An autonomic delivery framework for HTTP adaptive streaming in multicast-enabled multimedia access networks

The consumption of multimedia services over HTTP-based delivery mechanisms has recently gained popularity due to their increased flexibility and reliability. Traditional broadcast TV channels are now offered over the Internet, in order to support Live TV for a broad range of consumer devices. Moreover, service providers can greatly benefit from offering external live content (e. g., YouTube, Hulu) in a managed way. Recently, HTTP Adaptive Streaming (HAS) techniques have been proposed in which video clients dynamically adapt their requested video quality level based on the current network and device state. Unlike linear TV, traditional HTTP- and HAS-based video streaming services depend on unicast sessions, leading to a network traffic load proportional to the number of multimedia consumers. In this paper we propose a novel HAS-based video delivery architecture, which features intelligent multicasting and caching in order to decrease the required bandwidth considerably in a Live TV scenario. Furthermore we discuss the autonomic selection of multicasted content to support Video on Demand (VoD) sessions. Experiments were conducted on a large scale and realistic emulation environment and compared with a traditional HAS-based media delivery setup using only unicast connections

Provider-Controlled Bandwidth Management for HTTP-based Video Delivery

Over the past few years, a revolution in video delivery technology has taken place as mobile viewers and over-the-top (OTT) distribution paradigms have significantly changed the landscape of video delivery services. For decades, high quality video was only available in the home via linear television or physical media. Though Web-based services brought video to desktop and laptop computers, the dominance of proprietary delivery protocols and codecs inhibited research efforts. The recent emergence of HTTP adaptive streaming protocols has prompted a re-evaluation of legacy video delivery paradigms and introduced new questions as to the scalability and manageability of OTT video delivery. This dissertation addresses the question of how to enable for content and network service providers the ability to monitor and manage large numbers of HTTP adaptive streaming clients in an OTT environment. Our early work focused on demonstrating the viability of server-side pacing schemes to produce an HTTP-based streaming server. We also investigated the ability of client-side pacing schemes to work with both commodity HTTP servers and our HTTP streaming server. Continuing our client-side pacing research, we developed our own client-side data proxy architecture which was implemented on a variety of mobile devices and operating systems. We used the portable client architecture as a platform for investigating different rate adaptation schemes and algorithms. We then concentrated on evaluating the network impact of multiple adaptive bitrate clients competing for limited network resources, and developing schemes for enforcing fair access to network resources. The main contribution of this dissertation is the definition of segment-level client and network techniques for enforcing class of service (CoS) differentiation between OTT HTTP adaptive streaming clients. We developed a segment-level network proxy architecture which works transparently with adaptive bitrate clients through the use of segment replacement. We also defined a segment-level rate adaptation algorithm which uses download aborts to enforce CoS differentiation across distributed independent clients. The segment-level abstraction more accurately models application-network interactions and highlights the difference between segment-level and packet-level time scales. Our segment-level CoS enforcement techniques provide a foundation for creating scalable managed OTT video delivery services

Random Linear Network Coding for 5G Mobile Video Delivery

An exponential increase in mobile video delivery will continue with the demand for higher resolution, multi-view and large-scale multicast video services. Novel fifth generation (5G) 3GPP New Radio (NR) standard will bring a number of new opportunities for optimizing video delivery across both 5G core and radio access networks. One of the promising approaches for video quality adaptation, throughput enhancement and erasure protection is the use of packet-level random linear network coding (RLNC). In this review paper, we discuss the integration of RLNC into the 5G NR standard, building upon the ideas and opportunities identified in 4G LTE. We explicitly identify and discuss in detail novel 5G NR features that provide support for RLNC-based video delivery in 5G, thus pointing out to the promising avenues for future research.Comment: Invited paper for Special Issue "Network and Rateless Coding for Video Streaming" - MDPI Informatio

PEER-TO-PEER VIDEO CONTENT DELIVERY OPTIMIZATION SERVICE IN A DISTRIBUTED NETWORK

Η δυναμικά προσαρμοζόμενη ροή βίντεο μέσω HTTP (DASH) παρέχει βελτιώσεις στην ποιότητα της εμπειρίας χρήσης (QoE) κατά την αναπαραγωγή βίντεο σε δίκτυα παλαιότερα των δικτύων 5ης γενιάς (5G). Ωστόσο, οι εφαρμογές τύπου νέφους τις οποίες μπορεί να παρέχει η αρχιτεκτονική δικτύων 5ης γενιάς, σε συνδυασμό με την υλοποίηση υπολογιστικών υποδομών νέφους στο άκρο του δικτύου και κοντά στους τελικούς χρήστες, μπορεί να βελτιώσει σημαντικά τόσο την ποιότητα της προσφερόμενης υπηρεσίας (QoS) όσο και την εμπειρία χρήσης λόγω της δυνατότητας προσωρινής αποθήκευσης περιεχομένου βίντεο στο άκρο του δικτύου, λόγω της δυνατότητας παροχής προσωρινής αποθήκευσης μέρους του βίντεο στο άκρο του δικτύου. Επιπροσθέτως, εκτός της αποθήκευσης στο και διανομής βίντεο από το άκρο του δικτύου προς τους τελικούς χρήστες, οι νέες υποδομές βίντεο θα παρέχουν τη δυνατότητα διανομής περιεχομένου βίντεο απευθείας από συσκευή σε συσκευή (D2D). Αξιοποιώντας τις τεχνολογίες αυτές, μπορούν να υλοποιηθούν καινοτόμες υπηρεσίες ροής βίντεο, οι οποίες μπορούν όχι μόνο να βελτιώσουν την εμπειρία χρήσης των τελικών χρηστών κατά την αναπαραγωγή βίντεο, αλλά και να μειώσουν το συνολικό κόστος διανομής βίντεο καθώς και την συμφόρηση των δικτύων, άρα και την καθυστέρηση από άκρο σε άκρο και τη συμφόρηση στα δίκτυα διανομής περιεχομένου (CDN) των παρόχων υπηρεσιών διανομής και ροής βίντεο. Στην παρούσα διπλωματική εργασία μελετούμε την επίπτωση που έχουν διάφοροι συνδυασμοί τεχνικών προσωρινής αποθήκευσης, διανομής, καθώς και επιλογής ανάλυσης, σε περιεχόμενο βίντεο, πάνω στην ποιότητα της προσφερόμενης υπηρεσίας και στην εμπειρία των τελικών χρηστών που βρίσκονται στο άκρο του δικτύου, οι οποίες μπορούν να αξιοποιηθούν στη δημιουργία μιας καινοτόμας υπηρεσίας που βελτιστοποιεί τη διανομή περιεχομένου βίντεο μεταξύ ομότιμων κόμβων (P2P) σε ένα κατανεμημένο δίκτυο.Dynamtic Adaptive Streaming over HTTP (DASH) has yield several improvements in the video playback Quality of Experimence (QoE) for the end users in pre-fifth generation (5G) networks. However, cloud applications that 5G networks enable, combined with cloud infrastructures at the edge of the network and in close vicinity to the end users, can offer significant improvements in both the offered Quality of Service (QoS) and QoE because of the video content caching capabilities at the edge of the network that the edge cloud can offer. Furthermore, in addition to edge caching and edge video streaming to the end users, new video infrastructures can offer Device-to-Device (D2D) video content exchange and delivery. Taking advantage of these technologies, innovative video streaming services can be developed which not only improve the video playback QoE for the end users but also reduce the video delivery costs and generated network traffic, which also means reduced end-to-end latency and reduced overhead in video content providers’ Content Delivery Network (CDN). In this thesis we study the impact of using different combinations of distinct video caching techniques, video segment request and streaming algorithms and video resolution selection logics on the QoS and the QoE of end users at the network edge, which can be used in developing an innovative Peer-to-Peer (P2P) video content delivery optimization service in a distributed network

Optimized algorithms for multimedia streaming

Ph.DDOCTOR OF PHILOSOPH

Cache as a service:leveraging SDN to efficiently and transparently support Video-on-Demand on the last mile

High quality online video streaming, both live and on-demand, has become an essential part of consumers’ every-day lives. The popularity of video streaming as placed a heavy burden on the network infrastructure that now has to transfer an enormous amount of data very quickly to the end-user. To further exacerbate the situation, the Video-on-Demand (VoD) distribution paradigm uses a unicast independent flow for each user request. This results in multiple duplicate flows carrying the same video assets many times end-to-end. We present OpenCache: a highly configurable, efficient and transparent in-network caching service that aims to improve the VoD distribution efficiency by caching video assets as close to the end-user as possible. OpenCache leverages Software Defined Networking to benefit last mile environments by improving network utilisation and increasing the Quality of Experience for the end-user. Our evaluation on a pan-European OpenFlow testbed uses adaptive video streaming and demonstrates that with the use of OpenCache, the external link utilisation is reduced by 100%. Furthermore the streaming application receives better quality video and observes higher throughput, lower latency and shorter start up and buffering times

AngelCast: cloud-based peer-assisted live streaming using optimized multi-tree construction

Increasingly, commercial content providers (CPs) offer streaming solutions using peer-to-peer (P2P) architectures, which promises significant scalabil- ity by leveraging clients’ upstream capacity. A major limitation of P2P live streaming is that playout rates are constrained by clients’ upstream capac- ities – typically much lower than downstream capacities – which limit the quality of the delivered stream. To leverage P2P architectures without sacri- ficing quality, CPs must commit additional resources to complement clients’ resources. In this work, we propose a cloud-based service AngelCast that enables CPs to complement P2P streaming. By subscribing to AngelCast, a CP is able to deploy extra resources (angel), on-demand from the cloud, to maintain a desirable stream quality. Angels do not download the whole stream, nor are they in possession of it. Rather, angels only relay the minimal fraction of the stream necessary to achieve the desired quality. We provide a lower bound on the minimum angel capacity needed to maintain a desired client bit-rate, and develop a fluid model construction to achieve it. Realizing the limitations of the fluid model construction, we design a practical multi- tree construction that captures the spirit of the optimal construction, and avoids its limitations. We present a prototype implementation of AngelCast, along with experimental results confirming the feasibility of our service.Supported in part by NSF awards #0720604, #0735974, #0820138, #0952145, #1012798 #1012798 #1430145 #1414119. (0720604 - NSF; 0735974 - NSF; 0820138 - NSF; 0952145 - NSF; 1012798 - NSF; 1430145 - NSF; 1414119 - NSF