We propose the TelcoFog architecture as a novel, secure, highly distributed and ultradense fog computing infrastructure, which can be allocated at the extreme edge of a wired/wireless network for a Telecom Operator to provide multiple unified, cost-effective and new 5G services, such as Network Function Virtualization (NFV), Mobile Edge Computing (MEC), and services for third parties (e.g., smart cities, vertical industries or Internet of Things (IoT)).The distributed and programmable fog technologies that are proposed in TelcoFog are expected to strengthen the position of the Mobile Network and cloud markets. TelcoFog, by design, is capable of integrating an ecosystem for network operators willing to provide NFV, MEC and IoT services. TelcoFog key benefits are the dynamic deployment of new distributed low-latency services.The novel TelcoFog architecture consists of three main building blocks: a) a scalable TelcoFog node, that is seamlessly integrated in the Telecom infrastructure; b) a TelcoFog controller, focused on service assurance and based on service data modeling using YANG, that is integrated in the management and orchestration architecture of the Telecom operator; and c) TelcoFog services, which are able to run on top of the TelcoFog and Telecom infrastructure. The TelcoFog architecture is validated through a Proof of Concept for IoT services.
Media use cases for emergency services require mission-critical levels of reliability for the delivery of media-rich services such as video streaming. With the upcoming deployment of the Fifth Generation (5G) networks, a wide variety of applications and services with heterogeneous performance requirements are expected to be supported, and any migration of missioncritical services to 5G networks presents significant challenges in the Quality of Service (QoS), for emergency service operators. This paper presents a novel SliceNet framework, based on advanced and customisable network slicing to address some of the highlighted challenges in migrating eHealth telemedicine services to 5G networks. An overview of the framework outlines the technical approaches in beyond the-state-of-the-art network slicing. Subsequently, the paper emphasises the design and prototyping of a media-centric eHealth use case, focusing on a set of innovative enablers towards achieving end-to-end QoS-aware network slicing capabilities, required by this demanding use case. Experimental results empirically validate the prototyped enablers and demonstrate the applicability of the proposed framework in such media-rich use cases.
Abstract-Achieving ever-growing Quality of Service (QoS) requirements for business customers is a major concern over the current Internet. However, presently, its architecture and infrastructures are inflexible to meet the demand of increased QoS requirements. OpenFlow, OF-Config (OpenFlow Configuration and Management protocol), and OVSDB (Open vSwitch Database Management protocol) protocols are well-known software defined networking (SDN) technologies for the Future Internet, enabling flexibility by decoupling the control plane from networking devices. In this paper, we propose a QoS framework using the SDN technologies and test the framework in failure-conditions using single and multiple autonomous system scenarios of the current Internet. We show that an effectively high QoS can be achieved for business customers using our framework.
Network slicing has emerged as a major new networking paradigm for meeting the diverse requirements of various vertical businesses in virtualised and softwarised 5G networks. SliceNet is a project of the EU 5G Infrastructure Public Private Partnership (5G PPP) and focuses on network slicing as a cornerstone technology in 5G networks, and addresses the associated challenges in managing, controlling and orchestrating the new services for users especially vertical sectors, thereby maximising the potential of 5G infrastructures and their services by leveraging advanced software networking and cognitive network management. This paper presents the vision of the SliceNet project, highlighting the gaps in existing work and challenges, the proposed overall architecture, proposed technical approaches, and use cases.
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