P2P Video Streaming Systems Research Articles

A path selection approach with genetic algorithm for P2P video streaming systems

In peer-to-peer (P2P) video streaming applications, the Quality of Experience (QoE) obtained by peers may vary according to the level of network congestion on the path between the peer and its parents. In this paper, we have proposed a parent selection approach for hybrid push-pull based video streaming systems, taking physical paths into account. In this approach, we proactively measured the disjunction of paths between peers and partners and chose the set of parents among partners having maximum disjoint paths by using a genetic algorithm at the beginning of the streaming session. The peers continue the paths of parent set to keep disjoint during streaming. The proposed system was tested on NS3 and the obtained results show that the proposed approach provides an increase up to 10 % in continuity index compared to hybrid push-pull based system which does not consider underlying network infrastructure. Furthermore, higher performance in terms of other parameters related to QoE such as Peak Signal to Noise Ratio (PSNR), reset count, and network related parameters such as video propagation success among peers and re-selection rates of new parents is observed with the proposed approach.

Adaptive content-and-deadline aware chunk scheduling in mesh-based P2P video streaming

In mesh-based Peer-to-Peer (P2P) live video streaming systems packet scheduling is an important factor in overall video playback quality. In mesh based P2P video streaming systems, each video sequence is divided into chunks, which are then distributed by multiple suppliers to the receivers. The suppliers need to be coordinated by the receiver through specifying a transmission schedule for each of them. Many previous studies on scheduling of P2P streaming tend to mainly focus on networking issues which strongly depend on a particular P2P architecture such as tree or mesh. These algorithms suffer from some design issues: 1) they are too complex to deploy, 2) they do not take video characteristics into account and 3) they do not have sender-side transmission policy. To address all three of these problems, we propose a new chunk scheduling scheme which consists of two parts: i) receiver-side scheduler and ii) sender-side transmission order scheme. The proposed receiver-side scheduler considers the contribution level of each video frame as well as the frame’s urgency in order to define a priority for each video frame. It attempts to request frames with highest priority from peers which can deliver them in a shorter time. We also design a new chunk transmission order scheme that decides which requested chunk will be sent out first based on its importance to the requesting neighbor. Our simulation results show that the proposed scheduling scheme improves the overall quality of the perceived video in mesh-based P2P video streaming architectures substantially.

A learning-based resource allocation approach for P2P streaming systems

Video-on-Demand (VoD) systems are rising as a new dominant way to distribute video content over IP networks, although VoD services provisioning comes with its own scalability challenges for service providers. P2P video streaming systems are among the most scalable ways to deliver VoD services. While there has been much research work in the broad area of P2P communications, very limited research has been directed to the issue of resource allocation in P2P streaming systems where the real-time aspect adds another dimension to the problem. Most research work on P2P resource allocation tends to approach the problem with static strategies that do not dynamically adjust to changing content demand (popularity) trends, and fail to outperform over a long time period. In this article we specifically focus on the problem of maximizing the P2P streaming system capacity by effectively alternating between different resource allocation strategies. Switching between different resource allocation strategies is guided by a run-time statistical analysis of performance against a predicted content popularity pattern. A key contribution of this article resides in effectively combining different, and potentially conflicting, performance objectives when deciding which resource allocation strategy to use for the current time period. With our P2P resource allocation framework, a VoD service operator can combine any number of resource allocation strategies and formulate different performance objectives (decision criteria) that meet its requirements.

A belief‐desire‐intention agent architecture for partner selection in peer‐to‐peer live video streaming applications

AbstractIn peer‐to‐peer (P2P) video streaming systems, one of the most challenging parts is to schedule video data dissemination, that is, each peer should carefully select the partner(s) it receives video from and the partner(s) it sends data to. We believe that an agent‐based partner selection approach may improve the quality of streaming by taking both autonomy and dynamic plan selection into account in a goal‐oriented manner. In this study, a Belief‐Desire‐Intention agent architecture for partner selection in P2P video streaming systems is introduced. The major concern of our study is to exhibit how to select the best partner during video streaming session whilst maximizing the quality of video and minimizing delay and hop count. The effects and comparative results of executing proposed agent behaviours are evaluated in the study. The proposed autonomous agent‐based approach also provides an infrastructure in which the best plan for the achievement of optimum streaming goal can be dynamically determined and executed at runtime. Experimental results of the implementation have revealed to us that both of the partner selection methods (with or without agents) manage to increase the video quality. However, the agent‐based approach performs better in terms of received bitrate, delay and hop count during streaming.

Software agents for peer‐to‐peer video streaming

Peer-to-peer (P2P) video streaming systems enable video data exchange between peers by reducing the overload of the servers while utilising network resources. Multi-agent systems (MASs), including many autonomous and intelligent software agents working on behalf of video peers, may also provide a feasible infrastructure for the implementation of P2P video streaming systems. Within this context, research on the use of software agents in video streaming systems has recently emerged. In this study, the authors discuss the development of an agent-based P2P video streaming system. Software engineering of the MAS with covering various aspects such as agent internals and interactions in the system is described. Performance evaluation of the proposed agent-based P2P system comparing with the popular in-use streaming application is also reported. Results show that a well-defined behaviour of a parent selection software agent can improve the continuity index in P2P video streaming systems. Therefore the users in the system can watch video in a better quality and lower end-to-end delay comparing with the currently used video streaming applications. They also examine that peer welcoming (traffic localisation) behaviour of the agents decreases the internal Internet service provider traffic significantly.

MATIN: A Random Network Coding Based Framework for High Quality Peer-to-Peer Live Video Streaming

In recent years, Random Network Coding (RNC) has emerged as a promising solution for efficient Peer-to-Peer (P2P) video multicasting over the Internet. This probably refers to this fact that RNC noticeably increases the error resiliency and throughput of the network. However, high transmission overhead arising from sending large coefficients vector as header has been the most important challenge of the RNC. Moreover, due to employing the Gauss-Jordan elimination method, considerable computational complexity can be imposed on peers in decoding the encoded blocks and checking linear dependency among the coefficients vectors. In order to address these challenges, this study introduces MATIN which is a random network coding based framework for efficient P2P video streaming. The MATIN includes a novel coefficients matrix generation method so that there is no linear dependency in the generated coefficients matrix. Using the proposed framework, each peer encapsulates one instead of n coefficients entries into the generated encoded packet which results in very low transmission overhead. It is also possible to obtain the inverted coefficients matrix using a bit number of simple arithmetic operations. In this regard, peers sustain very low computational complexities. As a result, the MATIN permits random network coding to be more efficient in P2P video streaming systems. The results obtained from simulation using OMNET++ show that it substantially outperforms the RNC which uses the Gauss-Jordan elimination method by providing better video quality on peers in terms of the four important performance metrics including video distortion, dependency distortion, End-to-End delay and Initial Startup delay.

Multiple description coded video streaming in peer-to-peer networks

It is known that in a peer-to-peer (P2P) network a peer node serves as both a receiver and a supplier, which enables uploading bandwidth of peer nodes to be utilized efficiently while relieving burden of the server node. This solves the scalability problem typically encountered in the traditional client–server model. However, frequent peer churn and varying bandwidth of peer nodes in P2P networks pose significant challenges for video streaming. These challenges can be addressed from both the P2P system design and the advanced video coding perspectives. In this paper, we first present a survey on the existing P2P video streaming systems that leverage the multiple description coding (MD coding or MDC) techniques, featured in providing strong error resilience for video delivery and supporting heterogeneity for peer nodes. Compared with layered coded video streaming, MD coded video streaming presents stronger robustness without requiring special provisions in P2P system design at a modest cost of compression efficiency, which is desirable in dynamic and error-prone P2P networks. In the MD coded video streaming, packet scheduling is critical to performance of mesh-based P2P systems. A new packet scheduling framework is formulated for receiver-driven MD coded video streaming, where a receiver collects peer nodes' information and generates a transmission schedule for MDC packets. In the proposed framework, a rate-distortion optimized packet selection scheme is developed to minimize the expected distortion subject to limited downloading bandwidth. Accordingly a rate-distortion based prioritized peer selection scheme is employed to choose an appropriate peer node for each of the selected packets. Simulation results validate the effectiveness of the proposed scheduling scheme and the advantage of MDC over layered coding in a network with frequent peer churn.

Quality of data delivery in peer-to-peer video streaming

QoS in a P2P video streaming system is evaluated in three stages: content generation, data delivery and video playback. We use jitter-free probability as the main performance metric to study Quality of Data delivery (QoD). A new model that incorporates both bandwidth and data availability of P2P network is proposed. Our model relies on a sharing factor that models data availability among all peers. We simulate on a minimalistic network to demonstrate how to apply the analytical model to design a P2P video streaming system with a very low jitter rate. Our simulation experimental results reveal that the lower bound on jitter-free probability is indeed effective to reflect the QoD of the entire system. Our model captures the impact of many design choices, including upload bandwidth limit, peer selection strategies, and video stream chunking schemes.

An effective mesh-pull-based P2P video streaming system using Fountain codes with variable symbol sizes

In this paper, we propose an effective mesh-pull-based video streaming system over P2P networks using Fountain codes with variable symbol sizes for video-on-demand services. The goal of the proposed system is to provide a stable video streaming service of high quality with minimum computational complexity and a short initial latency over P2P networks. Basically, Fountain codes are adopted in the proposed system to simplify the handshaking procedure, which causes a large initial latency, and to support a robust video streaming service despite packet losses. The proposed Fountain encoding mechanism works by using feedback information to reduce unnecessary encoded symbol generation. In addition, the Fountain code symbol size is continuously adjusted to minimize additional computational overhead required for Fountain encoding/decoding. The proposed system is fully implemented in software and examined over an Internet environment.

Experimental comparison of a tree-based and a mesh-based peer-to-peer video streaming system

We analyse two commercial peer-to-peer (P2P) video streaming systems via active measurements: a tree-based overlay multicast and a mesh-based overlay. Our controlled IP test bed allows us to reproduce near-identical network conditions for both systems and test them under varying network conditions and peer behaviour. We report on how these systems adapt to heterogeneous networks and peer behaviour. Our results include quality-of-service information in terms of the fraction of the total video stream received by each peer for live playback. We also report the server bandwidth versus P2P bandwidth consumed by the system under different conditions. The dynamic behaviour of the P2P video streaming systems is captured via measuring the size of interactions (bytes downloaded) among peers. Finally, we report the correlation between the underlying traffic-shaped bandwidth assigned to a peer and the actual amount of P2P data uploaded by the peer. Our analysis shows that the mesh-based overlay mimics the underlying IP network more closely than the tree-based overlay, indicating that the former relays data volumes more proportionally to the upload capacities. On the other hand, the tree-based system is more efficient in bandwidth usage.

High-Quality P2P Video Streaming System Considering the Cooperation of Constitution Information and Delivery Status

Recently, video streaming services using P2P (Peer-to-Peer) have attracted attention to solve the problem of load concentration on servers and to reduce large latency. Many P2P streaming systems, like Coolstreaming, however, take a complicated approach to control playback timing severely. This leads to less churn resiliency and less adaptability to fluctuation of network traffic. Therefore, we focus on a simple and robust approach to realize “pseudo” streaming with high quality, which is based on BitTorrent. In the existing methods with the simple approach, peers download pieces just closer to playback timing to decrease the playback discontinuity. However, these methods do not consider the constitution of video structure in sophisticated manner. P2P streaming system must consider several important metrics for high-quality and fair distribution. Therefore, in this paper, we propose a new P2P video streaming system considering the cooperation of three important metrics; video structure, playback timing, and piece dispersion on network. In this system, users vary three piece selections to suit the delivery status. Specifically, users preferentially download pieces which affect the video quality, which are closer to playback timing, and which improve the delivery efficiency. Moreover, we show the effectiveness of the proposed method by computer simulation.

Hybrid Fault Tolerant Peer to Peer Video Streaming Architecture

In this paper, we propose a fault tolerant hybrid p2p-CDN video streaming arhitecture to overcome the problems caused by peer behavior in peer-to-peer (P2P) video streaming systems. Although there are several studies modeling and analytically investigating peer behaviors in P2P video streaming systems, they do not come up with a solution to guarantee the required Quality of the Services (QoS). Therefore, in this study a hybrid geographical location-time and interest based clustering algorithm is proposed to improve the success ratio and reduce the delivery time of required content. A Hybrid Fault Tolerant Video Streaming System (HFTS) over P2P networks conforming the required QoS and Fault Tolerance is also offered. The simulations indicate that the required QoS can be achieved in streaming video applications using the proposed hybrid approach.

A Flexible Multiple Description Coding Framework for Adaptive Peer-to-Peer Video Streaming

Efficient peer-to-peer (P2P) video streaming is a challenging task due to time-varying nature of both the number of available peers and network/channel conditions. This paper proposes a novel adaptive P2P video streaming system, which features: (i) a new flexible multiple-description coding (F-MDC) framework, such that the number of base and enhancement descriptions, and the rate and redundancy level of each description can be adapted on the fly (by only post-processing of the encoded bitstream), and (ii) a new adaptive TCP-friendly rate-controlled (TFRC), on-demand, many-to-one P2P video streaming solution based on the proposed F-MDC framework. We extend the highly scalable video coder , to MDC within the proposed F-MDC framework. Optimization of the design parameters of the proposed F-MDC method is discussed within the context of the proposed adaptive P2P streaming solution, where the number and quality of available streaming peers/paths are a priori unknown and vary in time. Experimental results, by means of NS-2 network simulation of a P2P video streaming system, show that adaptation of the number, type of descriptions and the rate and redundancy level of each description according to network conditions yields significantly superior performance when compared to other scalable MDC schemes using a fixed number of descriptions/layers with fixed rate and redundancy level.