Cooperative announcement-based caching for video-on-demand streaming

Recently, video-on-demand (VoD) streaming services like Netflix and Hulu have gained a lot of popularity. This has led to a strong increase in bandwidth capacity requirements in the network. To reduce this network load, the design of appropriate caching strategies is of utmost importance. Based on the fact that, typically, a video stream is temporally segmented into smaller chunks that can be accessed and decoded independently, cache replacement strategies have been developed that take advantage of this temporal structure in the video. In this paper, two caching strategies are proposed that additionally take advantage of the phenomenon of binge watching, where users stream multiple consecutive episodes of the same series, reported by recent user behavior studies to become the everyday behavior. Taking into account this information allows us to predict future segment requests, even before the video playout has started. Two strategies are proposed, both with a different level of coordination between the caches in the network. Using a VoD request trace based on binge watching user characteristics, the presented algorithms have been thoroughly evaluated in multiple network topologies with different characteristics, showing their general applicability. It was shown that in a realistic scenario, the proposed election-based caching strategy can outperform the state-of-the-art by 20% in terms of cache hit ratio while using 4% less network bandwidth

Design of Scalable On-Demand Video Streaming Systems Leveraging Video Viewing Patterns

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

Ontwerp en evaluatie van content distributie netwerken voor multimediale streaming diensten.

Traditionele Internetgebaseerde diensten voor het verspreiden van bestanden, zoals Web browsen en het versturen van e-mails, worden aangeboden via één centrale server. Meer recente netwerkdiensten zoals interactieve digitale televisie of video-op-aanvraag vereisen echter hoge kwaliteitsgaranties (QoS), zoals een lage en constante netwerkvertraging, en verbruiken een aanzienlijke hoeveelheid bandbreedte op het netwerk. Architecturen met één centrale server kunnen deze garanties moeilijk bieden en voldoen daarom niet meer aan de hoge eisen van de volgende generatie multimediatoepassingen. In dit onderzoek worden daarom nieuwe netwerkarchitecturen bestudeerd, die een dergelijke dienstkwaliteit kunnen ondersteunen. Zowel peer-to-peer mechanismes, zoals bij het uitwisselen van muziekbestanden tussen eindgebruikers, als servergebaseerde oplossingen, zoals gedistribueerde caches en content distributie netwerken (CDN's), komen aan bod. Afhankelijk van de bestudeerde dienst en de gebruikte netwerktechnologieën en -architectuur, worden gecentraliseerde algoritmen voor netwerkontwerp voorgesteld. Deze algoritmen optimaliseren de plaatsing van de servers of netwerkcaches en bepalen de nodige capaciteit van de servers en netwerklinks. De dynamische plaatsing van de aangeboden bestanden in de verschillende netwerkelementen wordt aangepast aan de heersende staat van het netwerk en aan de variërende aanvraagpatronen van de eindgebruikers. Serverselectie, herroutering van aanvragen en het verspreiden van de belasting over het hele netwerk komen hierbij ook aan bod

Energy efficiency in content delivery networks

The increasing popularity of bandwidth-intensive video Internet services has positioned Content Distribution Networks (CDNs) in the limelight as the emerging provider platforms for video delivery. The goal of CDNs is to maximise the availability of content in the network while maintaining the quality of experience expected by users. This is a challenging task due to the scattered nature of video content sources and destinations. Furthermore, the high energy consumption associated with content distribution calls for developing energy-efficient solutions able to cater for the future Internet. This thesis addresses the problem of content placement and update while considering energy consumption in CDNs. First, this work contributed a new energy-efficient caching scheme that stores the most popular content at the edge of the core network and optimises the size of cached content to minimise energy usage. It takes into account the trend of daily traffic and recommends putting inactive segments of caches in sleep-mode during off-peak hours. Our results showed that power minimisation is achieved by deploying switch-off capable caches, and the trend of active cache segments over the time of day follows the trend of traffic. Second, the study explores different content popularity distributions and determines their influence on power consumption. The distribution of content popularity dictates the resultant cache hit ratio achieved by storing a certain number of videos. Therefore, it directly influences the power consumption of the cache. The evaluation results indicated that under video services where the popularity of content is very diverse, the optimum solution is to store the few most popular videos in caches. In contrast, when video popularities are similar, the most power efficient scheme is either to cache the whole library or to avoid caching completely depending on the size of the video library. Third, this thesis contributed an evaluation of the power consumption of the network under real world TV data and considering standard and high definition TV programmes. We proposed a cache replacement algorithm based on the predictable nature of TV viewings. The time-driven proactive cache replacement algorithm replaces cache contents several times a day to minimise power consumption. The algorithm achieves major power savings on top of the power reductions introduced by caching. CDNs are expected to continue to be the backbone for Internet video applications. This work has shown that storing the right amount of popular videos in core caches reduces from 42% to 72% of network power consumption considering a range of content popularity distributions. Maintaining up-to-date cache contents reduces up to 48% and 86% of power consumption considering fixed and sleep-mode capable caches, respectively. Reducing the energy consumption of CDNs provides a valuable contribution for future green video delivery

Content-aware resource allocation model for IPTV delivery networks

Nowadays, with the evolution of digital video broadcasting, as well as, the advent of high speed broadband networks, a new era of TV services has emerged known as IPTV. IPTV is a system that employs the high speed broadband networks to deliver TV services to the subscribers. From the service provider viewpoint, the challenge in IPTV systems is how to build delivery networks that exploits the resources efficiently and reduces the service cost, as well. However, designing such delivery networks affected by many factors including choosing the suitable network architecture, load balancing, resources waste, and cost reduction. Furthermore, IPTV contents characteristics, particularly; size, popularity, and interactivity play an important role in balancing the load and avoiding the resources waste for delivery networks. In this paper, we investigate the problem of resource allocation for IPTV delivery networks over the recent architecture, peer-service area architecture. The Genetic Algorithm as an optimization tool has been used to find the optimal provisioning parameters including storage, bandwidth, and CPU consumption. The experiments have been conducted on two data sets with different popularity distributions. The experiments have been conducted on two popularity distributions. The experimental results showed the impact of content status on the resource allocation process

Smart PIN: performance and cost-oriented context-aware personal information network

The next generation of networks will involve interconnection of heterogeneous individual networks such as WPAN, WLAN, WMAN and Cellular network, adopting the IP as common infrastructural protocol and providing virtually always-connected network. Furthermore, there are many devices which enable easy acquisition and storage of information as pictures, movies, emails, etc. Therefore, the information overload and divergent content’s characteristics make it difficult for users to handle their data in manual way. Consequently, there is a need for personalised automatic services which would enable data exchange across heterogeneous network and devices. To support these personalised services, user centric approaches for data delivery across the heterogeneous network are also required. In this context, this thesis proposes Smart PIN - a novel performance and cost-oriented context-aware Personal Information Network. Smart PIN's architecture is detailed including its network, service and management components. Within the service component, two novel schemes for efficient delivery of context and content data are proposed: Multimedia Data Replication Scheme (MDRS) and Quality-oriented Algorithm for Multiple-source Multimedia Delivery (QAMMD). MDRS supports efficient data accessibility among distributed devices using data replication which is based on a utility function and a minimum data set. QAMMD employs a buffer underflow avoidance scheme for streaming, which achieves high multimedia quality without content adaptation to network conditions. Simulation models for MDRS and QAMMD were built which are based on various heterogeneous network scenarios. Additionally a multiple-source streaming based on QAMMS was implemented as a prototype and tested in an emulated network environment. Comparative tests show that MDRS and QAMMD perform significantly better than other approaches

Video-on-Demand over Internet: a survey of existing systems and solutions

Video-on-Demand is a service where movies are delivered to distributed users with low delay and free interactivity. The traditional client/server architecture experiences scalability issues to provide video streaming services, so there have been many proposals of systems, mostly based on a peer-to-peer or on a hybrid server/peer-to-peer solution, to solve this issue. This work presents a survey of the currently existing or proposed systems and solutions, based upon a subset of representative systems, and defines selection criteria allowing to classify these systems. These criteria are based on common questions such as, for example, is it video-on-demand or live streaming, is the architecture based on content delivery network, peer-to-peer or both, is the delivery overlay tree-based or mesh-based, is the system push-based or pull-based, single-stream or multi-streams, does it use data coding, and how do the clients choose their peers. Representative systems are briefly described to give a summarized overview of the proposed solutions, and four ones are analyzed in details. Finally, it is attempted to evaluate the most promising solutions for future experiments. Résumé La vidéo à la demande est un service où des films sont fournis à distance aux utilisateurs avec u

Improved Iptv Channel Change times Through Multicast Caching of Pre-selected Channels

Name: RAY, THOMAS Date of Degree: DECEMBER, 2014 Title of Study: IMPROVED IPTV CHANNEL CHANGE TIMES THROUGH MULTICAST CACHING OF PRE-SELECTED CHANNELSMajor Field: ELECTRICAL ENGINEERINGAbstract: IPTV has grown in recent years to an estimated 100 million users worldwide. IPTV uses IGMP processes to stream an individual channel to a user until the next channel change when the current channel is stopped and the new selection begins streaming. One of the critical factors determining customer satisfaction is the requirement to have reasonably rapid channel change times of 2 seconds or less, but current channel change times are frequently above that threshold. Numerous research efforts have been ongoing to reduce these times including edge servers, I-frame management, buffering improvements, dynamic video coding, and pre-selecting channels. Channel pre-selection involves sending additional channels in hopes that the user's next selection will already be present at the user's set top box to reduce the channel change time. While this pre-selection technique has previously been proposed, the proposals have been limited in scope, typically based on set top box replacement, and lack specific details regarding the expected channel change reductions attained. This research addressed all of these shortcomings beginning with laboratory testing to verify that the channel change time reduction for successful pre-selection is two times the network delay plus the IGMP processing time which equates to an average of 320 millisecond reduction per channel change. Several pre-selection models were developed and evaluated using theoretical calculations, functional testing, and performance simulations. Sample data was generated to reflect a wide range of user IPTV viewing behavior for use in the performance simulations. The top two models resulted in an average of well over 70% success rates in accurately pre-streaming the user's next selection in the multicast cache output. This approach also has the benefit of being implemented on IPTV provider equipment and would typically only require firmware upgrades without the need for expensive new equipment or changes to existing standards. Operational considerations were also discussed to reduce problems and delays during the implementation phase of the system. Additional applications and future improvements were also presented.Electrical Engineerin