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

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In pursuit of a flexible, resource efficient and highperformant 5G infrastructure, many operators, vendors and research consortia are currently developing, testing and integrating their NFV platform with associated management and orchestration (MANO) functionality. The SONATA NFV platform follows a micro-service design, which involves a tight coupling between an SDK, monitoring and MANO functionality, targeting a secure and stable software foundation. This experience paper gives a thorough overview on the encountered challenges, insights and resulting learnings when implementing and integrating the SONATA Service Platform using a continuous integration and delivery DevOps methodology. This is the result of a strong cooperation between prominent equipment vendors, network operators, software companies and universities, providing a set of constructive recommendations in hope of catalysing the development and deployment of NFV platforms.

Abstract.Jini is an infrastructure built on top of the mobile code facilities of the Java programming language enabling clients and services to spontaneously engage in arbitrary usage scenarios. For a small home or office environment the currently available infrastructure might be adequate, but for mission-critical applications it lacks essential security properties. In the sequel we identify weak points in the Jini architecture and its protocols and propose an extension to the architecture that provides a solution to the identified security problems. We describe the design choices underlying our implementation which aims at maximum compatibility with the existing Jini specifications.

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Ubiquitous network access allows people to access an ever increasing range of services from a variety of mobile terminals, including laptops, tablets and smartphones. A flexible and economically efficient way of provisioning such services is through Cloud Computing. Assuming that several cloudenabled datacenters are made available at the edges of the Internet, service providers may take advantage of them by optimally locating service instances as close as possible to their users. By localizing traffic at the edges of access networks, such an approach may result beneficial for both service and network providers. In this paper we present FollowMe Cloud (FMC), a technology developed at NEC Laboratories Europe that allows transparent migration of services in TCP/IP networks, thanks to the dynamic configuration of a set of coordinated OpenFlow switches located at the edge of the network. In particular, in this paper we analyze the scalability properties of an FMC-based system and propose a role separation strategy based on distribution of control plane functions which enables scale-out of the system. By means of simulation, we prove that the application of the proposed separation strategy results in less state retained by individual OpenFlow controllers and in more effective localization of network traffic.

Abstract-5G does not only aim at higher capacity and lower latency than current 4G in mobile broadband networks, but also to increase the level of programmability, control and flexibility to meet the requirements from innovative use cases such as IoT, smart manufacturing, and immersive media. However, several difficulties still need to be overcome for a better technological adoption. To reduce the time-to-market for networked services and to lower the entry barrier to third party developers of VNFs and network services, an integrated development and operations (DevOps) methodology is a promising way. One of the biggest challenges in upcoming 5G DevOps is the validation and verification (V&V) of individual VNFs and network services (VNF graphs) so that operators can be sure of their behavior. In this paper, we propose an NFV architecture that supports the DevOps methodology with a V&V platform and an advanced NFV catalogue. The conceptual components of the V&V platform, the foreseen methodology and the outcomes are explained. Finally, we explore some perspectives in applying such V&V approach in another 5G research project.

Cloud computing becomes increasingly prevalent for outsourcing IT functions. The basic feature of offering virtual data center slices to customers has been in use for some time now. So far, customers only get the raw resources, with only little insight and control of their resources. But to let customers build reliable services on top of the rented infrastructure, they need adequate monitoring and control capabilities. In the future, we expect operators to offer such functions to their customers. In this paper, we introduce our approach towards offering a holistic monitoring system to data center customers. It offers generic monitoring information propagation and storage covering various types of resources (network, servers, and applications), all kinds of monitoring information, and all tenants. As virtualized data centers are usually large and multitenant, our solution is built with these properties in mind.