NFV-MANO has become the de-facto standard for network service orchestration in future programmable network infrastructures. Specifically, relevant standards define an architecture and a data model that allows an orchestration entity to deploy, dynamically configure and monitor virtual and physical network function across virtualized datacenters. Although the model offers extensive details for network functions management and host-level network configuration, end-to-end connectivity management beyond the datacenter remains limited, modeled by the WAN Infrastructure Manager (WIM) abstraction. Although many open-source service management frameworks offer NFV-MANO support, the community still lacks a WIM reference implementation. In this paper, we present the DataPlane Broker (DPB), the first open source WIM implementation for Ethernet networks. The system develops an extensive data model to seamlessly translate NFV-MANO connectivity requirement to network configuration for SDN-enabled networks and supports point-to-point and point-to-multipoint virtual links with strong QoS guarantees. DPB currently offers complete integration with the current stable OSM version (v5) and we demonstrate that it provides good scaling properties under high service provision requirements.

Leading state-of-the-art research facilities at the Universities of Edinburgh (UoE), Bristol (UoB), Lancaster (UoLan), King's College London (KCL) and Digital Catapult (DCAT) are interconnected through a dedicated JISC/JANET network infrastructure. Using Software Defined Networking (SDN) and Network Function Virtualisation (NFV) technologies, these distributed test-beds are integrated using a multi-domain NFV Orchestrator. This paper introduces a novel specialist distributed test-bed developed for facilitating the increasingly large and complex experimentation of future Internet system architectures, technologies, services and applications between the geographically dispersed laboratories across the UK. The aim is to enable students, researchers and enterprises to interconnect with and carry out remote experiments using these test-beds. Each one contributes a range of key capabilities for Internet research including optical networks, optical wireless and radio frequency communications, Internet of Things (IoT), SDN, NFV, as well as cloud computing technologies and services.

The modern Smart Grid (SG) requires the adequate exploitation of Ancillary Services (AS) in order to dynamically support evolving energy demands, ensure grid stability and optimize energy trading transactions. Distributed Renewable Energy Sources (DRES) are considered as the most promising avenue to underpin the dynamic composition of AS. Nonetheless, the inherent legacy, distributed and resourceconstrained properties of DRES deployments trigger a plethora of challenges with respect to the underlying end-to-end (E2E) data communication performance with direct implications on AS orchestration. Hence, assuring resilient and scalable E2E AS provisioning is a highly challenging task requiring advanced networking mechanisms. This work goes beyond architectural, policy-level and theoretical suggestions of how 5G can be utilized in the SG context and provide a proof-of-concept, system for DRES management. We introduce Ukko; an open-source, 5G network service design facilitating the programmable, "innetwork" orchestration of DRES management, supporting realtime AS application requirements. Experiments conducted over a UK-wide 5G testbed using real use-case scenarios demonstrate that the proposed solution can assure scalable and resilient DRES management at the likely occurrence of data communication challenges.

This study identifies a method to create fine-grained multilayer maps of the Internet's structure, which are currently lacking. We begin with an investigation of current techniques for geolocating hosts using passive, active, and hybrid methods. This is followed by a survey of the fundamental problems that IP geolocation techniques must address. The survey points to the obvious difficulties in using Delay-Distance models and suggests that the use of Return Trip Times can lead to highly misleading results. We therefore develop a new procedure that combines state-of-the-art methods to avoid many of the fundamental problems in Internet topology mapping, whilst creating finer-grained internet maps than those currently available. This procedure is tested on the UK infrastructure by conducting a series of tests using distributed measurement points provided by the RIPE Atlas platform. Our results show that we can accurately geolocate routers between two endpoints to create a fine-grained map of the internet infrastructure involved in our measurements. Researchers have long recognized the scarcity of ground truth datasets where IP geolocation is a concern. As a byproduct of our new method reported in this paper, we create a validation dataset that maps hundreds of IP addresses to geo-coordinate landmarks or vantage points, which is highly desirable for IP geolocation research. Finally, we discuss some limitations of this method, and we summarise the next steps toward accurate and complete Internet infrastructure maps.