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Open Cloud Computing Interface (OCCI) is the only open standard for managing any kinds of cloud resources, e.g., Infrastructure as a Service, Platform as a Service, and Software as a Service. However, no model-driven tooling exists to assist OCCI users in designing, editing, validating, generating, and managing OCCI artifacts (i.e., extensions that represent specific application domains and configurations that define running systems). In this paper, we propose the first model-driven tool chain for OCCI called OCCIware Studio. This tool chain is based on a metamodel defining the static semantics for the OCCI standard in Ecore and OCL. OCCIware Studio provides OCCI users facilities for designing, editing, validating, generating, and managing OCCI artifacts. We detail the tooled process to define an OCCI extension. In addition, we show how the cloud user can leverage the generated tooling for this extension to create his own OCCI configurations and manage them in the cloud. We illustrate our paper with the OCCI Infrastructure extensiondefining OCCI-compliant compute, network, and storage resources.

In this paper, we introduce NUBOMEDIA, an open source elastic cloud Platform as a Service (PaaS) specifically designed for real-time interactive multimedia and WebRTC services. NUBOMEDIA exposes its capabilities through simple Application Programming Interfaces (APIs), making possible to deploy and execute developers’ applications. To that aim, NUBOMEDIA combines the simplicity and ease of development of API services with the flexibility of PaaS infrastructures. Once an application is implemented, developers just need to deploy it on top of NUBOMEDIA providing elasticity as a service and reliable communication.

Traditional cloud computing providers enable developers to program and deploy applications in the cloud by using platform as a service (PaaS) providers. Despite the benefits of such an approach, this service model usually comes with a high level of the lock in effect into the service provider. The lock in effect occurs when a software developer needs to change its cloud provider. When this happens, it usually means a major application rewrite, specific for the new PaaS. This paper details the initial results of a project whose goal is to build a PaaS where vendor lock in does not occur. With this PaaS, developers wishing to deploy their applications into the cloud may continue to program using their usual development environments. There are no necessary changes required to make the application PaaS compatible. As a proof of concept, we developed an open source PaaS management application as a regular web application and then deployed it on the cloud.

Main objective of this research work is to improve the checkpoint efficiency for integrated multilevel checkpointing algorithms (IMLCA) and prevent checkpointing from becoming the bottleneck of cloud data centers. In order to find an efficient checkpoint interval, checkpointing overheads has also considered in this paper. Traditional checkpointing methods stores persistently snapshots of the present job state and use them for resuming the execution at a later time. The attention of this research is strategies for deciding when and whether a checkpoint should be taken and evaluating them in regard to minimizing the induced monetary costs. By varying rerun time of checkpoints performance comparisons are which will be used to evaluate optimal checkpoint interval. The purposed fail-over strategy will work on application layer and provide highly availability for Platform as a Service (PaaS) feature of cloud computing.

The distant data centre-centric Internet of Things systems face the latency issue especially in the real-time-based applications. Recently, Fog Computing models have been introduced to overcome the latency issue by utilising the proximity-based computational resources. However, the increasing users of Fog Computing servers will cause bottleneck issues and consequently the latency issue arises again. This paper introduces the utilisation of Mist Computing (Mist) model, which exploits the computational and networking resources from the devices at the very edge of IoT networks. The proposed service-oriented mobile-embedded Platform as a Service framework enables the edge IoT devices to provide a platform that allows requesters to deploy and execute their own program models. The framework supports resource-aware autonomous service configuration that can manage the availability of the functions provided by the Mist node based on the dynamically changing hardware resource availability. Additionally, the framework also supports task distribution among a group of Mist nodes. The prototype has been tested and performance evaluated on the real world devices.

Cloud Computing is becoming a new computing model that organizations are adopting, mainly for the great benefits that presents. Platform as a Service (PaaS), enables the development of modern applications in cloud infrastructures, abstracting developers several infrastructure management issues. Due to the growing number of existing PaaS providers, the selection of a provider whose services are most appropriate to the requirements of an organization is not a trivial problem, considering the variety of options and the absence of appropriate comparable metrics. This work presents a framework for a methodological selection of a PaaS provider, providing suitable metrics to compare heterogeneous PaaS environments offered by existing providers. As an example of utilization of the proposed framework, two PaaS providers were compared.

Cloud services can be consumed using web service calls through the APIs provided by the cloud provider. Although using a fine-grained web-service request allows better flexibility of services, this approach will require service consumers to make multiple service requests to the cloud. The cloud will end up receiving a significantly higher number of requests, lowering the performance and increasing latency. The fine-grain APIs can also leave the data in an inconsistent state and create maintenance problems. Using coarse-grain requests will reduce the load on the server, especially necessary for cloud PAAS (Platform as a service) with governor limits on the number of API requests. In our research, we have proved that encapsulating multiple objects in a single API request will also improve the bandwidth, latency and API consumption for cloud PAAS.

The Internet of Things (IoT) is changing people’s surrounding physical world into an information ecosystem that facilitate our everyday life. Billions of smart objects become data-generating “things” that can sense environmental changes and report their sensed data. Leveraging the huge amount of sensory information is a key issue to realize the IoT solutions in many areas. Adequate technologies are required for data collection, transmission, data processing, analysis, reporting, and advanced querying. In this thesis, an IoT Stream Analytics Platform that supports IoT application and service development is proposed: it provides user applications a way to capture flowing data from multitudes of data sources and provide analytical insights in real time based on user needs. Developers can conveniently build their IoT applications on this platform without having to consider the diversity and complexity of smart devices and their underlying networks.

Muchas de las aplicaciones desarrolladas para las empresas e instituciones demandan una alta inversión en costos y una planificación excesivamente prolongada en el tiempo de entrega. Para brindar una solución, agilizando los entregables y reduciendo costos, se unió conceptos de tecnologías actuales como son la Computación en la Nube y las Metodologías Ágiles. El objetivo es demostrar que las aplicaciones se pueden desarrollar en un tiempo mucho menor a las tradicionales y aproximadamente con la mitad del costo estimado. Para lo cual se realizó una investigación de las aplicaciones que se vienen desarrollando actualmente en la Computación en la Nube de tipo PaaS (Plataforma como Servicio), el concepto teórico y práctico de las Metodologías Ágiles y la unión explosiva de ambos para ofrecer entregables eficientes sin abandonar la calidad que demanda el mercado actual en la realización de aplicaciones. El resultado es demostrar la eficiencia en el desarrollo de aplicaciones uniendo los conceptos de Computación en la Nube y las Metodologías Ágiles (SCRUM)., Many of the applications developed for companies and institutions demand high investment costs and an excessively long planning lead time. To provide a solution, streamlining and reducing costs deliverables, concepts of current technologies such as Cloud Computing and Agile Methodologies joined. The objective to demonstrate that applications can be developed in a much smaller traditional and approximately half of the estimated cost time. For which conducted an investigation of the applications that are being developed today in the Cloud Computing type PaaS (Platform as a Service) , the theoretical and practical concept of Agile Methodologies and explosive bonding of both to provide efficient deliverables without leave the quality required by the current market in the development of applications . The result is to demonstrate the efficiency of application development linking the concepts of Cloud Computing and Agile Methodologies (Scrum).

For PaaS-deployed (Platform as a Service) customer-facing applications (e.g., online gaming and online chatting), ensuring low latencies is not just a preferred feature, but a must-have feature. Given the popularity and powerfulness of Java platforms, a significant portion of today's PaaS platforms run Java. JVM (Java Virtual Machine) manages a heap space to hold application objects. The heap space can be frequently GC-ed (Garbage Collected), and applications can be occasionally stopped for long time during some GC and JVM activities. In this work, we investigated the JVM pause problem. We found out that there are some (and large) JVM STW pauses cannot be explained by application-level activities and JVM activities during GC, instead, they are caused by OS mechanisms. We successfully reproduced such problems and root-cause-ed the reasons. The findings can be used to enhance JVM implementation. We also proposed a set of solutions to mitigate and eliminate these large STW pauses. We share the knowledge and experiences in this writing.

The aim of this work is to obtain information about cloud services and to compare which of them is better or more suitable in different situations. To reach named aim author in this work analyzed tendency of cloud services users in Latvia, compared information about the possibilities using different cloud services. Summarizing achieved research results there were defined general advantages and disadvantages for cloud services and concluded that before to start using cloud services it sow every person must consider various aspects and decide which services is better and more acceptable for him.

In the past few years, the great transmission of theoretical concept of different industries such as E-commerce into real application has been used by cloud computing. Based on cloud features and characteristics those are encouraging small companies that providing their E-commerce products to adopt their development into cloud computing. In order to assist the E-commerce small companies with the right way to start with the basic requirements and upgrading their computing resources as their cloud user base grows with time, herewith the E-commerce as the services model for cloud computing is proposed. The main goal of the proposed model is to integrate the E-commerce as a service enterprise and cloud computing. Cloud computing provide a number of internal services such as software as a service (SaaS), hardware as a service (HaaS), platform as a service (PaaS), infrastructure as a service (IaaS), data as a service (DaaS) and communication as a service (CaaS) beside an external services such as the internet service provider, IT service provider, software developer, system integration provider and hardware suppliers. The paper concluded that integrations of the internal and external services could sustain E-commerce development in cloud environment.

This research examines the Marine Corps’ implementation of its private cloud computing environment into its Enterprise Architecture. Specifically, this analysis reviews the challenges presented in migrating the USMC College of Distance Education and Training’s (CDET) entire portfolio of IT applications to the Marine Corps Enterprise Information Services (MCEITS) cloud data center. This study explores the necessary modifications to CDET’s applications and business processes to make the migration a success, and how the modifications may help CDET realize the intrinsic benefits of cloud computing. The analysis begins by establishing an understanding of the MCEITS' hosting environment and CDET’s system requirements. Next, a review of cloud migration models and lessons learned from a commercial migration case provide context for examining the migration of CDET’s applications. After providing an understanding of CDET’s current As-Is processes, the research focus is on applying the migration guidance to develop and propose To-Be processes for post-migration operations. This research concludes that CDET will benefit from the migration, as MCEITS will become responsible for the maintenance and upkeep of the network operating systems, database management systems, and infrastructure, and for competing data backups. This frees CDET personnel to concentrate on the development of CDET’s applications. Also, the migration will result in a more streamlined change and procurement processes for acquiring computing resources. However, CDET will need to create new processes to facilitate coordination between the organizations. http://archive.org/details/migratingtocloud1094548564 Outstanding Thesis Lieutenant Commander, United States Navy Approved for public release; distribution is unlimited.

Cloud computing delivers almost all of its services including software, user's data, system resources, processes and their computation over the Internet. Cloud computing consists of three main classes; Software as a Service, Infrastructure as a Service and Platform as a Service. Using Software as a Service (SaaS), users are able to rent application software and databases which they then install onto their computer in the traditional way. In the Enterprise Resource Planning (ERP) system, the system service environment changed so as to allow the application of the SaaS in the cloud computing environment. This change was implemented in order to provide the ERP system service to users in a cheaper, more convenient and efficient form through the Internet as opposed to having to set up their own computer. Recently many SaaS ERP packages are available on the Internet. For this reason, it is very difficult for users to find the SaaS ERP package that would best suit their requirements. The QoS (Quality of Service) model can provide a solution to this problem. However, according to recent research, not only quality attributes' identification for SaaS ERP, but also a process for finding and recommending software in the cloud computing environment, has proved to be lacking. In this paper, we propose a QoS model for SaaS ERP. The proposed QoS model consists of 6 criteria; Functionality, Reliability, Usability, Efficiency, Maintainability and Business. Using this QoS model, we propose a Multi Criteria Decision Making (MCDM) system that finds the best fit for the SaaS ERP in the cloud computing environment and makes recommendations to users in priority order. In order to organize the quality clusters, we organized an expert group and got their opinion to organize the quality clusters using Social Network Group. Social Networks can be used efficiently to get opinion by various types of expert groups. In order to establish the priority, we used pairwise comparisons to calculate the priority weights of each quality attribute while accounting for their interrelation. Finally, using the quality network model and priority weights, this study evaluated three types of SaaS ERPs. Our results show how to find the most suitable SaaS ERPs according to their correlation with the criteria and to recommend a SaaS ERP package which best suits users' needs.

Cloud computing, networking, and their related service (CCNS) management including grid computing (as appropriate) have recently emerged out of hypes to viable computing/networking tools for reducing infrastructure deployment and servicemanagement costswithout sacrificing the quality of service/experience (QoS/E). There are many definitions of CC; see for example, IETF Website, http://trac.tools. ietf.org/area/app/trac/wiki/Clouds and NIST website, http://www.nist.gov/itl/cloud/. The concept of CC has since been expanded to cover other types of resources as well. These resources include storage resources (DropBox, Microsoft SkyDrive, Google Drive, etc.), communications resources (software defined networking, Networkingas- a-Service or NaaS, etc.), and others. Consequently, the term CC is being commonly used for applications and services that utilize distributed virtualized computing, communications, storage, and any other resources, in general.

In Cloud Computing age, distributed interaction simulation would encounter many difficulties, especially the WAN-based interaction. A scheme of remodeling the traditional RTI software to be with "Platform as a Service (PaaS)" architecture was proposed. This paper puts forward two different software architectures to adapt to different network environments. Kernel idea is encapsulating the APIs of traditional RTI to be Web Services, deploying and scheduling these Web Services on servers, so, a distributed interaction platform is provided to simulation users on WAN. Users could utilize the services from the platform to execute simulation interaction. Finally, an experiment was carried out to test the time-latency performance of the remodeled software.

Main objective of this research work is to improve the checkpoint efficiency for integrated multilevel checkpointing algorithms and prevent checkpointing from becoming the bottleneck of cloud data centers. In order to find an efficient checkpoint interval, checkpointing overheads has also considered in this paper. Traditional checkpointing methods stores persistently snapshots of the present job state and use them for resuming the execution at a later time. The attention of this research is strategies for deciding when and whether a checkpoint should be taken and evaluating them in regard to minimizing the induced monetary costs. By varying rerun time of checkpoints performance comparisons are which will be used to evaluate optimal checkpoint interval. The purposed fail-over strategy will work on application layer and provide highly availability for Platform as a Service (PaaS) feature of cloud computing.

Software as a service (SaaS)—or, as it is commonly called, cloud computing—is becoming the current choice for software procurement. With cloud computing, computer services are typically provided to users over the Internet—instead of using software products on one's own PC. Companies are now also looking to switch to a similar service, called platform as a service (PaaS). This article explains what PaaS is, and the pros and cons of adopting its use. © 2012 Wiley Periodicals, Inc.

Cloud computing is the new era of technology, it uses virtualization and automation to provide user with self-service computing products that provide infinite scale at low cost. It serves user in many ways such as Infrastructure as a Service (IaaS), Software as a Service (SaaS), Platform as a Service (PaaS) etc. While serving as an IaaS it is inevitable that resources must be provided in an efficient way in order to meet the Service Level Agreement (SLA). This paper mainly addresses challenges, performance issues and techniques for resource allocation in cloud computing.

Cloud computing developers face multiple challenges in adapting systems and applications for increasingly heterogeneous datacenter architectures.

In advancement of cloud brokers for communication between different cloud providers, and the cloud-of-clouds territory denoting the integration of different cloudsincluding clouds offering different abstractions and services (e.g., Infrastructure as a Service vs. Platform as a Service) present new challenges to software developers. Actually, while support for developing specific types of applications to run in different individual cloud infrastructures is slowly becoming acceptable, there is little support for programming applications that run across several clouds or types of clouds. Combination of application, datacenters, and programming techniques in the multi-cloud environment poses numerous difficulties to framework engineers. Diverse cloud suppliers offer distinctive communication abstractions, and applications shows distinctive correspondence designs. By abstracting from hardware addresses and lower-level communication.

With the increasing prevalence and demand of large scale cloudcomputing environment, a researcher has to draw more attentiontowards the services provided by the CLOUD. As the access tothe server is increasing, centralized and distributed computingarchitecture will produce bottlenecks data which affect thequality of cloud computing services and bring the huge supportto users. In this paper we are going to propose certain vitalaspects such as memory utilization, storage capacity to check theefficiency and performance of various clouds in cloudcomputing environment. This is based upon the static data. Theproposed mechanism enables users to access memories invarious systems depending on the predefined criteria. Selectionmethod for accessing the memory of a resource is properlyintroduced in this paper. Our evaluation results show that theaggregation of various clouds is effective in indicating the betterefficiency and also to reduce network traffic sent over cloudnetworks.

Although cloud computing has rapidly emerged as a widely accepted computing paradigm, the research on cloud computing is still at an early stage. Cloud computing suffers from different challenging issues related to security, software frameworks, quality of service, standardization, and power consumption. Efficient energy management is one of the most challenging research issues. The core services in cloud computing system are the SaaS (Software as a Service), PaaS (Platform as a Service), and IaaS (Infrastructure as a Service). In this paper, we study state-of-the-art techniques and research related to power saving in the IaaS of a cloud computing system, which consumes a huge part of total energy in a cloud computing system. At the end, some feasible solutions for building green cloud computing are proposed. Our aim is to provide a better understanding of the design challenges of energy management in the IaaS of a cloud computing system.

Cloud computing has heralded many advantages including self-service, elasticity, pay as you go, improved accessibility to computation resources, and ease of deployment and deployment automation. However, to extend those advantages to a larger audience, higher-level abstractions such as Software as a Service (SaaS) or Platform as a Service (PaaS) are needed. This paper presents Stratos, which is a Platform-as-a-Service based around the principles and design of Service Oriented Architecture (SOA). Furthermore, we introduce the concept of Cloud Native attributes, which we argue are properties essential to extend the benefits of the underlying Cloud to PaaS and SaaS users. We present Stratos as a Cloud Native PaaS offering, discuss the architecture that enables Cloud Native attributes, and discuss scenarios where Stratos can be useful to the end user.

Runtime testing of large-scale systems running in dynamic and distributed environments is a costly and a resource consuming task. With the aim of handling such runtime validation activity in a cost...

In this paper we present the case study of an application of a parallel simulation optimization deployed on a private Cloud. The compute-intensive application uses a Master/Worker model, supporting communication over both Java RMI and Globus Grid Services between the nodes. The Master deploys Workers over a Eucalyptus Cloud using the Nimbus Context Broker for just-in-time configuration and runtime Worker discovery. The computational performance of the Workers under different communication mechanisms and deployment scenarios is presented in an attempt to evaluate the use of Virtual Machines in a Cloud as a tool to achieve application scaling. The deployment of this particular application was crafted to support on-the-fly addition of working nodes. The case study suggests a deployment pattern that shapes some requirements and considerations of a scalable Globus-driven Platform as a Service Cloud. Copyright © 2011 John Wiley & Sons, Ltd.

Cloud computing could offer good business models for small computational science and engineering (CSE) research groups because these groups often do not have enough human resources and knowledge to manage the complexity of computational and data infrastructure for their research, while cloud computing aims to eliminate that complexity from the user. In this paper, we have analyzed current status of supporting tools for small CSE groups to utilize cloud computing. Although cloud computing is perceived as an interesting model, we have identified several issues that prevent a wide adoption of cloud computing from small CSE research groups. We also present recommendations for addressing these issues in order to attract small CSE groups to utilize cloud computing.

This article is for security architects whose companies are moving critical systems to the cloud. Whenever technology architecture changes, it's worth revisiting the assumptions that went into security architecture and design. This is particularly relevant for security and cloud computing; although many organizations rate security as a critical issue in moving to the cloud, few know what to do about it.

AS SOMEWHAT OF a technology-hype curmudgeon, I was until very recently in the camp that believed cloud computing was not much more than the latest marketing-drivem hysteria for an idea that has been around for years. Outsourced IT infrastructure services, aka Infrastructure as a Service (IaaS), has been around since at least the 1980s, delivered by the telecommunication companies and major IT outsourcers. Hosted applications, aka Platform as a Service (PaaS) and Software as a Service (SaaS), were in vogue in the 1990s in the form of application service providers (ASPs). Looking at cloud computing through this perspective had me predicting how many more months it would be before the industry came up with another "exciting" technology with which to generate mass confusion and buzz. However, I have recently been enlightened as to the true potential of cloud computing and have become very excited.

Ein bisher unerreichtes Ziel der entwicklung betrieblicher Softwaresysteme ist die angleichung von it und Organisation. Die aufkommenden Platform-as-a-Service-Angebote (PaaS) bieten das Potenzial, diesem Ziel naher zu kommen. Neben den technischen Herausforderungen mussen jedoch auch die Softwareentwicklungsmethoden den neuen Gegebenheiten angepasst werden. Erst dadurch lassen sich Flexibilitat und Effizienz in der Softwareentwicklung signifikant steigern. Der Artikel stellt eine solche Methode basierend auf einer modernen Prozessplattform vor. Anhand von simulierten Softwareanderungen in einem realen Szenario zeigen wir die Vorteile der neuen Methode gegenuber der klassischen komponentenbasierten Entwicklung. Unser Ziel ist es, dadurch den Graben zwischen Business und IT weiter zu schliesen.

In this paper, we developed a system for large scale on-line interactive game server based on Platform as a Service(PaaS). Small and medium sized game developing companies have various aspects of limitation to launch a large scale on line game site. By using the system proposed in this paper, small and medium sized game developing companies can easily publish their games into market.

Ontologies can be used to describe common cloud functionalities and enable common terminology to assist in cloud interoperability. In this work, we have developed the ontology for resources and operations and the ontology of interoperability problems. The aim is to clearly describe and categorize the existing functionalities, features and specificities of commercial platform asaservice offers. The first ontology also provides data type mappings among different Paa Sstorages and cross-Paa Sdata types used in inputs and outputs of the remote APIoperations to provideacommon layer for information exchange and data migration among different Paa Sproviders. The ontologies were evaluated by tools and by human experts. Furthermore, the ontologies were used in cloud interoperability prototype to show their practical applicability.

In this paper, a modular platform which provides student services for smart educational environment is described. The platform represents a point of mutual integration of various services, such as hosting platform for students? projects, platform for integrating SMS service with students? web applications, Internet of Things platform which enables acquiring data from sensors distributed within the University building and controlling various actuators. Platform is deployed as a part of Smart Learning environment. It is integrated with single sign on service and it uses CAS and Oauth2. REST API is also provided. PHP Symfony framework, relational and non-relational databases are used for deploying the platform. The platform was evaluated and tested.

Cloud Computing is one of the technologies with rapid development in recent years where there is increasing interest in industry and academia. This technology enables many services and resources for end users. With the rise of cloud services number of companies that offer various services in cloud infrastructure is increased, thus creating a competition on prices in the global market. Cloud Computing providers offer more services to their clients ranging from infrastructure as a service (IaaS), platform as a service (PaaS), software as a service (SaaS), storage as a service (STaaS), security as a service (SECaaS), test environment as a service (TEaaS). The purpose of providers is to maximize revenue by their price schemes, while the main goal of customers is to have quality of services (QoS) for a reasonable price. The purpose of this paper is to compare and discuss several models and pricing schemes from different Cloud Computing providers.

This paper addresses the problem of how to architect aspects of an Electronic Marketplace (e-Marketplace) to enable Software SMEs (Small and Medium Scale Enterprises) Engineers to easily discover the most appropriate Platform-as-a-Service (PaaS) offerings available in a marketplace. While there are existing architectural models for e-Marketplaces, these models largely ignore the semantic aspects of the descriptions of offerings in the marketplace. In addition, they provide little support for recommendations and decision making for consumers in the marketplace. These shortcomings make the reuse of existing e-Marketplace architectures inadequate for some categories of services such as PaaS services which are characterised by relatively complex technical specifications. We address this problem by integrating a Semantic Recommendation Layer into a PaaS e-Marketplace architecture. Requirements for this layer were obtained from a series of interviews with Software SME engineers and PaaS providers within the context of a Three-year EU Project. We describe the major components of the Layer and the underpinning recommendation and decision model. Results from this work should contribute to domain-specific architecture for e-Marketplaces.

Different cloud computing service providers offer their customers' services with different risk levels. The customers wish to minimize their risks for a given expenditure or investment. This paper concentrates on consumers' point of view. Cloud computing services are composed of services organized according to a hierarchy of software application services, beneath them platform services which also use infrastructure services. Providers currently offer software services as bundles which include the software, platform and infrastructure services. Providers also offer platform services bundled with infrastructure services. Bundling services prevent customers from splitting their service purchases between a provider of software and a different provider of the underlying platform or infrastructure. In this paper the underlying assumption is the existence of a free competitive market, in which consumers are free to switch their services among providers. The proposed model is aimed at the potential customer who wishes to compare the risks of cloud service bundles offered by providers. The article identifies the major components of risk in each level of cloud computing services. A computational scheme is offered to assess the overall risk on a common scale.

As a lightweight and flexible virtualization technology, container virtualization has been adopted by more and more platform as a service (PaaS) system. With the popularity of container virtualization and PaaS, cloud forensics need to find a way of extracting integrate and reliable data from containers. In this paper, we propose a container forensics framework called DCFF which is designed to acquire data simultaneously from containers running on different hosts and transform forensics data into compatible format centrally.

Cloud Computing allows users to access a shared pool of computing resources which include networks, servers, storage, applications and services. One of the major advantages of cloud is that the resources can be rapidly provisioned. However, many enterprises are still unwilling to move their IT infrastructure to cloud. Major concerns of enterprises are the initial expenditure on capital and the cost of maintenance of the cloud infrastructure which requires a new set of expertise. The huge licensing cost of proprietary cloud solutions is also a major concern. Hence open source cloud solutions are gaining popularity. In this paper we discuss major challenges faced while implementing an on-premise cloud using OpenStack and the solutions developed to overcome the same. The source code availability and strong support from a wide community made us choose OpenStack. The cloud usage model, introduced for better ROI (Return on Investment), which is capable of providing both Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) is also discussed. Our experience proved that irrespective of all the challenges enterprise can save both time and money with the adoption of an on-premise open source cloud with a suitable service model.

Modelling and Simulation is heavily influenced by availability of computational power and resources, to successfully complete simulation tasks. In this paper, we investigate deploying the FLAME framework, the only supercomputing framework that automatically produces parallelisable code on different parallel hardware architectures, on cloud infrastructures. The framework focuses on agent-based modelling (ABM) technique which has presented various challenges in the high-performance computing fields and how these reflect in Cloud environments. Computationally these simulations are extremely complex to program with interconnected software, using massive amount of computational power and architectural challenges. High-performance computing grids have provided solutions to some of these issues, but are still not capable enough to solve most of the issues faced by the modelers. This paper discusses the computational problems of executing these simulations and open challenges. Presenting ABM-as-a-service with a possible framework on how this can be implemented with a platform as a service backend. Computational problems such as memory, processing and time are discussed highlighting the issues for enabling these services for non-computing scientists.

The demand for knowledge extraction has been increasing. With the growing amount of data being generated by global data sources (e.g., social media and mobile apps) and the popularization of context-specific data (e.g., the Internet of Things), companies and researchers need to connect all these data and extract valuable information. Machine learning has been gaining much attention in data mining, leveraging the birth of new solutions. This paper proposes an architecture to create a flexible and scalable machine learning as a service. An open source solution was implemented and presented. As a case study, a forecast of electricity demand was generated using real-world sensor and weather data by running different algorithms at the same time.

In cloud computing, enterprises and individual consumers can have access to storage, computing and bandwidth resources through network terminal, and do not need to install applications. Cloud computing can be divided into three categories: Software as a Service (SaaS) and Platform as a Service (PaaS) and Infrastructure as a Service (IaaS). Eucalyptus is the most widely deployed IaaS cloud service software platform in the world. It builds a cloud service layer as IaaS by using the existing infrastructure. In this article, we built the Eucalyptus cloud platform on the server, and the deployment of software Dev C++ on the Eucalyptus platform. Consumers can have remote access to the software through the Internet without installing the software in the local. Over the last few years, Big Data analysis has attracted huge attention from enterprises and research institutions. Hadoop is considered as one of the most important tools in computing development in order to tackle the Big Data. It is very convenient for Eucalyptus to create and deploy the VM instances which is provided the distributed environment on demand, where the Hadoop applications are going to be executed. So we implement Hadoop platform on Eucalyptus cloud infrastructure, and evaluate the Hadoop applications running on Eucalyptus cloud under different stressing conditions.

HPC applications are widely used in scientific and industrial research, data analytic and visualization, social behavioral studies etc. Most HPC applications require dedicated, available and highly customized resources and environments for computation since they exhibit intense resource utilization. These needs were traditionally provided by clusters and supercomputers which are difficult to setup, manage or operate. While majority of the HPC installations ensure good resource utilization, the reach of these is restricted to few who are members of a specific HPC community. Cloud computing is emerging as a latest computing technology. The on-demand nature of cloud has provoked interest to explore if cloud properties can be useful for HPC setups. This paper is a work in that direction. The prevalent public clouds have accessibility to many and have been explored by the HPC community too. The biggest deterrent identified on these computing platforms for HPC workloads is the virtualization layer used by the cloud systems for resource provisioning. In this paper we propose a Platform-as-a-Service model to build an HPC cloud setup. The key goals for the architecture design is to include features like on-demand provisioning both for hardware as well as HPC runtime environment for the cloud user and at the same time ensure that the HPC applications do not suffer virtualization overheads. The architecture builds the required HPC platform by providing dedicated node or a group of nodes booted with the desired HPC environment without the virtualization layer. Technologies like Wake-on-LAN and network booting are used to achieve this goal. Once the usage of these resources is relinquished, the same nodes are re-deployed for another HPC platform. Thus this architecture merges cloud properties with HPC platforms for delivering effective performance. We show the results of benchmarks used to evaluate performance difference between a virtualized and non-virtualized environment for this observation.

In the last few years, we witnessed a growing interest in interoperability and portability topics within the Cloud Computing area. In fact, most heterogeneous PaaS solutions have been developed with no standard APIs, and with different models and levels of service; in this scenario, vendor lock-in becomes an issue. Cloud4SOA project aims to design and develop a Reference Architecture that could solve interoperability and portability problems within the Cloud domain. This paper describes our work on Cloud4SOA Semantic and SOA layer presenting a common knowledge base framework and a standardized set of harmonized APIs to overcome diversities among PaaS solution and report interesting experimental results collected for two real-world PaaS deployments.

Cloud computing is one of the key tools used in the analysis of big data. Cloud users have the option to work with the infrastructure (IaaS) or with the platform (PaaS). At first glance it may seem that PaaS is an ideal tool for this task. However, a closer look at PaaS reveals that there are several problems regarding clouds. The main problem is the static aspect of clouds. Users cannot customize the platform on their demand. They have to change the platform or work with the existing cloud infrastructure. Therefore the concept of tailored platform is presented in this paper. Tailored platforms are adaptable to the requirements of users. An abstract model was used for designing the tailored platforms architecture. The platforms are deployed in the clouds environment consists of clouds provided by different providers (multicloud environment). Users also have the opportunity to optimize the application runs using multiple criteria.