Improving BitTorrent's Peer Selection For Multimedia Content On-Demand Delivery

The great efficiency achieved by the BitTorrent protocol for the distribution of large amounts of data inspired its adoption to provide multimedia content on-demand delivery over the Internet. As it is not designed for this purpose, some adjustments have been proposed in order to meet the related QoS requirements like low startup delay and smooth playback continuity. Accordingly, this paper introduces a BitTorrent-like proposal named as Quota-Based Peer Selection (QBPS). This proposal is mainly based on the adaptation of the original peer-selection policy of the BitTorrent protocol. Its validation is achieved by means of simulations and competitive analysis. The final results show that QBPS outperforms other recent proposals of the literature. For instance, it achieves a throughput optimization of up to 48.0% in low-provision capacity scenarios where users are very interactive.Comment: International Journal of Computer Networks & Communications(IJCNC) Vol.7, No.6, November 201

Robustness of BitTorrent-like VoD protocols

Besides server supported solutions for Video-on-demand, approaches based on distributed systems such as BitTorrent are being used due to their efficiency and high scalability. There are several protocol variants proposed in the literature, which are mainly concerned with providing mechanisms for piece selection and peer selection. In this paper, using the concept of Design Space Analysis, we give comparisons of the performances of several BitTorrent-like Video-on-demand protocols under the assumption that other protocol variants may also enter the system

Analyzing Peer Selection Policies for BitTorrent Multimedia On-Demand Streaming Systems in Internet

The adaptation of the BitTorrent protocol to multimedia on-demand streaming systems essentially lies on the modification of its two core algorithms, namely the piece and the peer selection policies, respectively. Much more attention has though been given to the piece selection policy. Within this context, this article proposes three novel peer selection policies for the design of BitTorrent-like protocols targeted at that type of systems: Select Balanced Neighbour Policy (SBNP), Select Regular Neighbour Policy (SRNP), and Select Optimistic Neighbour Policy (SONP). These proposals are validated through a competitive analysis based on simulations which encompass a variety of multimedia scenarios, defined in function of important characterization parameters such as content type, content size, and client interactivity profile. Service time, number of clients served and efficiency retrieving coefficient are the performance metrics assessed in the analysis. The final results mainly show that the novel proposals constitute scalable solutions that may be considered for real project designs. Lastly, future work is included in the conclusion of this paper.Comment: 19 PAGE

A Framework For Efficient Data Distribution In Peer-to-peer Networks.

Peer to Peer (P2P) models are based on user altruism, wherein a user shares its content with other users in the pool and it also has an interest in the content of the other nodes. Most P2P systems in their current form are not fair in terms of the content served by a peer and the service obtained from swarm. Most systems suffer from free rider\u27s problem where many high uplink capacity peers contribute much more than they should while many others get a free ride for downloading the content. This leaves high capacity nodes with very little or no motivation to contribute. Many times such resourceful nodes exit the swarm or don\u27t even participate. The whole scenario is unfavorable and disappointing for P2P networks in general, where participation is a must and a very important feature. As the number of users increases in the swarm, the swarm becomes robust and scalable. Other important issues in the present day P2P system are below optimal Quality of Service (QoS) in terms of download time, end-to-end latency and jitter rate, uplink utilization, excessive cross ISP traffic, security and cheating threats etc. These current day problems in P2P networks serve as a motivation for present work. To this end, we present an efficient data distribution framework in Peer-to-Peer (P2P) networks for media streaming and file sharing domain. The experiments with our model, an alliance based peering scheme for media streaming, show that such a scheme distributes data to the swarm members in a near-optimal way. Alliances are small groups of nodes that share data and other vital information for symbiotic association. We show that alliance formation is a loosely coupled and an effective way to organize the peers and our model maps to a small world network, which form efficient overlay structures and are robust to network perturbations such as churn. We present a comparative simulation based study of our model with CoolStreaming/DONet (a popular model) and present a quantitative performance evaluation. Simulation results show that our model scales well under varying workloads and conditions, delivers near optimal levels of QoS, reduces cross ISP traffic considerably and for most cases, performs at par or even better than Cool-Streaming/DONet. In the next phase of our work, we focussed on BitTorrent P2P model as it the most widely used file sharing protocol. Many studies in academia and industry have shown that though BitTorrent scales very well but is far from optimal in terms of fairness to end users, download time and uplink utilization. Furthermore, random peering and data distribution in such model lead to suboptimal performance. Lately, new breed of BitTorrent clients like BitTyrant have shown successful strategic attacks against BitTorrent. Strategic peers configure the BitTorrent client software such that for very less or no contribution, they can obtain good download speeds. Such strategic nodes exploit the altruism in the swarm and consume resources at the expense of other honest nodes and create an unfair swarm. More unfairness is generated in the swarm with the presence of heterogeneous bandwidth nodes. We investigate and propose a new token-based anti-strategic policy that could be used in BitTorrent to minimize the free-riding by strategic clients. We also proposed other policies against strategic attacks that include using a smart tracker that denies the request of strategic clients for peer listmultiple times, and black listing the non-behaving nodes that do not follow the protocol policies. These policies help to stop the strategic behavior of peers to a large extent and improve overall system performance. We also quantify and validate the benefits of using bandwidth peer matching policy. Our simulations results show that with the above proposed changes, uplink utilization and mean download time in BitTorrent network improves considerably. It leaves strategic clients with little or no incentive to behave greedily. This reduces free riding and creates fairer swarm with very little computational overhead. Finally, we show that our model is self healing model where user behavior changes from selfish to altruistic in the presence of the aforementioned policies

On the Optimization of BitTorrent-Like Protocols for Interactive On-Demand Streaming Systems

This paper proposes two novel optimized BitTorrent-like protocols for interactive multimedia streaming: the Simple Interactive Streaming Protocol (SISP) and the Exclusive Interactive Streaming Protocol (EISP). The former chiefly seeks a trade-off between playback continuity and data diversity, while the latter is mostly focused on playback continuity. To assure a thorough and up-to-date approach, related work is carefully examined and important open issues, concerning the design of BitTorrent-like algorithms, are analyzed as well. Through simulations, in a variety of near-real file replication scenarios, the novel protocols are evaluated using distinct performance metrics. Among the major findings, the final results show that the two novel proposals are efficient and, besides, focusing on playback continuity ends up being the best design concept to achieve high quality of service. Lastly, avenues for further research are included at the end of this paper as well.Comment: 20 page

Closest playback-point first: A new peer selection algorithm for P2P VoD systems

Peer-to-peer (P2P) based video-on-demand (VoD) streaming service has been gaining popularity recently. Unlike live streaming, a VoD peer always starts its playback from the beginning of a stored video. The playback-points of different peers, as well as the amount of video contents/pieces they cached, depend on when they join the video session, or their viewing ages. As a result, the upload bandwidth of younger peers tends to be underutilized because older peers are not interested in their cached video pieces. The collaborative piece exchange among peers is undermined due to the unbalanced supply and demand. To address this issue, a playback-point based request peer selection algorithm is proposed in this paper. Specifically, when a peer requests a particular video piece, among the set of potential providers, a request is sent to the peer that has the smallest playback-point difference with itself. We call this request peer selection algorithm closest playback-point first (CPF). With CPF, peers with similar available content can be loosely grouped together for a more balanced collaborative piece exchange. Extensive packet-level simulations show that with CPF, the video playback quality is enhanced and the VoD server load is significantly reduced. © 2011 IEEE.published_or_final_versionThe IEEE Global Telecommunications Conference (GLOBECOM 2011), Houston, TX, USA, 5-9 December 201

Modeling and Evaluation of Multisource Streaming Strategies in P2P VoD Systems

In recent years, multimedia content distribution has largely been moved to the Internet, inducing broadcasters, operators and service providers to upgrade with large expenses their infrastructures. In this context, streaming solutions that rely on user devices such as set-top boxes (STBs) to offload dedicated streaming servers are particularly appropriate. In these systems, contents are usually replicated and scattered over the network established by STBs placed at users' home, and the video-on-demand (VoD) service is provisioned through streaming sessions established among neighboring STBs following a Peer-to-Peer fashion. Up to now the majority of research works have focused on the design and optimization of content replicas mechanisms to minimize server costs. The optimization of replicas mechanisms has been typically performed either considering very crude system performance indicators or analyzing asymptotic behavior. In this work, instead, we propose an analytical model that complements previous works providing fairly accurate predictions of system performance (i.e., blocking probability). Our model turns out to be a highly scalable, flexible, and extensible tool that may be helpful both for designers and developers to efficiently predict the effect of system design choices in large scale STB-VoD system