Abstract-Internet video streaming applications have been demanding more bandwidth and higher video quality, especially with the advent of Virtual Reality (VR) and Augmented Reality (AR) applications. While adaptive streaming protocols like MPEG-DASH (Dynamic Adaptive Streaming over HTTP) allows video quality to be flexibly adapted, e.g., degraded when mobile network condition deteriorates, this is not an option if the application itself requires guaranteed 4K quality at all time. On the other hand, conventional end-to-end TCP has been struggling in supporting 4K video delivery across long-distance Internet paths containing both fixed and mobile network segments with heterogeneous characteristics. In this paper, we present a novel and practically-feasible system architecture named MVP (Mobile edge Virtualization with adaptive Prefetching), which enables content providers to embed their content intelligence as a virtual network function (VNF) into the mobile network operator's (MNO) infrastructure edge. Based on this architecture, we present a context-aware adaptive video prefetching scheme in order to achieve QoE-assured 4K video on demand (VoD) delivery across the global Internet. Through experiments based on a real LTE-A network infrastructure, we demonstrate that our proposed scheme is able to achieve QoE-assured 4K VoD streaming, especially when the video source is located remotely in the public Internet, in which case none of the state-of-the-art solutions is able to support such an objective at global Internet scale.Index Terms-MPEG-DASH, mobile edge computing, network function virtualization, prefetching, quality of experience, video on demand

Satellite communication has recently been included as one of the key enabling technologies for 5G backhauling, especially for the delivery of bandwidth-demanding enhanced mobile broadband (eMBB) applications in 5G. In this paper, we present a 5G-oriented network architecture that is based on satellite communications and multi-access edge computing (MEC) to support eMBB applications, which is investigated in the EU 5GPPP Phase-2 SaT5G project. We specifically focus on using the proposed architecture to assure Quality-of-Experience (QoE) of HTTP-based live streaming users by leveraging satellite links, where the main strategy is to realise transient holding and localization of HTTP-based (e.g., MPEG-DASH or HTTP Live Streaming) video segments at 5G mobile edge while taking into account the characteristics of satellite backhaul link. For the very first time in the literature, we carried out experiments and systematically evaluated the performance of live 4K video streaming over a 5G core network supported by a live geostationary satellite backhaul, which validates its capability of assuring live streaming users' QoE under challenging satellite network scenarios.

Abstract-HTTP-based live streaming has become increasingly popular in recent years, and more users have started generating 4K live streams from their devices (e.g., mobile phones) through social-media service providers like Facebook or YouTube. If the audience is located far from a live stream source across the global Internet, TCP throughput becomes substantially suboptimal due to slow-start and congestion control mechanisms. This is especially the case when the end-to-end content delivery path involves radio access network (RAN) at the last mile. As a result, the data rate perceived by a mobile receiver may not meet the high requirement of 4K video streams, which causes deteriorated Quality-of-Experience (QoE). In this paper, we propose a scheme named Edge-based Transient Holding of Live sEgment (ETHLE), which addresses the issue above by performing context-aware transient holding of video segments at the mobile edge with virtualized content caching capability. Through holding the minimum number of live video segments at the mobile edge cache in a context-aware manner, the ETHLE scheme is able to achieve seamless 4K live streaming experiences across the global Internet by eliminating buffering and substantially reducing initial startup delay and live stream latency. It has been deployed as a virtual network function at an LTE-A network, and its performance has been evaluated using real live stream sources that are distributed around the world. The significance of this paper is that by leveraging virtualized caching resources at the mobile edge, we address the conventional transport-layer bottleneck and enable QoE-assured Internet-wide live streaming services with high data rate requirements.Index Terms-HTTP live streaming, mobile edge computing, network function virtualization, quality of experience, video caching

In this paper, we present a Mobile Edge Computing (MEC) scheme for enabling network edge-assisted video adaptation based on MPEG-DASH (Dynamic Adaptive Streaming over HTTP). In contrast to the traditional over-the-top (OTT) adaptation performed by DASH clients, the MEC server at the mobile network edge can capture radio access network (RAN) conditions through its intrinsic Radio Network Information Service (RNIS) function, and use the knowledge to provide guidance to clients so that they can perform more intelligent video adaptation. In order to support such MECassisted DASH video adaptation, the MEC server needs to locally cache the most popular content segments at the qualities that can be supported by the current network throughput. Towards this end, we introduce a two-dimensional user Quality-of-Experience (QoE)-driven algorithm for making caching / replacement decisions based on both content context (e.g., segment popularity) and network context (e.g., RAN downlink throughput). We conducted experiments by deploying a prototype MEC server at a real LTE-A based network testbed. The results show that our QoE-driven algorithm is able to achieve significant improvement on user QoE over 2 benchmark schemes.

Abstract-Satellite communication has recently been included as one of the enabling technologies for 5G backhauling, in particular for the delivery of bandwidth-demanding enhanced mobile broadband (eMBB) application data in 5G. In this paper we introduce a 5G-oriented network architecture empowered by satellite communications for supporting emerging mobile video delivery, which is investigated in the EU 5GPPP Phase 2 SAT5G Project. Two complementary use cases are introduced, including (1) the use of satellite links to support offline multicasting and caching of popular video content at 5G mobile edge, and (2) real-time prefetching of DASH (Dynamic Adaptive Streaming over HTTP) video segments by 5G mobile edge through satellite links. In both cases, the objective is to localize content objects close to consumers in order to achieve assured Quality of Experiences (QoE) in 5G content applications. In the latter case, in order to circumvent the large end-to-end propagation delay of satellite links, testbed based experiments have been carried out to identify specific prefetching policies to be enforced by the Multiaccess computing server (MEC) for minimizing user perceived disruption during content consumption sessions.

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With the continually increased attention on Electric Vehicles (EVs) due to environment impact, public Charging Stations (CSs) for EVs will become common. However, due to the limited electricity of battery, the driver may experience discomfort for long charging waiting time, if travelling towards a CS which is heavily loaded for charging. With this concern, we manage on-the-move EV charging by coordinating which CS to select for charging, and propose a CS-selection scheme considering EVs anticipated charging reservations generally including arrival time and expected charging time, in particular the parking duration is further considered in this paper. Upon this, by addressing mobility uncertainty that EVs may not reach their selected CSs on time due to uncertain traffic condition on the road, a periodical reservation updating for requesting the change of CS-selection decision is proposed to further coordinate charging management. The motivation for this is mainly due to that the mobility uncertainty affects the accuracy of reported reservation information, concerning the arrival time at selected CSs and expected charging time upon arrival. Evaluation results show the effectiveness of our proposal when considering realistic EV and CS characteristics.

We have harnessed the salient features of information-centric networking (ICN) and implemented a communication infrastructure, called C-DAX, for supporting smart grid applications. We will demonstrate the operations of C-DAX both in a laboratory setup and a real field trial that involves the deployment of C-DAX in a live electricity grid in the Netherlands. This demo will showcase the capabilities of C-DAX, highlighting how ICN satisfies stringent smart grid application requirements.