P2P Video Streaming Research Articles

A Hybrid Approach for WebRTC Video Streaming on Resource-Constrained Devices

This paper introduces thorough comparative and interoperability analyses involving a browser-based P2P video streaming approach utilizing WebRTC (web real-time communication), along with WebRTC hybrid solutions developed using the React Native framework (for mobile) and the electron framework (for desktop and Raspberry Pi). The assessment is carried out based on various metrics, including CPU (central processing unit) load, RAM (random access memory) utilization, and network data consumption. The obtained findings highlight the potential of integrating WebRTC P2P video streaming into hybrid applications as a promising alternative for real-time video streaming applications in embedded systems; given that, compared to the current mainstreams, e.g., Chrome or Firefox, the proposed approach has superiority performance in terms of CPU load, RAM usage, and network occupancy. The results also demonstrated that interoperability is ensured between the two types of applications (web-based and hybrid-based one).

Semi-Structured BitTorrent Protocol with Application to Efficient P2P Video Streaming

Semi-Structured BitTorrent Protocol with Application to Efficient P2P Video Streaming

Controlling P2P-CDN Live Streaming Services at SDN-Enabled Multi-Access Edge Datacenters

Recognizing the shortcomings of current hybrid peer-to-peer (P2P) content-distribution network (CDN) video solutions and the potential of emerging multi-access edge datacenters, we propose a novel P2P-CDN service model that is hosted at software defined networks (SDN)-enabled multi-access edge datacenters operated by network service providers (NSP). An important feature of the proposed service architecture is that both CDN access by peers and P2P video streaming between peers within edge access networks are fully controlled by cooperation of the video content provider (VCP) and NSP to optimize video service key performance indicators (KPI). The proposed fully controlled P2P-CDN architecture with P2P group formation and chunk scheduling managed at edge datacenters reduces the load on CDN servers while overcoming quality of experience (QoE) fluctuations per flow and unfairness between multiple heterogeneous video-resolution clients over reserved access network slices. Other advantages of this service include: i) better video quality and lower delay for clients; ii) better use of edge network resources; iii) avoiding illegal, unauthorized P2P content sharing. To the best of our knowledge, there are no solutions in the literature that address P2P-CDN services managed at NSP-edge datacenters combining P2P-assisted CDN, SDN-assisted edge computing, and premium service over reserved slices. Experimental results show that the proposed P2P-CDN service deployed at SDN-enabled edge datacenters provides excellent service KPI compared to other state-of-the-art solutions.

Game theory approach to peer-to-peer video streaming: a comprehensive survey

Recent reports and forecasts indicate video is the most important part of the internet traffic. This traffic is the result of increasing video applications, also the high expectations of today users. In fact, streaming HD videos with minimum initial buffering time and interruption forms the QoE backbone. Therefore, resource provisioning for this demands is very challenging and the scalability of these systems depends on spending a high cost on preparation new resources or taking the advantage of users' abilities in the form of a peer-to-peer (P2P) system. Although P2P architecture can significantly improve scalability, it has severe management complexity challenges. The dynamic nature and the autonomy of peers are the prominent reasons for this issue. Because of the strategic context in P2P video streaming and due to the existence of conflicting actions for participant entities in such systems, using game theory has been very interesting as a mathematical tool for modelling and analysing in recent related investigations. Due to the multitude of these methods, the lack of a comprehensive review is intensively palpable. This paper seeks to fill this research gap especially with focus on applying non-cooperative games to P2P video streaming resource allocation.

Game theory approach to peer-to-peer video streaming: a comprehensive survey

Recent reports and forecasts indicate video is the most important part of the internet traffic. This traffic is the result of increasing video applications, also the high expectations of today users. In fact, streaming HD videos with minimum initial buffering time and interruption forms the QoE backbone. Therefore, resource provisioning for this demands is very challenging and the scalability of these systems depends on spending a high cost on preparation new resources or taking the advantage of users' abilities in the form of a peer-to-peer (P2P) system. Although P2P architecture can significantly improve scalability, it has severe management complexity challenges. The dynamic nature and the autonomy of peers are the prominent reasons for this issue. Because of the strategic context in P2P video streaming and due to the existence of conflicting actions for participant entities in such systems, using game theory has been very interesting as a mathematical tool for modelling and analysing in recent related investigations. Due to the multitude of these methods, the lack of a comprehensive review is intensively palpable. This paper seeks to fill this research gap especially with focus on applying non-cooperative games to P2P video streaming resource allocation.

Multicast-Based Optimized Peer Control for Efficient P2P Video Streaming in TDM-PONs

An important issue in network traffic management for Internet service providers (ISPs) is how to efficiently handle a large amount of data traffic generated by peer-to-peer (P2P) applications. This paper discusses the efficiency of P2P video streaming in time-division-multiplexed (TDM)-passive optical networks (PONs). We summarize the technical requirements that are required to efficiently serve P2P video streaming in the broadcast-and-select architecture of the TDM-PON. The proposed localized multicast-based P2P (LM-P2P) mechanism controls generation of P2P sessions adaptively based on information about the peer location and multicast efficiency in the optical line termination (OLT) domain. The centralized control node of LM-P2P selects a multicast seeder and recommends it to later clients as a seeder so that the amount of P2P streaming traffic can be minimized both in the inter-OLT domain and in the intra-OLT domain. The efficiency of LM-P2P in allocation of network resources is achieved by optimal migration of the property of P2P streaming on the unique architectural feature of TDM-PON. The efficiencies of typical P2P localization and P2P caching are compared with LM-P2P, and the systematic issues in localization of P2P sessions and management of multicast sessions are also discussed. The efficiencies of the proposed mechanism are validated by numerical analysis and practical test results.

An efficient hybrid push-pull methodology for peer-to-peer video live streaming system on mobile broadcasting social media

With the rapid growth of wireless communication technology, the availability of highly flexible and video-friendly mobile terminal platforms (such as smartphones and tablets), the emergence of major video content providers (like YouTube, Ustream, and PPTV, which provide a large catalog of attractive contents), Peer-to-Peer (P2P) live video streaming over the wireless and Internet is becoming more and more attractive to users. One of the main challenges is to provide a good quality of service though the dynamic behavior of the network. Traditionally, tree-based model uses a push method, that broadcaster transfers data to other users. This model has low start-up delay. However, there are two main problems in this method: if the bandwidth of an internal node is low, children nodes may lose data and when an internal node failure, other nodes can't receive data until completing the recovery of the tree. On the other hand, mesh-based model uses a pull method, has low bandwidth of a neighbor node by pulling necessary data from a number of neighbor nodes. However, mesh-based model requires large buffers to support pull data from neighbor peers and there is an adjustment between minimum delay by sending pull request and overhead of whole system. So, both models have their own strengths and weaknesses. This paper proposes a new hybrid push-pull live P2P video streaming protocol called MobileCast that combines the benefits of pull and push mechanisms for live video delivery. We present new topology for P2P network with more stable and provide better video streaming quality. Our main goal is to minimize the network end-to-end delay, startup time, overhead, packet loss compared to the pure mesh networks, pure tree networks and provide a good quality of service though the dynamic behavior of the network.

Throughput analysis of P2P video streaming on single-hop wireless networks

Video streaming services have been developed using different approaches. Peer-to-peer (P2P) streaming is a competitive technique in the distribution of video contents, thanks to its collaborative and sharing features. Nowadays, several applications distribute television contents over a P2P platform, broadcasting plenty of channels to an increasing audience. The performance of such applications over wireless networks is still an open issue, considering the highly variable environment, and the scarce resources. Most of these applications are developed to work properly over wired networks. This paper presents a performance evaluation model of the traffic behavior through an analytical representation, resembling the network interactions during a video transmission. The model, useful in determining the throughput parameter, does accurately evaluate the network performance. The analytical model is validated through the emulation mode in NS-3 simulator.

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.

A distributed utility‐based scheduling for peer‐to‐peer video streaming over wireless networks

AbstractInteractive multimedia applications such as peer‐to‐peer (P2P) video services over the Internet have gained increasing popularity during the past few years. However, the adopted Internet‐based P2P overlay network architecture hides the underlying network topology, assuming that channel quality is always in perfect condition. Because of the time‐varying nature of wireless channels, this hardly meets the user‐perceived video quality requirement when used in wireless environments. Considering the tightly coupled relationship between P2P overlay networks and the underlying networks, we propose a distributed utility‐based scheduling algorithm on the basis of a quality‐driven cross‐layer design framework to jointly optimize the parameters of different network layers to achieve highly improved video quality for P2P video streaming services in wireless networks. In this paper, the quality‐driven P2P scheduling algorithm is formulated into a distributed utility‐based distortion‐delay optimization problem, where the expected video distortion is minimized under the constraint of a given packet playback deadline to select the optimal combination of system parameters residing in different network layers. Specifically, encoding behaviors, network congestion, Automatic Repeat Request/Query (ARQ), and modulation and coding are jointly considered. Then, we provide the algorithmic solution to the formulated problem. The distributed optimization running on each peer node adopted in the proposed scheduling algorithm greatly reduces the computational intensity. Extensive experimental results also demonstrate 4–14 dB quality enhancement in terms of peak signal‐to‐noise ratio by using the proposed scheduling algorithm. Copyright © 2015 John Wiley & Sons, Ltd.

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.

P2P Video Streaming Strategies based on Scalable Video Coding

Video streaming over the Internet has gained significant popularity during the last years, and the academy and industry have realized a great research effort in this direction. In this scenario, scalable video coding (SVC) has emerged as an important video standard to provide more functionality to video transmission and storage applications. This paper proposes and evaluates two strategies based on scalable video coding for P2P video streaming services. In the first strategy, SVC is used to offer differentiated quality video to peers with heterogeneous capacities. The second strategy uses SVC to reach a homogeneous video quality between different videos from different sources. The obtained results show that our proposed strategies enable a system to improve its performance and introduce benefits such as differentiated quality of video for clients with heterogeneous capacities and variable network conditions.

Review on Cloud Computing Application in P2P Video Streaming

Abstract Cloud computing has been introduced as a solution to several problems of the traditional web-based e-learning system, such as a limited storage, a high infrastructure maintenance costs and a low interoperability among the component of web-based e-learning system. However, the cloud computing system performance may deteriorate with increasing number of users and become worse when many users access the video streaming from the cloud system. This is due to the centralized architecture of the cloud computing that can generate network traffic congestion and bottleneck in the cloud servers. Peer-to-peer (P2P) architecture has been proposed to overcome this problem. Using P2P, all nodes in the cloud system can act as servers as well as clients at the same time for reducing the congestion and bottleneck of the system. Currently, there are few reviews on P2P video streaming although intensive studies have been done on the development of the system. With this condition, identifying and understanding the development of P2P video streaming will be expensive, time consuming and physically exhausting. The objective of this paper is to review the latest development of P2P video streaming based on cloud computing. A narrative review method has been used as the methodology for investigating the P2P video streaming’ articles from 2009 to 2014. The outcomes of this research shows that 90% of cloud based e-learning integrate with P2P when it's involving streaming video.

Optimal backup parent pools for resilient multicast trees on peer-to-peer networks

Due to churn as well as node and link failures in peer-to-peer (P2P) networks, providing resilient multicast is a challenging issue, particularly for overlay trees. In this work, we first study analytical properties of the backup parent pool that aims at improving the resilience of overlay multicast trees in P2P video streaming. We then present a novel greedy degree-constrained multicast tree construction algorithm that addresses the tradeoffs between maximizing resiliency, maximizing bandwidth utilization, and minimizing delay. The choice of essential design parameters is studied together with seamlessness of the streaming under a variety of fault scenarios. Simulation results indicate that the overhead introduced by the mechanism is negligible if there is sufficient bandwidth in the system. Both analytic and simulation results indicate that the proposed approach improves resiliency, bandwidth utilization, and delay. Comparisons with an algorithm from the literature are carried out and it is observed that the proposed method is superior under a wide range of conditions.

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 method for reliable P2P video streaming using variable bitrate video formats

A method for reliable P2P video streaming using variable bitrate video formats

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.

Layered P2P video streaming using asymmetric P2P topology and membership management

Peer-to-peer (P2P) video streaming applications are widely popular, e.g. PPstream and PPlive, because of higher transmission speed and data availability. A fact of P2P streaming is that different peers have different (asymmetric) capabilities for resource sharing, and thus, some asymmetric P2P (A-P2P) topology and membership management schemes should be adopted among P2P nodes having heterogeneous computing and communicating capabilities. Our research focuses on designing a novel A-P2P streaming architecture with a dedicated codec scheme that applies multiple description features into the scalable extension of H.264/AVC, which is adaptive and error-robust enough to tackle challenges in the A-P2P network environment. In the streaming architecture, our proposed device-aware P2P topology management is responsible for constructing a hierarchical membership-tree based on the capacity of upstream bandwidth and round-trip time. In addition, the buffer-aware scheduling scheme is able to determine whether the peer needs to reconnect to a proper source provider or not, based on the buffer status. In our experiments, corresponding performances, e.g. average peer-join time and average peak signal-to-noise ratio, were measured and demonstrated.

Performance analysis of packet loss recovery policies in P2P video streaming

Packet loss recovery is an important part of P2P video streaming networks due to inevitable packet loss in today's internet and interdependency of data units in compressed video streams. In addition, the architecture of P2P streaming networks, in which the data delivered to the receivers through chain of peers, can intensify the impact of the internet packet loss on the quality of perceived video at the receivers. FEC and ARQ are the two most important techniques that can be used to overcome the side effect of the internet packet loss in P2P video streaming networks. Based on these two techniques, different packet loss recovery strategies can be applied in different overlay hops of a given P2P streaming network. In this paper, we have modelled and analysed the performance and efficiency of variant packet loss recovery policies can be used in P2P streaming networks. Our analysis show that a hybrid packet loss recovery scheme in which the most important data units are protected by packet level FEC and the remaining lost ones are recovered through retransmission i.e., ARQ is the most efficient strategy that improves the performance of P2P video streaming networks.