The explosive growth in on-demand access of video across all forms of delivery (Internet, traditional cable, IPTV, wireless) has renewed the interest in scalable delivery methods. Approaches using Content Delivery Networks (CDNs), Peer-to-Peer (P2P) approaches, and their combinations have been proposed as viable options to ease the load on servers and network links. However, there has been little focus on how to take advantage of user viewing patterns to understand their impact on existing mechanisms and to design new solutions that improve the streaming service quality. In this dissertation, we leverage on the observation that users watch only a small portion of videos to understand the limits of existing designs and to optimize two scalable approaches -- the content placement and P2P Video-on-Demand (VoD) streaming. Then, we present our novel scalable system called Joint-Family which enables adaptive bitrate streaming (ABR) in P2P VoD, supporting user viewing patterns. We first provide evidence of such user viewing behavior from data collected from a nationally deployed VoD service. In contrast to using a simplistic popularity-based placement and traditionally proposed caching strategies (such as CDNs), we use a Mixed Integer Programming formulation to model the placement problem and employ an innovative approach that scales well. We have performed detailed simulations using actual traces of user viewing sessions (including stream control operations such as pause, fast-forward, and rewind). Our results show that the use of segment-based placement strategy yields substantial savings in both disk storage requirements at origin servers/VHOs as well as network bandwidth use. For example, compared to a simple caching scheme using full videos, our MIP-based placement using segments can achieve up to 71% reduction in peak link bandwidth usage. Secondly, we note that the policies adopted in existing P2P VoD systems have not taken user viewing behavior -- that users abandon videos -- into account. We show that abandonment can result in increased interruptions and wasted resources. As a result, we reconsider the set of policies to use in the presence of abandonment. Our goal is to balance the conflicting needs of delivering videos without interruptions while minimizing wastage. We find that an Earliest-First chunk selection policy in conjunction with the Earliest-Deadline peer selection policy allows us to achieve high download rates. We take advantage of abandonment by converting peers to "partial seeds"; this increases capacity. We minimize wastage by using a playback lookahead window. We use analysis and simulation experiments using real-world traces to show the effectiveness of our approach. Finally, we propose Joint-Family, a protocol that combines P2P and adaptive bitrate (ABR) streaming for VoD. While P2P for VoD and ABR have been proposed previously, they have not been studied together because they attempt to tackle problems with seemingly orthogonal goals. We motivate our approach through analysis that overcomes a misconception resulting from prior analytical work, and show that the popularity of a P2P swarm and seed staying time has a significant bearing on the achievable per-receiver download rate. Specifically, our analysis shows that popularity affects swarm efficiency when seeds stay "long enough". We also show that ABR in a P2P setting helps viewers achieve higher playback rates and/or fewer interruptions. We develop the Joint-Family protocol based on the observations from our analysis. Peers in Joint-Family simultaneously participate in multiple swarms to exchange chunks of different bitrates. We adopt chunk, bitrate, and peer selection policies that minimize occurrence of interruptions while delivering high quality video and improving the efficiency of the system. Using traces from a large-scale commercial VoD service, we compare Joint-Family with existing approaches for P2P VoD and show that viewers in Joint-Family enjoy higher playback rates with minimal interruption, irrespective of video popularity.

In 2011, home-video distribution company, The Criterion Collection, teamed up with streaming-content provider Hulu, extending their business model to include online streaming to subscribers through Hulu Plus. With the rise of Over-The-Top (OTT) media distribution services into the at-home market, the question that Criterion now faces is: how will the company survive as the market shifts away from Criterion’s established values? And, more pertinently, how does Criterion, by rebranding their image to compete in the streaming market, hope to attract new users without alienating their established fan base or sacrificing their brand identity? This thesis examines the Criterion Collection’s brand identity, business model, and history, focusing on its packaging and promotion, distribution channels (physical and streaming), and the formation of a self-established cinephile community through their website, Criterion.com. In my examination of Criterion’s attempts to branch out into new markets and adapt to alternative modes of media consumption, I argue that Criterion is taking strides to attract new audiences and build a tightly knit online fan community around their brand.

<p>The purpose of this thesis is to examine the possibilities of creating a MPEG-4-compatible set-top box for IP-networks based on open standards. </p><p>Existing alternatives for transporting MPEG-4 over IP are evaluated and ISMA is found to be an important actor within the area. ISMA is a non-profit corporation formed to provide a forum for the creation of specifications that define an interoperable implementation for streaming rich media over IP-networks. </p><p>Two different designs based on ISMA's recommendation are constructed and evaluated. The designs have different levels of complexity and the more complex design is found to be better due to its extended functionality. </p><p>During the design process a number of problems related to this kind of set-top box are discovered. It is believed, however, that many of these problems will be solved within the near future.</p>

The purpose of this thesis is to examine the possibilities of creating a MPEG-4-compatible set-top box for IP-networks based on open standards. Existing alternatives for transporting MPEG-4 over IP are evaluated and ISMA is found to be an important actor within the area. ISMA is a non-profit corporation formed to provide a forum for the creation of specifications that define an interoperable implementation for streaming rich media over IP-networks. Two different designs based on ISMA's recommendation are constructed and evaluated. The designs have different levels of complexity and the more complex design is found to be better due to its extended functionality. During the design process a number of problems related to this kind of set-top box are discovered. It is believed, however, that many of these problems will be solved within the near future.

Monitoring remains an important problem in computer science. This thesis describes which monitor information is needed to analyze distributed service environments. This thesis also describes how to get these information and how to store them in a monitoring database. The resulting model is used to describe a distributed media content environment and a simulation system that runs on the CLIC helps to generate measurements as in real systems. / Monitoring ist ein wichtiges Problem in der Informatik. In dieser Arbeit werden die benoetigten Daten beschrieben, welche zur Analyse von verteilten Dienstumgebungen dienen. Weiterhin wird beschrieben, wie man diese Daten messen und in einer geeigneten Datenbank speichern kann. Das daraus entstehende Modell wird verwendet um eine verteilte Medien-Daten-Umgebung zu beschreiben und eine Simulation auf dem CLIC erzeugt Messdaten wie sie in realen Systemen vorkommen.

We are witnessing a proliferation of video in the Internet; YouTube is the most bandwidth intensive service of today’s Internet. It accounts for 20 - 35% of the Internet traffic with 35 hours of videos uploaded every minute and more than 700 billion playbacks in 2010. Netflix, a web service that streams premium contents such as TV series, shows, and movies, consumes 30% of the network bandwidth in North America at peak time. Recently, leveraging the content distribution networks (CDNs), a new paradigm for video streaming on the Internet has emerged, namely, Adaptive HTTP Streaming (AHS). AHS has become the industry standard for video streaming over the Internet adopted by broadcast networks as well as VoD services such as YouTube, Netflix, Hulu, etc. In the 90’s and early 2000’s, Internet-based video streaming for high-bitrate video was challenging due to hardware limitations. In that era, to cover the hardware limitations, every software component of a video server needed to be carefully optimized to support the real-time guarantees for jitter-free video delivery. However, most of the software solutions have become less important with the remarkable hardware improvements over the past two decades. There is 100× speedup in CPU speeds; RAM capacity has increased by 1,000×; hard disk drive (HDD) capacity has grown by 10,000×. Today, CPU is no longer a bottleneck for video streaming. On the other hand, storage bandwidth and network bandwidth are still serious bottlenecks for large scale on-demand video streaming. In this dissertation, we aim at a scalable video content distribution system that addresses both storage bottleneck and network bottleneck. The first part of the dissertation pertains to the storage system on the server side: A multi-tiered storage system that exploits a flash memory solid-state drive (SSD) can meet the bandwidth needs in a much more cost- effective way than a traditional two-tier storage system. We first identify the challenges in architecting such a system given the performance quirks of flash-based SSDs, and the lim- itations of state-of-the-art multi-tiered storage systems for video streaming. Armed with the knowledge of these challenges, we show how to construct such a storage system and implement a real web server with multi-tiered storage, evaluate the system with AHS work- loads, and demonstrate significant performance gains while reducing the TCO. The second part of the dissertation pertains to the network system on the client side: Integrating peer- to-peer (P2P) technology with the client-server paradigm results in a much more scalable video content distribution system. AHS is a paradigm for client-driven video streaming; its philosophy matches well with that of P2P video streaming. An adaptation mechanism is the most important component of AHS that determines overall video streaming quality and user experience. We show a throughput-smoothing-based adaptation mechanism that is designed for a client-server architecture does not work well for a P2P architecture. We pro- vide a buffer-based adaptation mechanism, evaluate our solution with OMNeT++/INET simulator, and demonstrate significant performance gains.

Video traffic constitutes a major part of the Internet traffic nowadays. Yet most video delivery services remain best-effort, relying on server bandwidth over-provisioning to guarantee Quality of Service (QoS). Cloud computing is changing the way that video services are offered, enabling elastic and efficient resource allocation through auto-scaling. In this thesis, we propose a new framework of cloud workload management for multimedia delivery services, incorporating demand forecast, predictive resource allocation and quality assurance, as well as resource pricing as inter-dependent components. Based on the trace analysis of a production Video-on-Demand (VoD) system, we propose time-series techniques to predict video bandwidth demand from online monitoring, and determine bandwidth reservations from multiple data centers and the related load direction policy. We further study how such quality-guaranteed cloud services should be priced, in both a game theoretical model and an optimization model.Particularly, when multiple video providers coexist to use cloud resources, we use pricing to control resource allocation in order to maximize the aggregate network utility, which is a standard network utility maximization (NUM) problem with coupled objectives. We propose a novel class of iterative distributed solutions to such problems with a simple economic interpretation of pricing. The method proves to be more efficient than the conventional approach of dual decomposition and gradient methods for large-scale systems, both in theory and in trace-driven simulations.

Video traffic constitutes a major part of the Internet traffic nowadays. Yet most video delivery services remain best-effort, relying on server bandwidth over-provisioning to guarantee Quality of Service (QoS). Cloud computing is changing the way that video services are offered, enabling elastic and efficient resource allocation through auto-scaling. In this thesis, we propose a new framework of cloud workload management for multimedia delivery services, incorporating demand forecast, predictive resource allocation and quality assurance, as well as resource pricing as inter-dependent components. Based on the trace analysis of a production Video-on-Demand (VoD) system, we propose time-series techniques to predict video bandwidth demand from online monitoring, and determine bandwidth reservations from multiple data centers and the related load direction policy. We further study how such quality-guaranteed cloud services should be priced, in both a game theoretical model and an optimization model.Particularly, when multiple video providers coexist to use cloud resources, we use pricing to control resource allocation in order to maximize the aggregate network utility, which is a standard network utility maximization (NUM) problem with coupled objectives. We propose a novel class of iterative distributed solutions to such problems with a simple economic interpretation of pricing. The method proves to be more efficient than the conventional approach of dual decomposition and gradient methods for large-scale systems, both in theory and in trace-driven simulations.

The past decade has witnessed the fast development of peer-assisted video ondemand (PA-VoD) systems, which have attracted millions of online users. The efforts on improving the quality of video programs have never ceased since the beginning, and nowadays offering high-definition (HD) channels has become a common practice. However, compared with standard-definition (SD) channels, HD channels have to sustain a higher streaming rate to peers, which is a challenging task. In real systems, HD channels often suffer from poor streaming quality, or impose a heavy burden on the servers. This thesis conducts an in-depth study on peer cache and upload bandwidth management at the same time for multi-channel PA-VoD systems, where HD and SD channels coexist with different bandwidth and cache requirements. The objective is to minimize the server bandwidth consumption, and thus the maintenance cost of VoD service providers. The solution is cross-channel allocation (or view-upload decoupling), i.e., making SD channels help HD viewers with the surplus peer-contributed resources. The management of these resources includes bandwidth allocation and caching strategies. We first propose a generic modeling framework to capture the essential characteristics of PA-VoD systems: the demand and supply of bandwidth from peers. Our modeling framework can be customized or extended to model a variety of caching strategies, including FIFO, passive caching, and active caching with different user behaviors. We then apply the modeling framework to two representative scenarios: stationary scenarios, where the channels have fixed popularity; and non-stationary scenarios, in which a new movie is released, and peers enter the channel in a flash-crowd manner. We prove using our models that passive caching is efficient for stationary user behaviors, and derive the optimal caching solutions when the channels in the system demonstrate different popularity evolutions, i.e., with non-stationary behaviors. With the insights gained from our modeling work, we design effective centralized heuristic algorithms and practical distributed strategies for peer cache replacement and upload bandwidth allocation, with a near-optimal utilization of these resources. We propose centralized and distributed cross-channel allocation, and also extend the substreaming technique from live streaming to VoD systems, where it demonstrates its extreme feasibility. Our extensive simulation results verify the efficacy of these heuristic and practical strategies. / Graduate / 0984 / changlecsu@gmail.com

Από τις αρχές της δεκαετίας του 90 η υπηρεσία Video on Demand έπαιξε σημαντικό ρόλο στην εφαρμογή της διαδραστικής τηλεόρασης του εξωτερικού. Η ραγδαία αύξηση της χρήσης του διαδικτύου και κυρίως η βελτίωση των υποδομών αυτού έχουν επιφέρει σε παγκόσμιο επίπεδο τεράστιες μεταβολές στις μορφές επικοινωνίας οι οποίες έχουν καταστεί πλέον πιο άμεσες από ποτέ. Ως αποτέλεσμα αναπτύχθηκαν αρκετές δικτυακές εφαρμογές ασύγχρονου video streaming ή video on demand. Ωστόσο οι αυξημένες απαιτήσεις τους σε κλιμάκωση (scalability), προσαρμοστικότητα (flexibility), ανεκτικότητα σε σφάλματα και απόδοση, καθιστούν απαραίτητη την υποστήριξή τους από κατανεμημένες ή και παράλληλες αρχιτεκτονικές. Μία αρκετά υποσχόμενη προσέγγιση προς αυτή την κατεύθυνση είναι τα p2p (peer to peer) συστήματα καθώς οι ίδιοι οι χρήστες των εφαρμογών διαθέτουν ένα τεράστιο σύνολο από δικτυακή και υπολογιστική ισχύ. Στα συστήματα αυτά το περιεχόμενο που κατεβάζουν οι χρήστες διασπάται σε κομμάτια τα οποία ανταλλάσσονται από αυτούς, με σκοπό την τελική επανασύνδεση και ανάκτηση του συνολικού συρμού των δεδομένων. Ιδιαίτερο ενδιαφέρον παρουσιάζει η απαίτηση του χρήστη να παρακολουθεί μη διαδοχικά σημεία του video, να κάνει δηλαδή “άλματα” και πώς αυτή διαχειρίζεται από ένα p2p σύστημα. Σκοπός αυτής της διπλωματικής είναι η μελέτη της απόδοσης των p2p συστημάτων σε συνθήκες όπου οι χρήστες εκτελούν άλματα και η πρόταση αλγορίθμων για τη βέλτιστη διαχείριση τέτοιων αιτημάτων. Ως βέλτιστη θεωρούμε την κατάσταση στην οποία οι χρήστες δεν υπερφορτώνονται με εξερχόμενες συνδέσεις και δεν μένουν ποτέ χωρίς εισερχόμενες, ώστε να εξασφαλίζεται η συνεχής ροή του video. / The goal of each P2P VoD system is the provision of a real time streaming service in which each user (peer) is able to consume every point (part of the video) of every distribution object the time instant that demands it. The rapid, reliable and efficient transmission of the distribution object consist the core of the problem. The distribution of each object is done by exploiting both the upload bandwidth of the server and participating peers.Without loss of generality, in a P2P Video on demand (VoD) system a source(s) (named server) owns a set of videos which noted as distribution objects. The source (s) is responsible for providing the distribution object and contributes its upload bandwidth towards this objective. Peers that are clients of the streaming service act simultaneously as upload bandwidth contributors for the provision of the service. An interesting aspect of VoD is seeking functionality, in which a node can "jump" to another point of the video. In this thesis we introduce an algorithm tha approaches the issue of seeking an efficient way without unbalancing the traffic load