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Dynamic Bandwidth Adjustment for Instant Replay of Live Streams on BitTorrent Networks
Abstract
In general, people watching a live streaming program would sit and wait for its broadcasting at the very beginning. However, some of them could not do so and inevitably join in the middle of live program because of unexpected events. This situation would unfortunately result in an incomplete viewing experience, causing viewers not enjoying the full entertainment value of the live program and therefore dissatisfaction with the quality of services. In this paper, we propose the Dynamic Bandwidth Adjustment for Instant Replay of live streams on BitTorrent networks (DBAIR), which in addition to downloading the live content, the surplus bandwidth in a peer is allocated to pre-download broadcasted highlights, providing viewers with the ability to watch instant replays of missed live content. In such a system, the length or popularity of a highlight can be used to determine how to allocate the surplus bandwidth needed to download highlights. Once a user decides to watch a certain highlight, if the allocated bandwidth and the pre-downloaded video chunks does not guarantee smooth playback, bandwidth used to download other highlights can be sequentially borrowed. The experimental results show that with the aid of DBAIR, the time of completely downloading a highlight can be significantly shortened, resulting in better quality of experience.
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Peer-to-peer (P2P) networks play an important role in communication and resource sharing. In recent years, the importance of(P2P) networks has increased due to their scalability and simple, cost-efficient model. P2P file-sharing systems with decentralized file storage have emerged to allow peers to share resources and download files directly from one another. However, one major problem hindering the success of these services is a type of behavior called free-riding, in which a peer consumes system resources for free without sharing anything in return. In this article, we propose an approach based on points for overcoming the effect of free-riding. To evaluate the performance of our proposed algorithm, we compared it to the original BitTorrent protocol. The simulation results show that the proposed algorithm provides fairness between peers and prevents free-riders from downloading files when they reach the credit limit.
BitTorrent (BT) in the last years has been one of the most effective mechanisms for P2P content distribution. Although BT was created for distribution of time insensitive content, in this work we try to identify what are the minimal changes needed in the BT's mechanisms in order to support streaming. The importance of this capability is that the peer will now have the ability to start enjoying the video before the complete download of the video file. This ability is particularly important in highly polluted environments, since the peer can evaluate the quality of the video content early and thus preserve its valuable resources. In a nutshell, our approach gives higher download priority to pieces that are close to be reproduced by the player. This comes in contrast to the original BT protocol, where pieces are downloaded in an out-of-order manner based solely on their rareness. In particular, our approach tries to strike the balance between downloading pieces in: (a) playing order, enabling smooth playback, and (b) the rarest first order, enabling the use of parallel downloading of pieces. In this work, we introduce three different Piece Selection mechanisms and we evaluate them through simulations based on how well they deliver streaming services to the peers.
The ongoing process of globalization leads to a huge demand for highly scalable applications that are able to deal with millions of participants distributed all over the world. Peer-to-peer (P2P) technology enables an arbitrary large number of users to participate in distributed services like content distribution or collaboration tools. In order to verify a new protocol's performance and scalability simulation is a commonly used tool. First, predicting the network and peer behavior in the real world is only feasible if the simulation, i.e. all applied models as well as the peer state, is as realistic as possible. Second, many properties of the system only become observable when the number of participants is sufficiently large. Therefore, verifying the scalability of a system requires simulating huge worldwide networks. Due to limited processing power, central memory and availabe time, both requirements can only be fullfilled if the applied models are very efficient. In this paper we take a closer look at the network layer. We compare the most commonly-used network models and present a very efficient model for applying real-world network transmission times in large scale simulations
Automatic semantic annotation of video streams allows both to extract significant clips for production logging and to index video streams for posterity logging. Automatic annotation for production logging is particularly demanding, as it is applied to non-edited video streams and must rely only on visual information. Moreover, annotation must be computed in quasi real-time. In this paper, we present a system that performs automatic annotation of the principal highlights in soccer video, suited for both production and posterity logging. The knowledge of the soccer domain is encoded into a set of finite state machines, each of which models a specific highlight. Highlight detection exploits visual cues that are estimated from the video stream, and particularly, ball motion, the currently framed playfield zone, players’ positions and colors of players’ uniforms. The highlight models are checked against the current observations, using a model checking algorithm. The system has been developed within the EU ASSAVID project.
This paper considers the problem of adapting the BitTorrent protocol for on-demand streaming. BitTorrent is a popular peer-to-peer file sharing proto- col that efficiently accommodates a large number of requests for file downloads. Two components of the protocol, namely the rarest-first piece selection policy and the tit-for-tat algorithm for peer selection, are acknowledged to contribute toward the protocol's efficiency with respect to time to download files and its resilience to free riders. Rarest-first piece selection, however, is not suitable for on-demand streaming. In this paper, we present a new adaptive window-based piece selection policy that balances the need for piece diversity, which is pro- vided by the rarest-first algorithm, with the necessity of in-order piece retrieval. We also show that this simple modification to the piece selection policy allows the system to be efficient with respect to utilization of available upload capacity of participating peers, and does not break the tit-for-tat incentive scheme which provides resilience to free riders.
We propose a peer-to-peer multimedia streaming solution based on the BitTorrent content-distribution protocol. Our proposal includes two modifications that allow it to deliver multimedia data on time. First, we replace the rarest-first chunk downloading policy of BitTorrent by a policy requiring peers to download first the chunks that they will watch in the near future. Second, we introduce a new randomized tit-for-tat peer selection policy that gives free tries to a larger number of peers and lets them participate sooner in the media distribution. Our simulations indicate that both changes are required to achieve a good streaming quality.
This paper presents the measurement study of locality-aware P2P solutions over real-world Internet AS topol- ogy. By using the accesses of nodes of PlanetLab testbed, we create a detailed AS-level map including the end-to-end path of all nodes, as well as the relationship of all involved ASes. Based on this map, we evaluate the performance of a set of locality-aware P2P solutions, including an optimal solution guaranteeing the minimum AS hop count, as well as modified BitTorrent system with locality-awareness built into its neighbor selection, peer choking/unchoking, and piece selection processes. Our findings suggest that locality-awareness can help existing P2P solution to significantly decrease load on Internet, and achieve shorter downloading time. By comparing the performance of different kinds of locality-aware and traditional BitTorrent systems, we also point out the necessity to tradeoff between the goals of optimizing AS-related performance and achieving fairness among peers such as intra-AS traffic and peer burden fairness.
In this study, we propose a Peer-to-Peer (P2P) Video-on-Demand (VoD) streaming method which adjusts the receiving rate of pieces by considering the playback deadline of the pieces to reduce interrupted playback. P2P VoD streaming methods based on BitTorrent, such as BitTorrent Streaming (BiToS) and BiToS + Immediacy and Scarcity (BIS), have been proposed to support streaming. In the piece selection strategies of these two methods, a peer probabilistically selects a piece considering immediacy and/or scarcity (i.e., rarity) and receives the selected piece to reduce interrupted playback. However, the piece selection mechanisms still cause interrupted playback owing to probabilistic piece selection. In our proposed P2P VoD streaming method, a peer sequentially selects a piece, starting from the first piece and receives the selected piece at a transfer rate in time for predicted playback start time. As a result, the interrupted playback can be reduced further. In evaluation simulations, we show that the proposed streaming method outperforms previous streaming methods in terms of media playback continuity.
In recent years, the BitTorrent (BT) has been one of the most efficient mechanisms for Peer-to-Peer (P2P) non-realtime content distribution. Many approaches for streaming videos over BT have been proposed by modifying the piece selection policy to cope with the real time requirement. Most of them provide the continuity of video playback at the cost of the variety of pieces on P2P streaming networks. In this paper, we propose the novel urgency-aware BT streaming mechanism, called UR-Aware, which intends to enhance the video streaming efficiency over BT on P2P networks by balancing playback continuity and distribution of piece rareness. There are two sets for piece downloading, called Uset and Rset. The Uset contains the most urgent pieces of video playback, while the Rset contains the rarest pieces. Downloading bandwidth of a peer is dynamically allocated to the two sets based on the number of consecutive pieces beyond these playback position in Uset. Furthermore, to implicitly preserve the continuity of pieces for future playback, consecutive k pieces are grouped as a section which would be selected to insert into Rset based on its rareness. The experimental results show that the UR-Aware has the best performance among other BT streaming approaches in terms of video download time, piece late rate, and network throughput. In addition, the accumulated standard deviation of UR-Aware is closest to that of the native BT among those approaches, which also confirms the superiority of UR-Aware on video streaming over BT.
Peer-to-peer (P2P) live streaming systems have been increasingly popular and successful in today's Internet, which provide large collections of video channels to millions of users at low server costs. The large volumes of P2P streaming traffic are exceeding those incurred by BitTorrent-like file sharing applications, threatening huge traffic relay cost to the Internet service providers (ISPs). There have recently emerged proposals advocating localityaware P2P streaming protocol design, which aim to constrain streaming traffic within ISP boundaries and to alleviate traffic relay cost to the Internet Service Providers (ISPs). Nevertheless, there is a lack of in-depth understanding on the impact of such a locality-aware design on P2P streaming performance. Taking an analytical approach, we model the relation between streaming performance and traffic locality in P2P live streaming systems, in order to acquire useful insights for designing high-performance locality-aware realworld systems. We use end-to-end streaming delays as the performance metric for live streaming, and the number of copies of the live streams imported into an ISP to evaluate the volume of inter-ISP traffic. Considering multiple ISPs at different bandwidth levels, we characterize the generic relationship between the volume of inter-ISP traffic and the streaming performance; we then analyze the traffic volume when the best streaming performance is achieved and the streaming performance when minimum inter-ISP traffic is incurred. Our models and analyses provide intriguing insights on the design of effective locality-aware peer selection protocols and server deployment strategies across multiple ISPs. We also evaluate our models and theoretical results with large-scale simulations under realistic settings.
The peer-to-peer approach can greatly help to cope with highly dynamic live streaming workload by using idle client resources. Yet, P2P streaming typically comes at the cost of increased streaming delays caused by the inevitable multi-hop forwarding of content by peers within the overlay. Various P2P streaming approaches have been proposed aiming at a good tradeoff between flexibility, streaming delay, and costs in terms of traffic overhead for both content providers and clients. Recently, BitTorrent Inc. released a new P2P live streaming system termed BTLive, specifically targeted at low delay and low overhead. For content providers investigating the applicability of BTLive’s approach, it is essential to understand its properties as well as its limitations. So far, no publicly available study exists that quantitatively analyzes BTLive’s performance. To this end, this paper presents a measurement study of the official beta version of BTLive. The study aims to answer the following key questions: How peer-to-peer is BTLive? How delay optimized is BTLive? What is the overhead of BTLive? To answer these questions, traces of real BTLive traffic between a broadcast server and a number of peers deployed across Europe have been analyzed.
In recent years, the demand for live video streaming has steadily increased. Unfortunately, current video streaming architectures embody a number of drawbacks, which impact the quality of live video streaming and place a heavy demand on the video streaming server. Client–server architectures engender issues of network congestion, server bottlenecks and load-balancing, often leading to poor quality video playback at the client and thus making them inappropriate for live video streaming. Moreover, most live video streaming systems offer only a single, fixed bit rate video stream, which is typically not appropriate for all clients. If this bit rate is too high, then some clients may not possess sufficient bandwidth to view the video stream. Conversely, if it is set too low, then all clients will receive a low quality video stream, even those whose bandwidth can support a higher standard. The aforementioned issues can be addressed using multiple bit rate video streaming, thereby allowing clients to download content at a rate appropriate for their bandwidth. This paper focuses on the utilization of a BitTorrent-based, Peer-to-Peer (P2P) architecture, which mitigates the load on the video streaming server whilst supporting multiple bit rate live video streaming. Using this architecture, each client is able to share the responsibility of the streaming server by providing part of the steamed video content to other clients. Simulations conducted indicate that the proposed architecture offers better performance than both: the client–server approach and current P2P-based live video streaming systems.
In this paper we present findings from our windowing BitTorrent simulations and show that by carefully optimizing other factors a reasonable level of performance can be achieved while leaving the original BitTorrent tit-for-tat mechanism intact. We compare the previously proposed windowing piece selection algorithms for BitTorrent and propose a new one, called the stretching window algorithm. We also propose a new method for reducing buffering times, adjusting the window size as the download progresses, and we show its effectiveness. We also observe that windowing BitTorrent algorithms exhibit steady state behavior, and that even a small level of altruism leads to significantly improved system performance.
Bittorrent is currently one of the most popular peer-to-peer (P2P) file sharing protocols. However, it incurs such excessive amount of traffic that it may adversely affect users of legacy internet applications. To limit this adverse impact, an efficient methodology for bittorrent identification may be needed. In this paper, we propose a novel approach to identify local bittorrent peers. Our approach is based on behaviors of the choke algorithm, a main algorithm used in bittorrent. An advantage of our approach is that we can identify bittorrent peers without examining the packet pay-load. Therefore, our approach is free from privacy issues and still effective even though the packet payload is encrypted. Unlike previous works, we identify bittorrent hosts at the peer level instead of the flow level. Given that we use only information from network layer instead of transport layer, our work maintains fewer states and achieves robustness to changes in the transport layer. Furthermore, our work is effective even in restricted environments such as networks equipped with NAT devices or firewalls without modifications to existing network equipments. Our experimental result indicates that our approach can efficiently identify most of excessive bandwidth-consuming peers (i.e., peers transfer a large amount of data in our traces) with a low false-positive rate.
Recently efficient and scalable live video streaming system over the Internet has become a hot topic. In order to improve the system performance metrics, such as startup delay, source-to-end delay, playback continuity and scalability, many previous works developed two successful cases of content distribution network (CDN) and peer-to-peer (P2P) Network for the design of large-scale live video streaming systems, but no single one has yet delivered both the scale and service quality. To combine the advantages of CDN and P2P network has been considered as a feasible orientation for large-scale video stream delivering. In this paper, we propose a peer-assisted content distribution network, i.e. PACDN, which borrows the mesh-based P2P ideas into the traditional CDN to enhance the performance and scalability. The basic features of PACDN include: 1) To meet the real time requirement of live video stream service, i.e. to ensure that the video stream could be continuously and stably delivered from the source to each edge server for offering good QoS to different regions clients, the placement edge servers and source streaming server(s) build a hierarchical multi-tree based and in-hierarchy peer-assisted overlay, which is optimized according to the knowledge of underlying physical topology. This scheme in the design is called "server side peer-assisted". 2) To enhance the system scalability and reduce the deployment cost, clients and edge servers construct a Client/Server based and P2P network assisted overlay with the increasing of viewers, which is called "client side peer-assisted" in this design. We compare the inner performance of PACDN with existing approaches based on comprehensive simulations and analysis. The results show that our proposed design outperforms previous systems in the service quality and scalability. PACDN has been implemented as an Internet live video streaming service and it was successfully deployed for broadcasting many important live programs in Ch- ina in 2007. The industrial experiences prove that this design is scalable and reliable. We believe that the wide deployment of PACDN and its further development will soon benefit many more Internet users.
The BitTorrent file distribution system uses tit-for-tat as a method of seeking pareto efficiency. It achieves a higher level of robustness and resource utilization than any currently known cooperative technique. We explain what BitTorrent does, and how economic methods are used to achieve that goal.
In many sports games like soccer, a major portion of the essence is captured in relatively short durations of intense actions. These highlights are summaries of the games. The capture and effective presentation of these action highlights serve as an important browsing mechanism in a video library of soccer games, and require special techniques for the analyses of digital video. In this paper we present techniques to automatically detect and extract the soccer highlights by analyzing the image contents, and to present these shots of action by the panoramic reconstruction of selected events. The analyses include the recognition of prominent features of the game, tracking of ball, camera movement compensation for effective recognition, and construction of the panoramic views. 1. INTRODUCTION The length of a typical soccer game is more than an hour. In tournaments like the World Cup, 52 games are played. In a video library of soccer games, one may find hundreds of hours game recordings. ...
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