emerged as the backbone of modern economy by offering subscription-based services anytime, anywhere following a pay-as-you-go model. This has instigated (1) shorter establishment times for start-ups, (2) creation of scalable global enterprise applications, (3) better cost-to-value associativity for scientific and high performance computing applications, and (4) different invocation/execution models for pervasive and ubiquitous applications. The recent technological developments and paradigms such as serverless computing, software-defined networking, Internet of Things, and processing at network edge are creating new opportunities for Cloud computing. However, they are also posing several new challenges and creating the need for new approaches and research strategies, as well as the re-evaluation of the models that were developed to address issues such as scalability, elasticity, reliability, security, sustainability, and application models. The proposed manifesto addresses them by identifying the major open challenges in Cloud computing, emerging trends, and impact areas. It then offers research directions for the next decade, thus helping in the realisation of Future Generation Cloud Computing., Comment: 51 pages, 3 figures

With an increasing number of cloud computing offerings in the market, migrating an existing computational infrastructure to the cloud requires comparison of different offers in order to find the most suitable configuration. Cloud providers offer many configuration options, such as location, purchasing mode, redundancy, and extra storage. Often, the information about such options is not well organised. This leads to large and unstructured configuration spaces, and turns the comparison into a tedious, error-prone search problem for the customers. In this work we focus on supporting customer decision making for selecting the most suitable cloud configuration-in terms of infrastructural requirements and cost. We achieve this by means of variability modelling and analysis techniques. Firstly, we structure the configuration space of an IaaS using feature models, usually employed for the modelling of variability-intensive systems, and present the case study of the Amazon EC2. Secondly, we assist the configuration search process. Feature models enable the use of different analysis operations that, among others, automate the search of optimal configurations. Results of our analysis show how our approach, with a negligible analysis time, outperforms commercial approaches in terms of expressiveness and accuracy. We support the decision making in migration planning to the cloud.We use Feature Models to describe the configuration space of an IaaS.We automate the search of the most suitable IaaS configuration.Our approach improves the results of commercial applications on Amazon EC2.

Cloud computational platforms today are very promising for execution of scientific applications since they provide ready to go infrastructure for almost any task. However, complex tasks, which contain a large number of interconnected applications, which are usually called workflows, require efficient tasks scheduling in order to satisfy user defined QoS, like cost or execution time (makespan). When QoS has some restrictions – limited cost or deadline – scheduling becomes even more complicated. In this paper we propose heuristic algorithm for scheduling workflows in hard-deadline constrained clouds – Levelwise Deadline Distributed Linewise Scheduling (LDD-LS) – which, in combination with implementation of IC-PCP algorithm, is used for initialization of proposed metaheuristic algorithm – Cloud Deadline Coevolutional Genetic Algorithm (CDCGA). Experiments show high efficiency of CDCGA, which makes it potentially applicable for scheduling in cloud environments.

The paper gives an overview and analysis of software-defined technologies in the context of the actual problems of conventional computer networks. The virtualization process lies at the basis of software-defined network architecture. The basic concepts of software-defined networks are elaborated, as well as their implementation and configuration in cloud environment using OpenStack open-source software with Microsoft Hyper-V hypervisor. The practical part of this research showed that the implementation of a software-defined network into an existing standard network is relatively simple to realize, remaining all the time in open-source framework. All existing network functionalities were held, and it is also possible to provide additional network operations such as traffic monitoring in a completely open-source environment.

This research project examines the differences between software testing practices that are carried out on software that is installed locally (i.e. on premise) versus software that has migrated to a cloud hosted environment. In conjunction with this, focus was placed on determining what methodologies and frameworks are in existence for assisting with software migrations to the cloud. The reason for carrying out this research project was that the transition to cloud computing is becoming more and more mainstream, as a result organisations are required to focus their efforts on how best to move their software to the cloud while ensuring that its functionality remains intact. To determine what software testing differences are apparent and what migration strategies are available, existing literature in this area was reviewed and qualitative data was collected. Once all data was collated, results showed that there were in fact key differences in the complexity of software testing that was required for software that has migrated to the cloud. In addition, no generic strategy was found for carrying out a software migration to the cloud. Based on the findings of this research project, it is paramount that an organisation which plans on migrating any of if its software or infrastructure to the cloud needs to have a clear road map in place prior to any development or migration work commencing. By clearly planning and executing this process, clear testing and validation phases can be put in place which will ensure than an element of precaution and prior validation can be incorporated into the transition to the cloud.

Despite cloud abstractions, data is critical to applications hosted on cloud. Thus, overwhelming data flow also requires database tier to be scaled efficiently and dynamically besides other tiers in cloud platform. However, this is not easy since databases maintain tightly coupled state while promising transactional support. Objective of this paper is to survey scalable DBMS architectures deployed for hosting data-centric applications that are gaining momentum in analytical processing, scientific researches, personalized searches and corporate dealings. This paper reviews scalable architectures and their suitability to host specific classes of applications. Finally it addresses issues in current architectures and presents some future suggestions.

Cloud computing is the delivery of computing as a service rather than a product, whereby shared resources, software, and information are provided to computers and other devices and utilities. IT projects in any learning organization at a strategic board level and not –as before - just. e Learning systems usually require hardware and software resources. Many educational institutions cannot afford such investments. This paper highlight the contribution of E-Learning standards with the Cloud standards and the impact on using cloud computing for e-learning solutions. An analysis for the prominent issues in current e Learning systems through a comprehensive comparison between e Learning systems before and after moving to Cloud Computing environment, using a generic framework for “Cloud-based e Learning systems.

Managing Cloud resources efficiently necessitates effective policies that assign applications to hardware in a way that they require the least resources possible. Applications are first assigned to virtual machines which are subsequently placed on the most appropriate server host. If a server becomes overloaded, some of its virtual machines are reassigned. This process requires a hotspot detection mechanism in combination with techniques that select the virtual machine(s) to migrate. In this work we introduce two new virtual machine selection policies, Median Migration Time and Maximum Utilisation, and show that they outperform existing approaches on the criteria of minimising energy consumption, service level agreement violations and the number of migrations when combined with different hotspot detection mechanisms. We show that parametrising the the hotspot detection policies correctly has a significant influence on the workload balance of the system.

In the last few years, research has been motivated to provide a categorization and classification of security concerns accompanying the growing adaptation of Infrastructure as a Service (IaaS) clouds. Studies have been motivated by the risks, threats and vulnerabilities imposed by the components within the environment and have provided general classifications of related attacks, as well as the respective detection and mitigation mechanisms. Virtual Machine Introspection (VMI) has been proven to be an effective tool for malware detection and analysis in virtualized environments. In this paper, we classify attacks in IaaS cloud that can be investigated using VMI-based mechanisms. This infers a special focus on attacks that directly involve Virtual Machines (VMs) deployed in an IaaS cloud. Our classification methodology takes into consideration the source, target, and direction of the attacks. As each actor in a cloud environment can be both source and target of attacks, the classification provides any cloud actor the necessary knowledge of the different attacks by which it can threaten or be threatened, and consequently deploy adapted VMI-based monitoring architectures. To highlight the relevance of attacks, we provide a statistical analysis of the reported vulnerabilities exploited by the classified attacks and their financial impact on actual business processes., First Online: 08 December 2017

Pricing plays an important role for service provision in cloud computing. In this paper, we investigate price based resource access control in two Monopoly IaaS cloud market, respectively. The two IaaS cloud market is formed by one public cloud service providers (CSPs) and cloud broker (CB), provisioning cloud services to delay-sensitive cloud users (CUs). In the first monopoly cloud market, we treat the public CSP as an M/M/1 queueing system and study this CSP's pricing effect on the equilibrium behaviours of self-interested CUs. We propose two pricing mechanisms with the objective of maximizing revenue and social welfare, respectively. In the second monopoly cloud market, the CB is modelled as an M/M/∞ queueing system, which has infinite capacity to serve a common pool of CUs. We also analyze how pricing affects the equilibrium behaviors of CUs and the revenue-optimal and social-optimal pricing strategies in view of this CSP.

Streaming technology is currently experiencing a great progress. Faster internet more users streaming. Streaming services that exist today there are still weaknesses in both the upload speed, streaming speed and limited types of video extensions that can be played. To resolve these problems then made a video streaming service based local area network with a system of cloud computing that can work effectively in terms of upload speeds, streaming and variations in video formats. Video streaming application is classified as a service IaaS (Infrastructure as a Service Cloud) in cloud computing. On the use of streaming applications the user does not need to convert the video, with the purpose of uploading process can be faster and applications can play a variety of video formats.

International audience; Emerging applications for the Internet of Things (IoT) are complex programs which are composed of multiple modules (or services). For scalability, reliability and performance, modular applications are distributed on infrastructures that support utility computing (e.g., Cloud, Fog). In order to simply operate such infrastructures, an Infrastructure-as-a-Service (IaaS) manager is required. OpenStack is the de-facto open-source solution to address the IaaS level of the Cloud paradigm. However, OpenStack is itself a large modular application composed of more than 150 modules that make it hard to deploy manually. To fully understand how IaaSes are deployed today, we propose in this paper an overall model of the application deployment process which describes each step with their interactions. This model then serves as the basis to analyse five different deployment tools used to deploy OpenStack in production: Kolla, Enos, Juju, Kubernetes, and TripleO. Finally, a comparison is provided and the results are discussed to extend this analysis.

In contemporary IT and Internet society, Cloud computing brings a paradigm shift not only for successfully evolving large distributed software applications but also for delivering a number of innovative services and applications. Cloud computing is an umbrella enveloping several models of service, like SaaS, IaaS, PaaS, TaaS. In particular, software testing in/on/over cloud is the focus of this paper. We see software testing in the Cloud and TaaS as a novel domain-specific approach to software testing. However, the field is still immature and there does not yet exist a clear understanding of its concepts and constituent technologies. In this paper we provide an introductory overview of software testing in the cloud, based also on a systematic search of literature, along with its buzzwords and tools.

Semakin canggih dan berkembangnya teknologi informasi di berbagai aspek kehidupan, meniscayakan perguruan tinggi sebagai institusi pengembang ilmu pengetahuan dan teknologi (IPTEK) untuk merespon positif. Hal ini akan berdampak juga dalam perkembangan perangkar keras yang secara tidak langsung harus mengikuti perkembangan teknologi informasi yang ada sehingga akan dilakukan penambahan perangkat yang akan menyebabkan penambahan biaya untuk membeli perangkat yang baru. Hal tersebut dapat dipenuhi dengan menggunakan teknologi cloud computing. Cloud computing merupakan model komputasi, dimana sumber daya seperti daya komputasi, penyimpanan, jaringan dan perangkat lunak disediakan sebagai laayanan di internet. Sumber daya komputasi tersebut dapat dipenuhi oleh layanan layanan cloud Infrastructure as a Service (IaaS).Infrastructure as a Service tersebut dibangun dengan menngunakan Infrastruktur Cloud Ubuntu. Sistem Operasi yang digunakan adalah Ubuntu Server 12.04 LTS dan serta perangkat lunak yang digunakan untuk membangun infrastruktur adalah OpenStack versi essex. Hasil dari tugas akhir ini adalah terciptanya mesin virtual berdasarkan spesifikasi CPU, memory, dan disk yang dipilih melalui flavor yaitu m1.tiny dengan spesifikasi memori 512 MB, disk 0 GB, ephemeral 0 GB, vCPU 1. Image yang digunakan pada instance adalahsServer Ubuntu 12.04.3 LTS. Kecepatan CPU yang didapat pada mesin virtual tersebut adalah 3000,106 MHz. Penggunaan CPU pada instance dengan nama “webserver” meliputi 0,3% dengan sisa 0,97%, Memori 422764k dari total keseluruhan 503496.

En un mundo donde la transformación digital avanza a un ritmo veloz y aparecen de forma exponencial nuevas soluciones y capacidades tecnológicas, las grandes compañías necesitan sacar más y mejores productos al mercado. Sin embargo, sus pesadas arquitecturas tecnológicas legadas y sus capacidades de integración y escalabilidad no les permiten llegar al mercado en el tiempo y forma deseado. En este contexto, la investigación se centra en la creación de una arquitectura en la nube que permita habilitar, implantar, desarrollar e integrar servicios, soluciones y sistemas transaccionales de distinta naturaleza de forma segura, escalable, resiliente y ágil. La validación de la misma con el desarrollo de 3 patentes en explotación que implementan casos prácticos, ofrece veracidad al modelo propuesto para resolver el problema.

To achieve global competitiveness, governments in developing countries are evolving and implementing information technology policies, to enable their countries participate in the current ICT revolution. One barrier to attaining the education objectives of the policies is inadequate national ICT infrastructure and services. The inadequacy of ICT infrastructure and services is attributed to inadequate government funding, which in turn becomes difficult for education institutions to own and use sophisticated ICT facilities. In spite of inadequate funding, the gap can be reduced if education institutions in developing countries have access to ICT infrastructures available in developed countries. A technology platform that makes this possible is cloud computing. The design for national cloud computing model is proposed in this paper. This model is envisioned as a good strategy for achieving the education-related objectives of the Nigeria's national IT policy. By this model, the government would be responsible for providing high-end computing infrastructure and e- education services to educational institutions in the country. This model will provide affordable access to technologies for e-education, enabling more collaboration, and better education outcomes in developing countries.

In cloud computing environment, Infrastructure as a Service (IaaS) takes the lowest tier in the cloud pyramid where most control and management is needed. IaaS clouds offer IT infrastructure resources for computing, storage and networking to cloud users. In a real cloud data center, there are physical servers with a large number of virtual machines. These virtual machines are hosted with many heterogeneous applications. In order to optimize the utilization of computing resources and also saving energy consumption of cloud data centers, the applications running on the virtual machines will be migrated either to the same server or to another physical or virtual server. Identifying when it is best to migrate an application in a virtual machine has a direct impact on resource optimization. Performance optimization can be best achieved by an efficiently monitoring the utilization of computing resources. So, we need a comprehensive intelligent monitoring agent to analyze the performances of virtual machines. In this paper, we propose an agent based resource monitoring system that depicts the CPU and memory utilization. The monitoring agent collects the virtual machine resource usages and displays in a dashboard. Dashboard displays the key performance metrics such as CPU and memory utilization. The statistical report of dashboard provides information to cloud administrator for resource optimization.

Flight data recorders (FDRs, or black boxes) generate data that is collected on an embedded memory device. A well-known difficulty with these devices is that the embedded memory device runs out of space. To avoid getting into this problematic situation, the software of the FDR is designed to operate in a watchful mode, constantly working to minimize the use of memory space; otherwise a larger FDR would be needed. However, larger FDRs can be a problem because they have very rigorous requirements; thus, enlargement is costly. Outcomes of this research include the recommendation to send FDR data to a remote cloud storage system, so the data memory device will be unbounded.

Cloud computing offers benefits of sharing computing and network resources among multiple mobile network operators. To utilize such benefits, in earlier paper we proposed a platform called telecommunication network as a service (TaaS). Sharing of such resources in cloud technology affects security of whole mobile network in general and software defined network (SDN) & network functions virtualization (NFV) in particular. In this paper, we have analyzed open platform for network functions virtualization (OPNFV) activities and compared them with TaaS concept to find commonalities and see how well it addresses security concerns outlined for TaaS. Through a comparison we show OPNFV security doesn't cover application security at all, however it partially covers data security and considerably covers hypervisor, SDN & NFV security. Therefore, OPNFV security needs to be revised in areas of data and application domain specially to meet the security requirements for TaaS. Furthermore, we conclude that our proposed TaaS platform implements at least current security requirements outlined in OPNFV specification.

The paper deals with the problems of cloud computing applied for industrial applicationson the ground of practical experiences in certain manufacturing corporation. The main part of paperis orientated to proposal of the numerical model on the base of infrastructure as a service (IaaS) and its mathematical description. In addition the model has been extended to include the requirements of mission critical systems with real time behaviour and fail-safe features. The models were realised via virtualisation software Hypervisor which creates a group of available virtual resources through physical infrastructure, which can be offered to customers. Proposal solution enables to create a proper sizeof cloud infrastructure for hardware provisioning according to customer requirements.

To kickstart the process of morphing Messina into a "smart" city, an explicit mission for the crowdfunded #SmartME project, it is essential to set up an infrastructure of smart devices embedding sensors and actuators, to be scattered all over the urban area. An horizontal framework coupled with the Fog computing approach, by moving logic toward the "extreme" edge of the Internet where data needs to be quickly elaborated, decisions made, and actions performed, is a suitable solution for data- intensive services with time-bound constraints as those usually required by citizens. This is especially true in the context of IoT and Smart City where thousands of smart objects, vehicles, mobiles, people interact to provide innovative services. We thus designed Stack4Things as an OpenStack-based framework spanning the Infrastructure-as-a-Service and Platform-as-a-Service layers. We present some of the core Stack4Things functionalities implementing a Fog computing approach towards a run- time "rewireable" Smart City paradigm, by outlining node management and contextualization mechanisms, also describing its usage in terms of already supported and developed verticals, as well as a specific example related to environmental data collection through #SmartME.

This document reports the experience acquired from using the Microsoft Azure cloud Infrastructure as a Service (IaaS) within the distributed computing environments of the LHC experiments. The activity has been conducted in the framework of a joint collaboration between Microsoft and CERN-IT

Resume La securite des Clouds est un aspect essentiel qui n’est pas forcement aborde selon le point de vue de l’utilisateur. En particulier, sur une plate-forme de type Infrastructure-as-a-Service (IaaS), il est actuellement impossible pour un utilisateur de certifier de maniere fiable et securisee que l’environnement qu’il a deploye (typiquement sous forme d’une machine virtuelle) est toujours dans un etat qu’il juge integre et operationnel. Cet article s’attelle a cette tâche en proposant CertiCloud, une plate-forme Cloud de type IaaS qui exploite les concepts developpes dans le cadre du Trusted Computing Group (TCG) mais aussi les elements materiels que sont les Trusted Platform Module (TPM) pour offrir a l’utilisateur un environnement securise et securisant. Ces deux aspects sont garantis par les deux protocoles TCRR (TPM-based Certification of a Remote Resource) et VerifyMyVM qui sont a la base de CertiCloud. Quand le premier permet de certifier l’integrite d’une machine distante et d’echanger une clef de chiffrement symetrique, le second permet a l’utilisateur de s’assurer dynamiquement et a la demande de l’integrite de sa machine virtuelle executee sur les ressources de CertiCloud. Ces deux protocoles etant les briques de base de notre plate-forme, une attention toute particuliere a ete apportee a leurs elaborations. A cet effet, ils ont ete valides avec succes par AVISPA [1] et Scyther [9], deux outils de reference dans le domaine de la verification automatique des protocoles de securite (cette analyse est presentee dans cet article). Ensuite, la plate-forme CertiCloud est detaillee : outre les protocoles TCRR et VerifyMyVM, elle propose le stockage securise des environnements utilisateurs et leurs executions a travers un framework de virtualisation reprenant l’hyperviseur Xen. Quand les ressources physiques sont certifiees par TCRR, l’utilisateur peut utiliser a la demande le protocole VerifyMyVM pour s’assurer de l’integrite de son environnement deploye. Un prototype de CertiCloud a ete realise et nous presentons les premiers resultats experimentaux qui demontrent de la faisabilite et du faible surcout de notre approche sur des scenarios classiquement rencontres sur les infrastructures Cloud de type IaaS.

Running computational science applications on the emerging cloud infrastructures requires appropriate programming models and tools. In this paper we investigate the applicability of the component model to developing such applications. The component model we propose takes advantages of the features of the IaaS infrastructure and offers a high-level application composition API. We describe experiments on a scientific application from the bioinformatics domain, using a hybrid cloud infrastructure which consists of a private cloud running Eucalyptus and the Amazon EC2 public cloud. The measured performance of virtual machine startup time and virtualization overhead indicate promising prospects for exploiting such infrastructures along with the proposed component-based approach.

International audience; Cloud computing infrastructures are providing resources on demand for tackling the needs of large-scale distributed applications. To adapt to the diversity of cloud infras- tructures and usage, new operation tools and models are needed. Estimating the amount of resources consumed by each application in particular is a difficult problem, both for end users who aim at minimizing their costs and infrastructure providers who aim at control- ling their resources allocation. Furthermore, network provision is generally not controlled on clouds. This paper describes a framework automating cloud resources allocation, deploy- ment and application execution control. It is based on a cost estimation model taking into account both virtual network and nodes managed by the cloud. The flexible provisioning of network resources permits the optimization of applications performance and infrastructure cost reduction. Four resource allocation strategies relying on the expertise that can be cap- tured in workflow-based applications are considered. Results of these strategies are confined virtual infrastructure descriptions that are interpreted by the HIPerNet engine responsible for allocating, reserving and configuring physical resources. The evaluation of this framework was carried out on the Aladdin/Grid'5000 testbed using a real application from the area of medical image analysis.

All the associations are genuine thoughts to receive the cloud computing administrations, seeing its advantages as far as cost, openness, accessibility, adaptability and profoundly computerized procedure of upgrading. Cloud computing upgrade the present capacities progressively without further speculation. Cloud computing is a band of assets, applications, and administrations. With the execution of cloud computing, associations have solid worries about the security of their information. The research focuses on the security issues of cloud services. The AES and RSA algorithms will be verified on five parameters key generation time, encryption execution time, memory usage, file uploading time and file downloading time. The CloudSim simulator will be used to find results that the RSA is performing much better than AES in terms of encryption execution time.

Cloud computing has received a significant amount of attentions from both engineering and academic fields. Designing optimal pricing schemes of cloud services plays an important role for the success of cloud computing. How to set optimal prices of cloud resources in order to maximize these CSPs' revenues in an Infrastructure as a Service (IaaS) cloud market while at the same time meeting the cloud users' demand satisfaction is a challenging problem that CSPs should consider. However, most of the current works on cloud market are performed under the assumption that cloud users are not sensitive to delay, which is not practical. Towards this end, in this paper we study price-based service provision in an IaaS cloud market. Our simulations verify our analysis.

In this paper, we propose a server structure proposal and automatic performance verification technology which proposes and verifies an appropriate server structure on Infrastructure as a Service (IaaS) cloud with baremetal servers, container based virtual servers and virtual machines. Recently, cloud services have been progressed and providers provide not only virtual machines but also baremetal servers and container based virtual servers. However, users need to design an appropriate server structure for their requirements based on 3 types quantitative performances and users need much technical knowledge to optimize their system performances. Therefore, we study a technology which satisfies users' performance requirements on these 3 types IaaS cloud. Firstly, we measure performances of a baremetal server, Docker containers, KVM (Kernel based Virtual Machine) virtual machines on OpenStack with virtual server number changing. Secondly, we propose a server structure proposal technology based on the measured quantitative data. A server structure proposal technology receives an abstract template of OpenStack Heat and function/performance requirements and then creates a concrete template with server specification information. Thirdly, we propose an automatic performance verification technology which executes necessary performance tests automatically on provisioned user environments according to the template., Comment: Evaluations of server structure proposal were insufficient in section 4

© 2016 IEEE.To kickstart the process of morphing Messina into a «smart» city, an explicit mission for the crowdfunded #SmartME project, it is essential to set up an infrastructure of smart devices embedding sensors and actuators, to be scattered all over the urban area. An horizontal framework coupled with the Fog computing approach, by moving logic toward the «extreme» edge of the Internet where data needs to be quickly elaborated, decisions made, and actions performed, is a suitable solution for data- intensive services with time-bound constraints as those usually required by citizens. This is especially true in the context of IoT and Smart City where thousands of smart objects, vehicles, mobiles, people interact to provide innovative services. We thus designed Stack4Things as an OpenStack-based framework spanning the Infrastructure-as-a-Service and Platform-as-a-Service layers. We present some of the core Stack4Things functionalities implementing a Fog computing approach towards a run- time «rewireable» Smart City paradigm, by outlining node management and contextualization mechanisms, also describing its usage in terms of already supported and developed verticals, as well as a specific example related to environmental data collection through #SmartME.

La tecnologia cloud computing s'han convertit en una solució cada cop més habitual per a empreses que volen aprofitar els avantatges que aporta tenir el seu CPD localitzat al cloud, no obstant dur a terme aquesta solució requereix d'un anàlisi previ personalitzat per a cada empresa. Aquest article proposa l'estudi i la presa de decisions en el disseny de l'estructura informàtica d'una empresa que necessita realitzar un canvi en la seva infraestructura. En el cos de l'article es mostrarà un abstracte amb els punts claus que cal tenir en compte en el procés de migració dels serveis locals d'una empresa cap al cloud, una descripció sobre els conceptes bàsics que cal conèixer per realitzar un projecte d'aquestes característiques, s'explicarà com s'ha realitzat la implementació de la solució plantejada i finalment s'extrauran les conclusions obtingudes. La motivació de realitzar aquest treball, ha estat assolir una metodologia de treball i els conceptes globals de les Infraestructures com a servei, per aplicar-los en casos reals d'empreses que requereixin migrar part o la totalitat de la seva infraestructura al cloud. Cloud computing Technology have become a common solution for companies who want to exploit the advantages of locating their data center in the cloud. This solution requires to realize a customized analysis depending on the company. This article proposes the study and the decisions that have to be taken to design the network structure of a company that needs to improve their infrastructure. This article will show an abstract with the key points to consider when a local services migration has to be done, including a description of the basic concepts about cloud computing and the explanation of the proposed solution implementation, finally it will show the conclusions found. The motivation of this project has been to achieve a working methodology and the global concepts about an Infrastructures a service, to apply them in real cases of companies that need to migrate all o part of its infrastructure to the cloud. La tecnología cloud computing se ha convertido en una solución habitual para algunas empresas que quieren aprovechar las ventajas que aporta tener su CPD localizado en la nube, sin embargo, para llevar a cabo esta solución, se requiere de un análisis previo personalizado a la empresa. Este artículo propone el estudio y la toma de decisiones en el diseño de la estructura informática de una empresa que necesita realizar un cambio en su infraestructura. En el cuerpo del artículo se mostrará un guión con los puntos clave que hay que tener en cuenta en el proceso de migración de los servicios locales de una empresa a la nube, una descripción sobre los conceptos básicos que se necesitan conocer para realizar un proyecto de estas características, se explicará también como se ha realizado la implementación de un caso de uso planteado y finalmente se mostrarán las conclusiones extraídas. La motivación de realizar este trabajo ha sido alcanzar la metodología de trabajo y los conceptos globales de las infraestructuras como servicio para aplicarlos en escenarios reales de empresas que requieran migrar una parte o la totalidad de su infraestructura hacia la nube.

The article is focused on the selection criteria applied to the IaaS providers used by the organizations when migrating toward a cloud infrastructure.

Vse več podjetij se odloča za selitev svojih informacijskih storitev v bodisi javni, zasebni ali hibridni oblak. Zmanjševanje stroškov, prilagodljivost in hitrejša izvedba so zgolj nekatere od prednosti, vendar ob tem ne smemo pozabiti na nevarnosti, ki jih tak model prinaša. Ena izmed ključnih ovir pri selitvi storitev v oblak je zaklepanje uporabnikov znotraj ponudnika, saj različni ponudniki ponujajo lastne nestandardizirane formate podatkov in aplikacij. Pomemben faktor pri uporabi lastniških rešitev predstavlja tudi visok strošek licenčnin. V diplomskem delu se zato lotimo odprte tehnološke platforme FIWARE, ki predstavlja odprto alternativo uveljavljenim lastniškim rešitvam za postavitev oblačne infrastrukture. Glavni cilj je vzpostavitev in evalvacija zasebnega oblaka na odprti platformi z namenom nudenja infrastrukture kot storitve. Najprej definiramo koncepte računalništva v oblaku in preučimo tehnologije, ki te koncepte omogočajo, pri čemer se osredotočimo na nudenje infrastrukture kot storitve. Ogledamo si projekt FIWARE in se podrobno spoznamo s komponentami tehnološke platforme. Nato pripravimo načrt ciljne arhitekture in se lotimo integracije posameznih komponent v delujočo oblačno infrastrukturo. Oblačno infrastrukturo preizkusimo tako z uporabniškega kot administratorskega vidika ter analiziramo njeno delovanje. Na koncu izpostavimo ugotovitve in ključne lastnosti te rešitve. More and more companies are choosing to migrate their information technology services to either public, private or hybrid cloud. Cost savings, flexibility and faster time to market are just some of the benefits, but we should not forget the dangers that such a model entails. One of the key barriers to migrating services to the cloud is vendor lock-in as different providers offer their own non-standardized data formats and applications. An important factor in the use of proprietary solutions are also expensive licensing fees. In this thesis we, therefore, examine FIWARE open technology platform, which represents an open alternative to well established proprietary solutions for building cloud infrastructures. The main goal is to build and evaluate an Infrastructure as a Service cloud on an open platform. Firstly, we define the concepts of cloud computing and examine the technologies behind it, where we focus on providing Infrastructure as a Service. We take a look at a FIWARE project and thoroughly examine components of the technology platform. After that we prepare a plan for the target architecture and integrate individual components into a working cloud infrastructure. We test and analyse our cloud infrastructure from the end-user as well as administrator perspectives. Finally, we highlight the findings and key features of this solution.