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Open Source Software (OSS) has come to play a critical role in the software industry. Some large ecosystems enjoy the participation of large numbers of companies, each of which has its own focus and goals. Indeed, companies that otherwise compete, may become collaborators within the OSS ecosystem they participate in. Prior research has largely focused on commercial involvement in OSS projects, but there is a scarcity of research focusing on company collaborations within OSS ecosystems. Some of these ecosystems have become critical building blocks for organizations worldwide; hence, a clear understanding of how companies collaborate within large ecosystems is essential. This paper presents the results of an empirical study of the OpenStack ecosystem, in which hundreds of companies collaborate on thousands of project repositories to deliver cloud distributions. Based on a detailed analysis, we identify clusters of collaborations, and identify four strategies that companies adopt to engage with the OpenStack ecosystem. We also find that companies may engage in intentional or passive collaborations, or may work in an isolated fashion. Further, we find that a company's position in the collaboration network is positively associated with its productivity in OpenStack. Our study sheds light on how large OSS ecosystems work, and in particular on the patterns of collaboration within one such large ecosystem. [ABSTRACT FROM AUTHOR]

In view of the large-scale storage requirements in current space utilizations, Swift object storage system is used to realize long-term storage of data, while satisfying reliability, high efficiency and persistence. For the special needs of space utilizations, the strategy of Ring, the important components of the Swift, need to be transformed to adapt to the unique hardware equipment. The experimental results show that the strategy can balance the total write amount of each node as much as possible while balancing the network load. In other words, it can extend the overall life of the equipment, and make the whole system more suitable for the space environment. [ABSTRACT FROM AUTHOR]

In recent days, cloud computing and open sources, as the globally marketable trend in Information Communication Technology (ICT), are widely used and closely interrelated each other in the various application platforms and web-based services. The integrated services by these two technology components is recognized as one of a prospective web-based models in the geo-spatial applications. Despite these aspects, there are a few application cases dealing with geo-based or remotely sensed data sets. This study focused on a cloud-based service implementation for satellite image analysis based on the full open source stack: OpenStack, Orfeo Toolbox, GDAL, Proj, and Django. On OpenStack cloud computing environment, several virtual servers for system management and analysis functionalities have been constructed as a private cloud environment due to data security. This system can expand as a kind of hybrid cloud with an external cloud system using public and open data sets. For the practical processing instances are controlled on the auto-scaling scheme of cloud computing. Analysis functions for optical images within this service are thresholding segmentation, pan-sharpening with multi-resolution image sets, cloud detection, change detection with paired image sets. User-side of the web client does not need any additional requirements such as plug-in or data downloading except web accessing on this cloud service. It is implied that cloud-based online services on OpenStack can be applied to other types of Software-as-a-Service (SaaS) for geo-spatial image processing system in a specialized field. [ABSTRACT FROM AUTHOR]

Anomaly based intrusion detection systems suffer from a lack of appropriate evaluation data sets. Often, existing data sets may not be published due to privacy concerns or do not reflect actual and current attack scenarios. In order to overcome these problems, we identify characteristics of good data sets and develop an appropriate concept for the generation of labelled flow-based data sets that satisfy these criteria. The concept is implemented based on OpenStack, thus demonstrating the suitability of virtual environments. Virtual environments offer advantages compared to static data sets by easily creating up-to-date data sets with recent trends in user behaviour and new attack scenarios. In particular, we emulate a small business environment which includes several clients and typical servers. Network traffic is generated by scripts which emulate typical user activities like surfing the web, writing emails, or printing documents on the clients. These scripts follow some guidelines to ensure that the user behaviour is as realistic as possible, also with respect to working hours and lunch breaks. The generated network traffic is recorded in unidirectional NetFlow format. For generating malicious traffic, attacks like Denial of Service, Brute Force, and Port Scans are executed within the network. Since origins, targets, and timestamps of executed attacks are known, labelling of recorded NetFlow data is easily possible. For inclusion of actual traffic, which has its origin outside the OpenStack environment, an external server with two services is deployed. This server has a public IP address and is exposed to real and up-to-date attacks from the internet. We captured approximately 32 million flows over a period of four weeks and categorized them into five classes. Further, the chronological sequence of the flows is analysed and the distribution of normal and malicious traffic is discussed in detail. The main contribution of this paper is the demonstration of a novel approach to use OpenStack as a basis for generating realistic data sets that can be used for the evaluation of network intrusion detection systems. [ABSTRACT FROM AUTHOR]

In this paper we present the performance of parallel text processing with Map Reduce on a cloud platform. Scientific papers in Turkish language are processed using Zemberek NLP library. Experiments were run on a Hadoop cluster and compared with the single machine's performance. [ABSTRACT FROM AUTHOR]

The management of a laboratory for the many classes/areas in an education institution makes a set of challenges for the IT department which face a growing pressure to provide the necessary computing resources at the lowest price. This paper proposes a platform named CSCLab for the provisioning and management of laboratories with the computing resources necessary to teach a class using the cloud. The system was designed to be used by non-experts in cloud technologies and implemented to run in OpenStack but it can be easily adapted to other platforms with similar services. [ABSTRACT FROM AUTHOR]

Multimedia conference system is becoming increasingly popular among enterprises and government departments by right of its efficiency and cost-saving features. It supports people in different places share audio, video and documents to achieve real-time communication. However, traditional multimedia conference system can't meet users' personal and individual needs. Multi-tenancy has been proposed as a solution to the problem. It allows multiple tenants to share a single application instance securely. With a multi-tenant architecture, each tenant works with a customized virtual application instance. In this paper, we design and implement a multi-tenant architecture which supports the system with customizability and scalability. [ABSTRACT FROM PUBLISHER]

Abstract -- Because of inexpensive, on-demand resources, Cloud computing is a promising platform for scientific HPC applications, such as gene sequencing. However, it also poses challenges to users and developers in terms of running and maintaining HPC applications which is low-level and complex for scientists. This impacts reusability and reproducibility of the work and increases the cost of development and maintenance. N3phele is a cloud-based workbench that allows researchers to perform complex analysis using only browser and resources in infrastructure clouds, which are orchestrated by n3phele. Individual scientists may publish tools and workflow pipelines, registering them in n3phele for their own private or public collaborator use. To illustrate, the QIIME microbial community analysis toolkit has been registered into n3phele, and n3phele used to perform microbial analysis, including computationally intensive Roche 454 denoising, using Amazon EC2 and n3phele's point and click interface. N3phele substantially improves usability and manageability of complex scientific analysis pipelines in the cloud. [ABSTRACT FROM PUBLISHER]

Cloud management platforms may manage the resources provided by the infrastructure as a service (IaaS) cloud. With the rapid development of open-source cloud platforms, they have been widely used due to open and free, some of them can substitute commercial clouds. Some existed related works only concisely compare the basic features of open-source platforms, and not including some new released features. In this paper, we firstly present the function of OpenStack and OpenNebula briefly, and then compare them from provenance, architecture, hypervisors, security and other angles in detail. Moreover, we provide some deployment recommendations according to different user demands and platform characteristics. [ABSTRACT FROM PUBLISHER]

Cloud computing has become an essential technology not only for web provisioning, but also in mobile scenarios. Mobile devices are usually resource constrained due to processing and power limitations, so typical applications are not easy portable. Battery draining and application performance (resource shortage) have a big impact on the experienced quality, so shifting applications and services to the Cloud may improve mobile user's satisfaction. However, available Cloud solutions are mostly focused on scenarios with slowly changing provisioning, which are unable to support and promptly react to short-term provisioning requests. To address the new scenario, this paper proposes a novel Cloud monitoring and management architecture based on the data-centric publish-subscribe Data Distribution Service (DDS) standard. We present not only an architecture proposal, but also a real prototype that we have deployed in our experimental testbed. The experimental results show that our architecture is able to support the scheduling of highly dynamic tasks in the Cloud while maintaining low overheads. [ABSTRACT FROM PUBLISHER]

Today, many cloud Infrastructure as a Service(IaaS) frameworks exist. Users, developers, and administrators have to make a decision about which environment is best suited for them. Unfortunately, the comparison of such frameworks is difficult because either users do not have access to all of them or they are comparing the performance of such systems on different resources, which make it difficult to obtain objective comparisons. Hence, the community benefits from the availability of a testbed on which comparisons between the IaaS frameworks can be conducted. FutureGrid aims to offer a number of IaaS including Nimbus, Eucalyptus, OpenStack, and OpenNebula. One of the important features that FutureGrid provides is not only the ability to compare between IaaS frameworks, but also to compare them in regards to bare-metal and traditional high performance computing services. In this paper, we outline some of our initial findings by providing such a testbed. As one of our conclusions, we also present our work on making access to the various infrastructures on FutureGrid easier. [ABSTRACT FROM PUBLISHER]

FiRST (Future Internet Research for Sustainable Test-bed) is the future internet platform development project being performed in Korea. The goal of the project is to create the virtualized and dynamic service creation environments over future internet networks; it is an experimental project to realize future innovative service ideas over real network environments. Among this, cloud computing is the key enabler to control and allocate virtualized network resources (such as CPU, storage, and virtualized network configuration) for the requested services. However, researches on interworking between future internet and cloud computing is in initial phase. In this paper, we propose the FiRST Cloud Aggregate Manager (AM) based on GENI (Global Environment for Network Innovation) AM Application Programming Interface (API) for the federation between future internet test-bed and open source OpenStack cloud computing platform. After that, we propose the zero-client service for mobile cloud management. In order to control the zero-client service, we develop Cloud Mobility Client/Server. And, we validate and verified our FiRST Cloud AM and zero-client service by developing experimental test-bed. Through this test-bed, we confirm that the proposed FiRST Cloud AM and zero-client service efficiently interworks with future internet control plane framework by using GENI Control Framework (GCF) tools. [ABSTRACT FROM PUBLISHER]

This demo presents a Machine-to-Machine (M2M) service platform running on an OpenStack cloud environment. Access to this platform is secured with authentication based on 3GPP standardized Generic Bootstrapping Architecture (GBA). The M2M network in this testbed consists of Rasp- berry Pi gateways and resource-constrained devices such as Arduinos. These devices have associated sensors, that report physical data such as temperature, and actuators such as LEDs, that respond to actuation commands. In this demo, the sensor data is authenticated and integrity protected end- to-end with public-key elliptic curve digital signature algorithm (ECDSA). Lastly, the demo testbed includes a web- based cloud management interface referred to as the "IoT Portal". This portal allows a system administrator to specify pre-configured Virtual Machine (VM) images with custom applications. As an example, a M2M Web service is installed into the VMs. This web service collects and displays authenticated and verified sensor data and can also be used to send actuator commands. [ABSTRACT FROM AUTHOR]