P2P Streaming Systems Research Articles

Topology Optimization in Hybrid Tree/Mesh-based Peer-to-Peer Streaming System

Peer-to-Peer (P2P) video streaming is the fastest growing application of the Internet. One of the main challenge is to provide a high quality of service through the dynamic behavior of the network because a peer may join or leave anytime. Currently, P2P streaming network exist two types of users: streaming users - who use mobile devices with 3G/4G connection expect to watch the live video immediately and storage users - who use PC with wired Internet will download and then watch the video later. We realized that the streaming users may stop watching live video after a while if they find the video is out of their interest. Users leaving causes dynamic and affect the data delivery. On the other hand, the storage users that are downloading the video do not have the concern of interest and playback quality, until they start to watch the video. Hence, the storage users are relatively more stable than streaming users. This paper, we investigate the strategies on the topology construction and maintenance of P2P streaming systems with storage users are closer to the broadcaster than streaming users. And also we apply our idea on hybrid push-pull protocol that combines the benefits of pull and push mechanisms for live video delivery to provide better video streaming quality

REAL-TIME INTERACTIVE MECHANISM FOR LIVE STREAMING ON PEER-TO-PEER NETWORKS

Quality of live video streaming technology is based on quality of Experiences parameters (QoE). Approaching the peer-to-peer (P2P) or peer-assisted networks as a sympathetic solution is highly required, especially in light of its authentic scalability and its extremely low initial cost requirements. However, the design of robust, efficient, and performing P2P streaming systems remains a high challenge when real-time constraints are part of the quality of service (QoS), as in TV distribution or conferencing applications. One of the P2P main issues that affect the quality of streaming is the neighbor selection methodology. The proposed work presents an effective mesh-based neighbor selection approaches for video streaming – Uniform Peer Distribution Algorithm (UPDA) – based on QoS and QoE Parameters. UPDA shortens the latency to be ranging from 10 ms to 50 ms servicing up to 4000 online peers under failure / recovery tests. Simulation results demonstrate that the proposed UPDA achieves good performance in End-to End delay with a percentage of 10.4 % and packet delay variation about 2% compared to random neighbor selection method.

MOPSO-based Data Scheduling Scheme for P2P Streaming Systems

MOPSO-based Data Scheduling Scheme for P2P Streaming Systems

Formal verification of a peer-to-peer streaming protocol

Peer (P2P) networks have emerged as an efficient and affordable means of transmitting videos to numerous end-users via the Internet. The dynamic and heterogeneous nature of P2P streaming systems (P2PSS) makes testing, analyzing and verification a cumbersome task. However, formal methods offer efficient approaches to rigorously analyze and verify P2PSS. This paper demonstrates the use of formal verification techniques for analyzing the behavioral properties of P2PSS. We use temporal logics to analyze whether all the possible behaviors within the P2P streaming systems conform to the defined specifications. Specifically, we apply model checking to check the consistency, completeness and certainty of the model if the temporal properties of the proposed system satisfies the required specifications. Furthermore, the P2PSS framework was modeled and verified using Simulink Design Verifier (SDV) in MATLAB simulation tool. The simulations results showed 100% validation for all frames and 50% validation for I-frames prioritisation. Further, the probability of a peer capable of forwarding frames while receiving is at most 0.5.

Dynamical Analysis of an Internet-Based Video System

The dissemination of video applications across the Internet still remains the driving force for Internet traffic growth. Generally, video streaming systems are characterized with irregular transmitting pattern and fluctuation which usually leads to transmission delay and frame loss. Furthermore, the democratic platform created by peer-to-peer (P2P) network for video streaming suggests complex dynamical behaviour with difficult predictable performance. The existence of flash crowd and peer churn situations in P2P streaming systems obtained from random arrival and departure of peers exhibits chaotic attributes. In this paper, a P2P streaming system(UStream) was modelled using a system of first order differential equations. The dynamics of UStream were analysed using equilibrium points and eigenvalues structure. Instability region was tracked through numerical investigation. The numerical simulation conducted using the Mathematica package software showed that UStream exhibits spiral fixed point and strange attractors with certain initial conditions which confirms experimental measurement and observations. Also, the system responds exponentially with time and reflects instability pattern for the first 20 seconds and 500 seconds when investigated with client-to-server(CS)and P2P network models respectively.

Toward a full peer to peer MPEG-DASH compliant streaming system

MPEG-DASH standard has been proposed to standardize the proprietary solutions proposed to stream multi-qualities encoded video/audio over HTTP. Although MPEG-DASH relies on the client/server communication model, in this paper we show that it could be also used in a full P2P streaming system after making the necessary changes in the MPEG-DASH standard as well as in the main modules of the P2P streaming system. The main changes are made in the Media Presentation Description (MPD) file to support the P2P network bootstrapping mechanism (peers selection algorithm) as well as in the pieces selection algorithm to make the peer quality adaptation enabled as imposed by the MPEG-DASH. We choose the famous BitTorrent protocol as an example to implement the required changes. Extensive simulations have been conducted under the OMNeT + + simulator. The obtained results in terms of the average missed segments and the average waiting time on playback are reasonable with regards to 1) the BitTorrent known issue in the streaming context, to 2) the hard conditions we considered in our simulation set-up and 3) compared to some representative related works. This results show that MPEG-DASH could be easily supported by P2P streaming systems.

The Streaming Capacity of Sparsely Connected P2P Systems With Distributed Control

Peer-to-Peer (P2P) streaming technologies can take advantage of the upload capacity of clients, and hence can scale to large content distribution networks with lower cost. A fundamental question for P2P streaming systems is the maximum streaming rate that all users can sustain. Prior works have studied the optimal streaming rate for a complete network, where every peer is assumed to communicate with all other peers. This is however an impractical assumption in real systems. In this paper, we are interested in the achievable streaming rate when each peer can only connect to a small number of neighbors. We show that even with a random peer selection algorithm and uniform rate allocation, as long as each peer maintains Ω(logN) downstream neighbors, where N is the total number of peers in the system, the system can asymptotically achieve a streaming rate that is close to the optimal streaming rate of a complete network.We then extend our analysis to multi-channel P2P networks, and we study the scenario where “helpers” from channels with excessive upload capacity can help peers in channels with insufficient upload capacity. We show that by letting each peer select Ω(logN) neighbors randomly from either the peers in the same channel or from the helpers, we can achieve a close-to-optimal streaming capacity region. Simulation results are provided to verify our analysis.

Dynamic Strategy Selection based on Evidence Theory. Application on a P2P-VoD system

Peer-to-Peer Video-on-Demand (VoD) systems are rising as a new dominant way to distribute video content over IP networks. While many works addressed the broad area of P2P communications, few work has been focused onto the resource allocation in P2P streaming systems, where the real-time constraint adds another dimension to the problem. Most work on P2P resource allocation solve the problem with static rules strategies are not robust when they are facing to the content demand (popularity) trends. In this paper, we use a dynamic approach, which automatically selects the best strategy on a given time period. With the proposed P2P resource allocation method, a VoD service provider can combine any number of resource allocation strategies and formulate different performance objectives that meet its requirements. As part of our effort to develop algorithms that can be effectively deployed by broadband operators, we developed a full-scale emulator for P2P streaming that can support up to 10,000 peers. The P2P streaming emulator includes a VoD request generators, along with a SuperNode (with backend DataBase) that tracks and allocates network resources. In this paper the goal is to use a low complexity learning approach to enhance the performance of a P2P-VoD system based on evidence theory. The proposed approach is compared to both static and dynamic solutions. The obtained results show that the proposed approach allows to reduce the complexity of selecting resource allocation strategies, while maintaining a low rejection rate.

Incentive Mechanism Design for Heterogeneous Peer-to-Peer Networks: A Stackelberg Game Approach

With high scalability, high video streaming quality, and low bandwidth requirement, peer-to-peer (P2P) systems have become a popular way to exchange files and deliver multimedia content over the internet. However, current P2P systems are suffering from “free-riding” due to the peers’ selfish nature. In this paper, we propose a credit-based incentive mechanism to encourage peers to cooperate with each other in a heterogeneous network consisting of wired and wireless peers. The proposed mechanism can provide differentiated service to peers with different credits through biased resource allocation. A Stackelberg game is formulated to obtain the optimal pricing and purchasing strategies, which can jointly maximize the revenue of the uploader and the utilities of the downloaders. In particular, peers’ heterogeneity and selfish nature are taken into consideration when designing the utility functions for theStackelberg game. It is shown that the proposed resource allocation scheme is effective in providing service differentiation for peers and stimulating them to make contribution to the P2P streaming system.

Fighting pollution attacks in P2P streaming

In recent years, the demand for multimedia streaming over the Internet is soaring. Due to the lack of a centralized point of administration, Peer-to-Peer (P2P) streaming systems are vulnerable to pollution attacks, in which video segments might be altered by any peer before being shared. Among existing proposals, reputation-based defense mechanisms are the most effective and practical solutions. We performed a measurement study on the effectiveness of this class of solutions. We implemented a framework that allows us to simulate different variations of the reputation rating systems, from the centralized global approaches to the decentralized local approaches, under different parameter settings and pollution models. One key finding is that a centralized reputation system is only effective in static network and in defending against light pollution attacks. In general, a fully distributed reputation system is more suitable for the “real-time” P2P streaming system, since it is better in handling network dynamics and fast in detecting the polluters. Based on this key finding, we propose DRank, a fully distributed rank-based reputation system. Experimental results show that this technique is more flexible and robust in fighting pollution attacks.

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.

Transcoding in Two-class P2P Streaming Systems

Transcoding in Two-class P2P Streaming Systems

An IP-TV P2P streaming system that improves the viewing quality and confines the startup delay of regular audience

This paper investigates how a p2p television platform can take advantage of the presence of frequent channel viewers to grant them a more satisfying service than to less regular spectators, and how such privileged users can also be protected when unfavorable operating conditions manifest within the overlay. The explored idea is to learn beforehand about the users’ interests, monitoring their behavior in the recent past, in order to cluster them in groups that display different habits; then, the video chunk scheduling algorithm of the overlay is altered, with the aim of serving frequent spectators in a privileged manner, providing them with a better viewing experience and a faster access to the selected channel without overly penalizing less habitual customers. An analytical model is developed, to capture the difference in average startup delay that the proposed modifications introduce; several additional performance metrics are numerically determined, in order to thoroughly size up the performance of both groups of viewers. The obtained results show that a clear service differentiation is attained and demonstrate that, if bandwidth resources become scarce, frequent viewers are protected and still enjoy a broadcasting service of superior quality.

Central-Evaluation Neighbors Acquiring Method for P2P Streaming System

To solve the high startup delay and playback delay in P2P streaming system which are caused by peers randomly join or leave the network, we proposed a neighbors acquiring method. This paper presents the details of our neighbors acquiring method. We use tracker server to grasp the information of all nodes in the P2P network. Based on these information, tracker server could pass proper neighbor nodes to the peer node which request neighbors from tracker server through evaluation process. Some conditions are involved in the evaluation process, like node activeness, bandwidth, time nodes existing, buffer-map matching. We estimate our neighbors acquiring method through a P2P streaming system simulation. The simulation results show the P2P streaming system which uses our neighbors acquiring method has lower startup delay and playback delay than the P2P streaming system which uses random neighbors acquiring method.

Priori Knowledge Guided Approach for Optimal Peer Selection in P2P VoD Systems

With the rise of Video-on-Demand (VoD) systems as a preferred way to distribute video content over IP networks, many research works and innovations have focused on improving the scalability of streaming systems by looking at distributed approaches such as peer-to-peer (P2P). One of the most critical aspects in P2P-assisted streaming system is the real-time resource allocation, which drives the performance of the system in terms of capacity utilization and VoD requests rejection rates. In this paper, we specifically focus on the problem of maximizing the P2P streaming system utilization by effectively alternating between different resource allocation strategies. Switching between different resource allocation strategies is guided by a run-time statistical analysis of performances against predicted content popularity pattern. A key contribution of this paper resides in effectively combining different, and potentially conflicting, performance objectives when deciding on which resource allocation strategy to use. Indeed, we use a Bayesian Fusion to select the most appropriate resource allocation strategy to deal with future content demand. With our P2P resource allocation framework, a VoD service operator can combine any number of resource allocation strategies and formulate different performance objectives that meet the requirements of its network and the content consumption behavior of its users.

Bandwidth and Latency Aware Contribution Estimation in P2P Streaming System

In this article, a bandwidth and latency aware contribution estimation (BLACE) mechanism is proposed to enhance the efficiency of content distribution in a mesh peer-to-peer (P2P) streaming system. This is because the mesh P2P streaming system outperforms others in many aspects, but most content distribution mechanisms use only one of upload bandwidth and link latency as a factor, several contribution-aware schemes (CASs) just punish selfish peers, and some CASs only rearrange the content receiving order. Hence, the BLACE proposes a prevention way considering every peer's upload bandwidth, link latency, and the maximum playing delay of a stream at the same time to prioritize the content distribution. Moreover, BLACE is implemented on Coolstreaming with NS2 and experimental results show that BLACE could at the most shorten the receiving time about 15.44%, 13.94%, and 8.26%, and improve the whole performance about 7.05%, 2.81%, and 2.69% at the most, when it compares with the Coolstreaming, the Coolstreaming with bandwidth preference, and the Coolstreaming with latency preference, respectively.

A trust-based pollution attack prevention scheme in peer-to-peer streaming networks

Nowadays, peer-to-peer (P2P) streaming systems have become a popular way to deliver multimedia content over the internet due to their low bandwidth requirement, high video streaming quality, and flexibility. However, P2P streaming systems are vulnerable to various attacks, especially pollution attacks, due to their distributed and dynamically changing infrastructure. In this paper, by exploring the features of various pollution attacks, we propose a trust management system tailored for P2P streaming systems. Both direct trust and indirect trust are taken into consideration when designing the trust management system. A new direct trust model is proposed. A dynamic confidence factor that can dynamically adjust the weight of direct and indirect trust in computing the trust is also proposed and studied. A novel double-threshold trust utilization scheme is given. It is shown that the proposed trust management system is effective in identifying polluters and preventing them from further sharing of polluted data chunks.

HIPPO: An Adaptive, Scalable, Hierarchical P2PLive Streaming System

P2P live streaming is a hot research topic of Internet, but for the defective of system architecture and scheduling policy, P2P streaming applications have poor user experience, such as long start-delay, long play-delay, and low play-continuity and so on. Firstly, based on the analysis of the advantages and disadvantages of previous works, this paper designed and implemented a hierarchical P2P streaming system. The system is composed by three layers: source management servers, region management servers, and peers. The underlying P2P overlay network is organized through Mesh-pull mechanism. We propose a new scheduling strategy to utilize the capacity of the peer. The new adaptive scheduling strategy considers the urgency and scarcity of the data blocks, and selects the appropriate neighbor nodes by monitoring neighbor nodes’ the maximum load. The study of a real-life system provides valuable insights for the future development of P2P live streaming systems.

Hybrid Live P2P Streaming Protocol

A considerable part of the Internet traffic is due to Peer-to-Peer (P2P) protocols. The scalability of the P2P networks encourages implementing many P2P applications such as the file sharing, the media on demand and the live streaming. While many P2P solutions have been proposed the media freshness and the smooth media playback are still a challenging issues in the P2P live streaming. In this paper we propose the Hybrid Live P2P Streaming Protocol (HLPSP) which a live P2P streaming system based on a hybrid overlay (tree and mesh topology). The simulation results show that HLPSP outperforms the enhanced version of the famous CoolStreaming P2P system called DenaCast in terms of the startup delay, the end-to-end delay, the play-back delay and the data loss.

An Efficient Supplier Side Scheduling Algorithm for P2P Live Streaming System

Chunk scheduling is one of the key components in P2P streaming systems. Most of previous research works focus on receiver side’s chunk/peer selection strategies and neglect the service order and available uplink bandwidth allocation problem at supplier side, which will cause the user’s video quality descending under overloaded operating environments. In this paper, we propose the supplier side chunk priority model, formulate the supplier side scheduling problem as a linear programming problem and derive a greedy bandwidth resource allocation algorithm to solve it. The simulations demonstrate the proposed scheme effective comparing to the FCFS (First Come First Service) scheme.