Conference Paper

Storage optimization for a peer-to-peer video-on-demand network

DOI: 10.1145/1730836.1730844 Conference: Proceedings of the First Annual ACM SIGMM Conference on Multimedia Systems, MMSys 2010, Phoenix, Arizona, USA, February 22-23, 2010
Source: DBLP


This paper explores requirements for efficient pre-seeding of video-on-demand (VoD) movie data onto numerous customer set-top boxes in a cable ISP environment. The pre-seeded content will then be distributed to other set-top boxes in the same cable community using a peer-to-peer (P2P) network protocol such as BitTorrent. The challenges and solutions required for P2P VoD provided by a fixed provider such as a cable company are fundamentally different from those seen in traditional P2P networks or client-server VoD solutions. Our work pre-positions data into set-top boxes using a mathematical programming algorithm. The objective of the algorithm is to minimize uplink traffic, given a popularity model for various pieces of content and information about storage and bandwidth capacity constraints at the customer nodes. Given the complex non-linear nature of P2P interactions, these mathematical programs are solved using non-linear optimization approaches. Using a BitTorrent-like peer-to-peer data delivery system, we show through extensive simulations that our mathematical model for pre-seeding data based on object popularity and node bandwidth availability leads to noticeably greater reductions in uplink traffic and VoD server load than a weighted-random pre-seeding scheme that only considers object popularity.

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    • "The peers help to reduce the traffic in the network core, but the servers still remain an inevitable part of the system that guarantees the required QoS. These solutions together with various content distribution schemes prove to be efficient in reducing [4], [5], [6], [7], [8], [9] and even eliminating the traffic requested from the streaming servers [10], [11]. "
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    ABSTRACT: Video on Demand is a leading TV service offered by the IPTV operators in the past decade that has been rapidly gaining on popularity because it offers great convenience to the customers to watch any video they want at any time. However, the drawback of this service it that it is very resource demanding and expensive for the operator. One of the solutions for reducing the high traffic demands from the video servers is the imple-mentation of peer-assisted streaming, i.e., including the peers in the streaming process by taking advantage of their unused streaming and storage capacity. In order to estimate the reduction of the traffic demand depending on the network configuration and the intensity of demands for videos, we developed a stochastic model that determines the system behavior in stationary state. We proved that the model is a precise tool for estimating the server demands. However, the model requires high computation power for obtaining the desired results. The size of the number of linear equations that have to be solved grows rapidly with the growth of the number of peers and their streaming capacity, which is serious issue for using the model as a tool for estimation of the system performance. Therefore, we propose a sampling method that significantly reduces the size of the system of linear equations, and thus, reduces the computation time and resources required for obtaining the results. Our analysis shows that although the size of the system is reduced, the relative error compared to the original unreduced system is negligible.
    Full-text · Conference Paper · Apr 2014
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    • "CoopNet, PALS, PROP, Toast, and Zebroid provide on-demand streaming using P2P networks. Each of these systems seeks to support an infrastructure-based system with P2P networks and thus achieves scalability to some extent [20] [21]. However, all these existing solutions are not sufficient to provide effective services in the current scenario. "
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    ABSTRACT: Recently, many video applications like video telephony, video conferencing, Video-on-Demand (VoD), and so forth have produced heterogeneous consumers in the Internet. In such a scenario, media servers play vital role when a large number of concurrent requests are sent by heterogeneous users. Moreover, the server and distributed client systems participating in the Internet communication have to provide suitable resources to heterogeneous users to meet their requirements satisfactorily. The challenges in providing suitable resources are to analyze the user service pattern, bandwidth and buffer availability, nature of applications used, and Quality of Service (QoS) requirements for the heterogeneous users. Therefore, it is necessary to provide suitable techniques to handle these challenges. In this paper, we propose a framework for peer-to-peer- (P2P-) based VoD service in order to provide effective video streaming. It consists of four functional modules, namely, Quality Preserving Multivariate Video Model (QPMVM) for efficient server management, tracker for efficient peer management, heuristic-based content distribution, and light weight incentivized sharing mechanism. The first two of these modules are confined to a single entity of the framework while the other two are distributed across entities. Experimental results show that the proposed framework avoids overloading the server, increases the number of clients served, and does not compromise on QoS, irrespective of the fact that the expected framework is slightly reduced.
    Full-text · Article · Nov 2012 · Advances in Multimedia
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    ABSTRACT: Recently, a new peer-assisted architecture to build content delivery systems has been presented. This architecture is based on the use of the storage capacity of end-users’ set-top boxes (STBs), connected in a peer-to-peer (P2P) manner in order to help the content servers in the delivery process. In these systems, the contents are usually split into a set of smaller pieces, called sub-streams, which are randomly injected at the STBs. The present paper is focused on Video on Demand (VoD) streaming and it is assumed that the STB-based content delivery system is deployed over the global Internet, where the clients are distributed over different ISP networks. In this scenario, three different strategies are studied for increasing the percentage of data uploaded by peers, in order to offload the content servers as much as possible. First of all, a new mechanism is presented which determines which sub-stream has to be placed at which STB by a Non-Linear Programming (NLP) formulation. A different strategy for reducing the content server load is to take advantage of the available bandwidth in the different ISP networks. In this sense, two new mechanisms for forwarding the VoD requests to different ISP networks are presented. Finally, the present paper also shows that in some situations the available uplink bandwidth is associated with STBs that do not have the required sub-streams. Regarding this concern, a new mechanism has been designed that dynamically re-allocates some streams, which are being transmitted from specific STBs, to different STBs, in order to find the necessary resources to start new streaming sessions.
    No preview · Article · Sep 2012 · Peer-to-Peer Networking and Applications
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