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

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

Ad-hoc Stream Adaptive Protocol

With the growing market of smart-phones, sophisticated applications that do extensive computation are common on mobile platform; and with consumers’ high expectation of technologies to stay connected on the go, academic researchers and industries have been making efforts to find ways to stream multimedia contents to mobile devices. However, the restricted wireless channel bandwidth, unstable nature of wireless channels, and unpredictable nature of mobility, has been the major road block for wireless streaming advance forward. In this paper, various recent studies on mobility and P2P system proposal are explained and analyzed, and propose a new design based on existing P2P systems, aimed to solve the wireless and mobility issues

Watch Global, Cache Local: YouTube Network Traffic at a Campus Network - Measurements and Implications

User Generated Content has become very popular since the birth of web services such as YouTube allowing the distribution of such user-produced media content in an easy manner. YouTube-like services are different from existing traditional VoD services because the service provider has only limited control over the creation of new content. We analyze how the content distribution in YouTube is realized and then conduct a measurement study of YouTube traffic in a large university campus network. The analysis of the traffic shows that: (1) No strong correlation is observed between global and local popularity; (2) neither time scale nor user population has an impact on the local popularity distribution; (3) video clips of local interest have a high local popularity. Using our measurement data to drive trace-driven simulations, we also demonstrate the implications of alternative distribution infrastructures on the performance of a YouTube-like VoD service. The results of these simulations show that client-based local caching, P2P-based distribution, and proxy caching can reduce network traffic significantly and allow faster access to video clips

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

Decentralized Adaptive Helper Selection in Multi-channel P2P Streaming Systems

In Peer-to-Peer (P2P) multichannel live streaming, helper peers with surplus bandwidth resources act as micro-servers to compensate the server deficiencies in balancing the resources between different channel overlays. With deployment of helper level between server and peers, optimizing the user/helper topology becomes a challenging task since applying well-known reciprocity-based choking algorithms is impossible due to the one-directional nature of video streaming from helpers to users. Because of selfish behavior of peers and lack of central authority among them, selection of helpers requires coordination. In this paper, we design a distributed online helper selection mechanism which is adaptable to supply and demand pattern of various video channels. Our solution for strategic peers' exploitation from the shared resources of helpers is to guarantee the convergence to correlated equilibria (CE) among the helper selection strategies. Online convergence to the set of CE is achieved through the regret-tracking algorithm which tracks the equilibrium in the presence of stochastic dynamics of helpers' bandwidth. The resulting CE can help us select proper cooperation policies. Simulation results demonstrate that our algorithm achieves good convergence, load distribution on helpers and sustainable streaming rates for peers