Building Internet caching systems for streaming media delivery

The proxy has been widely and successfully used to cache the static Web objects fetched by a client so that the subsequent clients requesting the same Web objects can be served directly from the proxy instead of other sources faraway, thus reducing the server\u27s load, the network traffic and the client response time. However, with the dramatic increase of streaming media objects emerging on the Internet, the existing proxy cannot efficiently deliver them due to their large sizes and client real time requirements.;In this dissertation, we design, implement, and evaluate cost-effective and high performance proxy-based Internet caching systems for streaming media delivery. Addressing the conflicting performance objectives for streaming media delivery, we first propose an efficient segment-based streaming media proxy system model. This model has guided us to design a practical streaming proxy, called Hyper-Proxy, aiming at delivering the streaming media data to clients with minimum playback jitter and a small startup latency, while achieving high caching performance. Second, we have implemented Hyper-Proxy by leveraging the existing Internet infrastructure. Hyper-Proxy enables the streaming service on the common Web servers. The evaluation of Hyper-Proxy on the global Internet environment and the local network environment shows it can provide satisfying streaming performance to clients while maintaining a good cache performance. Finally, to further improve the streaming delivery efficiency, we propose a group of the Shared Running Buffers (SRB) based proxy caching techniques to effectively utilize proxy\u27s memory. SRB algorithms can significantly reduce the media server/proxy\u27s load and network traffic and relieve the bottlenecks of the disk bandwidth and the network bandwidth.;The contributions of this dissertation are threefold: (1) we have studied several critical performance trade-offs and provided insights into Internet media content caching and delivery. Our understanding further leads us to establish an effective streaming system optimization model; (2) we have designed and evaluated several efficient algorithms to support Internet streaming content delivery, including segment caching, segment prefetching, and memory locality exploitation for streaming; (3) having addressed several system challenges, we have successfully implemented a real streaming proxy system and deployed it in a large industrial enterprise

Architecture for Cooperative Prefetching in P2P Video-on- Demand System

Most P2P VoD schemes focused on service architectures and overlays optimization without considering segments rarity and the performance of prefetching strategies. As a result, they cannot better support VCRoriented service in heterogeneous environment having clients using free VCR controls. Despite the remarkable popularity in VoD systems, there exist no prior work that studies the performance gap between different prefetching strategies. In this paper, we analyze and understand the performance of different prefetching strategies. Our analytical characterization brings us not only a better understanding of several fundamental tradeoffs in prefetching strategies, but also important insights on the design of P2P VoD system. On the basis of this analysis, we finally proposed a cooperative prefetching strategy called "cooching". In this strategy, the requested segments in VCR interactivities are prefetched into session beforehand using the information collected through gossips. We evaluate our strategy through extensive simulations. The results indicate that the proposed strategy outperforms the existing prefetching mechanisms.Comment: 13 Pages, IJCN

Interactivity And User-heterogeneity In On Demand Broadcast Video

Video-On-Demand (VOD) has appeared as an important technology for many multimedia applications such as news on demand, digital libraries, home entertainment, and distance learning. In its simplest form, delivery of a video stream requires a dedicated channel for each video session. This scheme is very expensive and non-scalable. To preserve server bandwidth, many users can share a channel using multicast. Two types of multicast have been considered. In a non-periodic multicast setting, users make video requests to the server; and it serves them according to some scheduling policy. In a periodic broadcast environment, the server does not wait for service requests. It broadcasts a video cyclically, e.g., a new stream of the same video is started every t seconds. Although, this type of approach does not guarantee true VOD, the worst service latency experienced by any client is less than t seconds. A distinct advantage of this approach is that it can serve a very large community of users using minimal server bandwidth. In VOD System it is desirable to provide the user with the video-cassette-recorder-like (VCR) capabilities such as fast-forwarding a video or jumping to a specific frame. This issue in the broadcast framework is addressed, where each video and its interactive version are broadcast repeatedly on the network. Existing techniques rely on data prefetching as the mechanism to provide this functionality. This approach provides limited usability since the prefetching rate cannot keep up with typical fast-forward speeds. In the same environment, end users might have access to different bandwidth capabilities at different times. Current periodic broadcast schemes, do not take advantage of high-bandwidth capabilities, nor do they adapt to the low-bandwidth limitation of the receivers. A heterogeneous technique is presented that can adapt to a range of receiving bandwidth capability. Given a server bandwidth and a range of different client bandwidths, users employing the proposed technique will choose either to use their full reception bandwidth capability and therefore accessing the video at a very short time, or using part or enough reception bandwidth at the expense of a longer access latency

Design, analysis, and experimental verification of continuous media retrieval and caching strategies for network-based multimedia services

Ph.DDOCTOR OF PHILOSOPH

Characterizing Popularity Dynamics of User-generated Videos: A Category-based Study of YouTube

Understanding the growth pattern of content popularity has become a subject of immense interest to Internet service providers, content makers and on-line advertisers. This understanding is also important for the sustainable development of content distribution systems. As an approach to comprehend the characteristics of this growth pattern, a significant amount of research has been done in analyzing the popularity growth patterns of YouTube videos. Unfortunately, no work has been done that intensively investigates the popularity patterns of YouTube videos based on video object category. In this thesis, an in-depth analysis of the popularity pattern of YouTube videos is performed, considering the categories of videos. Metadata and request patterns were collected by employing category-specific YouTube crawlers. The request patterns were observed for a period of five months. Results confirm that the time varying popularity of di fferent YouTube categories are conspicuously diff erent, in spite of having sets of categories with very similar viewing patterns. In particular, News and Sports exhibit similar growth curves, as do Music and Film. While for some categories views at early ages can be used to predict future popularity, for some others predicting future popularity is a challenging task and require more sophisticated techniques, e.g., time-series clustering. The outcomes of these analyses are instrumental towards designing a reliable workload generator, which can be further used to evaluate diff erent caching policies for YouTube and similar sites. In this thesis, workload generators for four of the YouTube categories are developed. Performance of these workload generators suggest that a complete category-specific workload generator can be developed using time-series clustering. Patterns of users' interaction with YouTube videos are also analyzed from a dataset collected in a local network. This shows the possible ways of improving the performance of Peer-to-Peer video distribution technique along with a new video recommendation method

Enabling Large-Scale Peer-to-Peer Stored Video Streaming Service with QoS Support

This research aims to enable a large-scale, high-volume, peer-to-peer, stored-video streaming service over the Internet, such as on-line DVD rentals. P2P allows a group of dynamically organized users to cooperatively support content discovery and distribution services without needing to employ a central server. P2P has the potential to overcome the scalability issue associated with client-server based video distribution networks; however, it brings a new set of challenges. This research addresses the following five technical challenges associated with the distribution of streaming video over the P2P network: 1) allow users with limited transmit bandwidth capacity to become contributing sources, 2) support the advertisement and discovery of time-changing and time-bounded video frame availability, 3) Minimize the impact of distribution source losses during video playback, 4) incorporate user mobility information in the selection of distribution sources, and 5) design a streaming network architecture that enables above functionalities.To meet the above requirements, we propose a video distribution network model based on a hybrid architecture between client-server and P2P. In this model, a video is divided into a sequence of small segments and each user executes a scheduling algorithm to determine the order, the timing, and the rate of segment retrievals from other users. The model also employs an advertisement and discovery scheme which incorporates parameters of the scheduling algorithm to allow users to share their life-time of video segment availability information in one advertisement and one query. An accompanying QoS scheme allows reduction in the number of video playback interruptions while one or more distribution sources depart from the service prematurely.The simulation study shows that the proposed model and associated schemes greatly alleviate the bandwidth requirement of the video distribution server, especially when the number of participating users grows large. As much as 90% of load reduction was observed in some experiments when compared to a traditional client-server based video distribution service. A significant reduction is also observed in the number of video presentation interruptions when the proposed QoS scheme is incorporated in the distribution process while certain percentages of distribution sources depart from the service unexpectedly

QoE-Assured 4K HTTP live streaming via transient segment holding at mobile edge

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 on virtualized caching resources at the mobile edge, we have addressed the conventional transport-layer bottleneck and enabled QoE-assured Internet-wide live streaming to support the emerging live streaming services with high data rate requirements

Proactive Mechanisms for Video-on-Demand Content Delivery

Video delivery over the Internet is the dominant source of network load all over the world. Especially VoD streaming services such as YouTube, Netflix, and Amazon Video have propelled the proliferation of VoD in many peoples' everyday life. VoD allows watching video from a large quantity of content at any time and on a multitude of devices, including smart TVs, laptops, and smartphones. Studies show that many people under the age of 32 grew up with VoD services and have never subscribed to a traditional cable TV service. This shift in video consumption behavior is continuing with an ever-growing number of users. satisfy this large demand, VoD service providers usually rely on CDN, which make VoD streaming scalable by operating a geographically distributed network of several hundreds of thousands of servers. Thereby, they deliver content from locations close to the users, which keeps traffic local and enables a fast playback start. CDN experience heavy utilization during the day and are usually reactive to the user demand, which is not optimal as it leads to expensive over-provisioning, to cope with traffic peaks, and overreacting content eviction that decreases the CDN's performance. However, to sustain future VoD streaming projections with hundreds of millions of users, new approaches are required to increase the content delivery efficiency. To this end, this thesis identifies three key research areas that have the potential to address the future demand for VoD content. Our first contribution is the design of vFetch, a privacy-preserving prefetching mechanism for mobile devices. It focuses explicitly on OTT VoD providers such as YouTube. vFetch learns the user interest towards different content channels and uses these insights to prefetch content on a user terminal. To do so, it continually monitors the user behavior and the device's mobile connectivity pattern, to allow for resource-efficient download scheduling. Thereby, vFetch illustrates how personalized prefetching can reduce the mobile data volume and alleviate mobile networks by offloading peak-hour traffic. Our second contribution focuses on proactive in-network caching. To this end, we present the design of the ProCache mechanism that divides the available cache storage concerning separate content categories. Thus, the available storage is allocated to these divisions based on their contribution to the overall cache efficiency. We propose a general work-flow that emphasizes multiple categories of a mixed content workload in addition to a work-flow tailored for music video content, the dominant traffic source on YouTube. Thereby, ProCache shows how content-awareness can contribute to efficient in-network caching. Our third contribution targets the application of multicast for VoD scenarios. Many users request popular VoD content with only small differences in their playback start time which offers a potential for multicast. Therefore, we present the design of the VoDCast mechanism that leverages this potential to multicast parts of popular VoD content. Thereby, VoDCast illustrates how ISP can collaborate with CDN to coordinate on content that should be delivered by ISP-internal multicast

Design and analysis of stream scheduling algorithms in distributed reservation-based multimedia systems

Ph.DDOCTOR OF PHILOSOPH