Adaptive bitrate streaming protocols, such as DASH, have seen extensive interests for their adaptation capabilities to increase consumers' Quality of Experience (QoE) over the Internet, and have become de-facto standards in web video delivery. Compared with traditional single-server approaches, multipleserver streaming offers the opportunity to exploit expanded bandwidth, link diversity, and reliability. In this paper, we expose our solution for multiple-server support to dynamic adaptive streaming applications: Multiple-Source Streaming (MS-Stream). Thanks to its codec agnosticism and DASH-compliance our contribution is a pragmatic and evolving solution for QoE enhancement that can be applied to many streaming architectures (CDNs, Clouds) and is particularly suited for distributed environments such as P2P or Set-Top-Box overlays. In addition, splitting content into multiple independent sub-streams provides the opportunity to achieve easy-to-design bitrate adaptation and server-switching mechanisms. We empirically validate our approach using an extensive collection of network profiles provided by the DASH Industry Forum. Our solution is compared with the full potential of DASH with several servers over several QoE criteria. Results show the QoE gain of using MS-Stream against DASH; an online demonstration is made available.

In this paper we present a 5G Internet Radio-Light (IoRL) architecture for homes that can be readily deployed because it utilizes unlicensed visible light and millimeter wave part of the spectrum, which does not require Mobile Network Operator (MNO) permission to deploy and which is used to provide inhabitants of houses with accurate location, interaction, access to Internet and Cloud based services such as high resolution video on a Tablet PC. The paper describes the home use cases and the IoRL architecture.

Adaptive streaming protocols over HTTP (HAS), such as MPEG-DASH, have become the de-facto solutions to deliver video over the Internet. By avoiding buffer stalling, HAS increases end-user's Quality of Experience (QoE). These solutions always bind a client to one server. We propose to extend HAS capabilities to multiple-source streaming, which offers the opportunity to obtain higher QoE by exploiting expanded bandwidth and link diversity in distributed streaming infrastructures. We expose a pragmatic evolving DASH-compliant solution for dynamic adaptive Multiple-Source Streaming over HTTP (MS-Stream) that simultaneously utilizes several servers. We validated our approach using network profiles from DASH Industry Forum and Internet users. Our solution is compared to optimal -yet practically unfeasible-DASH solutions in multiple-source environments and over several QoE criteria. Results show the QoE gains of using MS-Stream against DASH; an online demonstration of our work is available.

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HTTP Adaptive Streaming (HAS) protocols have become the de-facto solutions to deliver video over the Internet, mainly due to their ability to limit video freezing and thus enhance consumers' Quality of Experience (QoE). Nevertheless, they do not have the possibility to improve the actual delivered video quality, limited by the available throughput between the delivering server and the client. Compared with this single-server approach, multiple-server streaming offers the opportunity to obtain enhanced QoE by benefiting from expanded bandwidth, link diversity and reliability in distributed streaming infrastructures. We present a prototype for a pragmatic evolving HAS-compliant streaming solution, simultaneously using several servers.

SummaryDelivering video content with a high and fairly shared quality of experience is a challenging task in view of the drastic video traffic increase forecasts, as live video traffic will grow 15‐fold by 2022. Currently, content delivery networks provide numerous servers hosting replicas of the video content, and consuming clients are redirected to the closest server. Then, the video content is streamed using adaptive streaming solutions. However, servers and network links often become overloaded during major events, and users may experience a poor or unfairly distributed quality of experience, unless more servers are provisioned. In this paper, we propose Muslin, a streaming solution supporting a high, fairly shared end users' quality of experience for live streaming, while minimizing the required content delivery platform scale. Muslin leverages on MS‐Stream, a content delivery solution, which aggregates video content from multiple servers to offer a high quality of experience for its users. Muslin dynamically provisions servers and replicates content into servers and advertises servers to clients based on real‐time delivery conditions. We have used Muslin to replay a 1‐day video‐games event, with hundreds of clients and several test beds. Our results show that our approach outperforms traditional content delivery schemes by increasing the fairness and quality of experience at the user side with a smaller infrastructure scale.

HTTP Adaptive Streaming have become the de-facto solutions to deliver video over the Internet due to their ability to enhance consumers' Quality of Experience (QoE). Nevertheless, they do not have the possibility to improve the actual delivered video quality, limited by the available client-server throughput. In comparison, multiple-server and P2P streaming offer the opportunity to obtain enhanced QoE by benefiting from expanded bandwidth, link diversity and reliability in distributed streaming infrastructures. We present a prototype for a hybrid P2P/multi-server quality-adaptive streaming solution, simultaneously using several servers and peers, and trading off the server infrastructure capacities and QoE gains.