Collaborative resource exchanges for peer-to-peer video streaming over wireless mesh networks

Peer-to-peer collaboration paradigms fundamentally change the passive way wireless stations currently adapt their transmission strategies to match available resources, by enabling them to proactively influence system dynamics through exchange of information and resources. In this paper, we focus on delay-sensitive multimedia transmission among multiple peers over wireless multi-hop enterprise mesh networks. We propose a distributed and efficient framework for resource exchanges that enables peers to collaboratively distribute available wireless resources among themselves based on their quality of service requirements, the underlying channel conditions, and network topology. The resource exchanges are enabled by the scalable coding of the video content and the design of cross-layer optimization strategies, which allow efficient adaptation to varying channel conditions and available resources. We compare our designed low complexity distributed resource exchange algorithms against an optimal centralized resource management scheme and show how their performance varies with the level of collaboration among the peers. We measure system utility in terms of the multimedia quality and show that collaborative approaches achieve ~50% improvement over non-collaborative approaches. Additionally, our distributed algorithms perform within 10% system utility of a centralized optimal resource management scheme. Finally, we observe 2-5 dB improvement in decoded PSNR for each peer due to the deployed cross-layer strategy     

A game theoretic approach to video streaming over peer-to-peer networks

We consider the problem of foresighted multimedia resource reciprocation in peer-to-peer (P2P) networks, which consist of rational peers aiming at maximizing their individual utilities. We introduce an artificial currency (credit) to take into account the characteristics of different parts of the video signal. The resource reciprocation with the proposed credit metric can be formulated as a stochastic game, in which the peers determine their optimal strategies using Markov Decision Process (MDP) framework. The introduced framework can be applied to the general video coding, and in particular, is suitable for the scalable video where various parts of the encoded bit stream have significantly different importance for the video quality.     

Robust mobile video streaming in a peer-to-peer system

In a peer-to-peer (P2P) video streaming system, peers not only consume video, but also route it to other peers in the system, where ordinary peers are assumed to have sufficient downlink speed and media capability. This assumption often fails when the P2P system consists of peers that are heterogeneous in their computing power, hardware, and media capability.In this paper, we address a problem of streaming video to mobile devices, which are less capable than ordinary peers. In order to stream video to mobile devices, transcoding is often required to render video suitable for their small display, limited downlink speed, and limited video decoding capability. However, performing transcoding at a single peer is vulnerable to peer churn, which leads to video disruption. We propose interleaved distributed transcoding (IDT), a robust video encoding scheme that allows peers more capable than mobile devices to perform transcoding in a collaborative fashion. IDT is designed in such a way that transcoded substreams are assembled into a single video stream, which can be decoded by any H.264/AVC baseline profile compliant decoder. Extensive simulations and its implementation in a real P2P system demonstrate that the proposed scheme not only reduces computational load at a peer, but also achieves robust streaming in the case of peer failure or packet loss due to adverse wireless channel conditions. We confirm this finding by analyzing the effect of distributed transcoding under peer failure.     

Ant colony optimization based packet scheduler for peer-to-peer video streaming

This letter describes a new packet scheduling algorithm for enhancing the quality of distributed peer-to-peer video streaming. The algorithm was designed for when streaming server peers use error recovery such as automatic-repeat-request (ARQ) rather than error protection to avoid overburdening network resources. Ant colony optimization was used for scheduling groups of packets to reflect the channel status and error recovery effect of multiple server peers heuristically. Simulation results show that the proposed algorithm can enhance the quality of distributed video streaming services.     

A Bayesian approach for user aware peer-to-peer video streaming systems

Peer-to-Peer (P2P) architectures for live video streaming has attracted a significant attention from both academia and industry. P2P design enables end-hosts to relay streams to each other overcoming the scalability issue of centralized architectures. However, these systems struggle to provide a service of comparable quality to that of traditional television. Since end-hosts are controlled by users, their behavior has a strong impact on the performance of P2P streaming systems, leading to potential service disruption and low streaming quality. Thus, considering the user behavior in these systems could bring significant performance improvements. Toward this end, we propose a Bayesian network that captures all the elements making part of the user behavior or related to it. This network is built from the information found in a cross-analysis of numerous large-scale measurement campaigns, analyzing the user behavior in video streaming systems. We validate our model through intensive simulations showing that our model can learn a user behavior and is able to predict several activities helping thus in optimizing these systems for a better performance. We also propose a method based on traces collection of the same user type that accelerates the learning process of this network. Furthermore, we evaluate the performance of this model through exploring its applications and comparison with non-contextual models.     

On using peer-to-peer communication in cellular wireless data networks

A recent class of approaches for enhancing the performance of cellular wireless data networks has focused on improving the underlying network model. It has been shown that using the peer-to-peer network model, a mode of communication typically seen in ad hoc wireless networks, can result in performance improvements such as increased data rate, reduced transmission power, better load balancing, and enhanced network coverage. However, the true impact of adopting the peer-to-peer network model in such an environment is yet to be fully understood. In this paper, we investigate the performance benefits and drawbacks of using the peer-to-peer network model for Internet access in cellular wireless data networks. We find that, although the peer-to-peer network model has significantly better spatial reuse characteristics, the improved spatial reuse does not translate into better throughput performance. Instead, we observe that using the peer-to-peer network model as-is might actually degrade the throughput performance of the network. We identify and discuss the reasons behind these observations. Using the insights gained through the performance evaluations, we then propose two categories of approaches to improve the performance of the peer-to-peer network model: approaches that leverage assistance from the base station and approaches that leverage the relaying capability of multihomed hosts. Through simulation results, we show that using the peer-to-peer network model in cellular wireless data networks is a promising approach when the network model is complemented with appropriate mechanisms.     

Game-theoretic pricing for video streaming in mobile networks

Mobile phones are among the most popular consumer devices, and the recent developments of 3G networks and smart phones enable users to watch video programs by subscribing data plans from service providers. Due to the ubiquity of mobile phones and phone-to-phone communication technologies, data-plan subscribers can redistribute the video content to nonsubscribers. Such a redistribution mechanism is a potential competitor for the mobile service provider and is very difficult to trace given users' high mobility. The service provider has to set a reasonable price for the data plan to prevent such unauthorized redistribution behavior to protect or maximize his/her own profit. In this paper, we analyze the optimal price setting for the service provider by investigating the equilibrium between the subscribers and the secondary buyers in the content-redistribution network. We model the behavior between the subscribers and the secondary buyers as a noncooperative game and find the optimal price and quantity for both groups of users. Based on the behavior of users in the redistribution network, we investigate the evolutionarily stable ratio of mobile users who decide to subscribe to the data plan. Such an analysis can help the service provider preserve his/her profit under the threat of the redistribution networks and can improve the quality of service for end users.     

Transmission algorithm for video streaming over cellular networks

2.5G and 3G cellular networks are becoming more widespread and the need for value added services increases rapidly. One of the key services that operators seek to provide is streaming of rich multimedia content. However, network characteristics make the use of streaming applications very difficult with an unacceptable quality of service (QoS). The 3GPP standardization body has standardized streaming services that will benefit operators and users. There is a need for a mechanism that will enable a good quality multimedia streaming that uses the 3GPP standard. This paper describes an adaptive streaming algorithm that uses the 3GPP standard. It improves significantly the QoS in varying network conditions while monitoring its performance using queueing methodologies. The algorithm utilizes the available buffers on the route of the streaming data in a unique way that guarantees high QoS. The system is analytically modeled: the streaming server, the cellular network and the cellular client are modeled as cascaded buffers and the data is sequentially streamed between them. The proposed Adaptive streaming algorithm (ASA) controls these buffers’ occupancy levels by controlling the transmission and the encoding rates of the streaming server to achieve high QoS for the streaming. It overcomes the inherent fluctuations of the network bandwidth. The algorithm was tested on General Packet Radio Service (GPRS), Enhanced Data rates for GSM Evolution (EDGE) and Universal Mobile Telecommunication System (UMTS) networks. The results showed substantial improvements over other standard streaming methods used today.     

Resource management for video streaming in ad hoc networks

Video streaming over wireless links is a challenging issue due to the stringent Quality-of-Service (QoS) requirements of video traffic, the limited wireless channel bandwidth and the broadcast nature of wireless medium. As contention-based or reservation-based (i.e., contention-free) medium access control (MAC) protocols in existing wireless link-layer standards cannot efficiently support multimedia applications such as video streaming, a hybrid approach has been proposed, which uses both contention and reservation-based channel access mechanisms to transmit packets for each video source. Using this content-aware resource management approach, each video source reserves well below its peak data rate, and uses contention-based media access to transmit the remainder of the packets. In this paper, we first propose two conflict avoidance strategies and two buffering architectures for video streaming over ad hoc networks. Considering the interactions of reservation and contention, we develop the analytical model for the saturated traffic case and then extend it to derive tight performance bounds for the unsaturated case. Using the MAC protocols specified in the WiMedia ECMA-368 standard as an example, extensive simulations have been conducted to validate the analysis. Real video traces have been used to examine the video streaming performance. The analytical and simulation results demonstrate the effectiveness and efficiency of the hybrid resource management approach, and also reveal the impact of the conflict avoidance strategy and buffering design on the video performance.     

Application-driven cross-layer optimization for video streaming over wireless networks

Mobile multimedia applications require networks that optimally allocate resources and adapt to dynamically changing environments. Cross-layer design (CLD) is a new paradigm that addresses this challenge by optimizing communication network architectures across traditional layer boundaries. In this article we discuss the relevant technical challenges of CLD and focus on application-driven CLD for video streaming over wireless networks. We propose a cross-layer optimization strategy that jointly optimizes the application layer, data link layer, and physical layer of the protocol stack using an application-oriented objective function in order to maximize user satisfaction. In our experiments we demonstrate the performance gain achievable with this approach. We also explore the trade-off between performance gain and additional computation and communication cost introduced by cross-layer optimization. Finally, we outline future research challenges in CLD.     

Multi-stream 3D video distribution over peer-to-peer networks

The recent advances in stereoscopic video capture, compression, and display have made 3-dimensional (3D) video a visually appealing and costly affordable technology. There have been a series of pioneer works on streaming 3D video over the Internet. Yet the remarkably increased data volume of 3D videos poses great challenges to the conventional client/server design, which has already suffered from supporting 2D videos.In this paper, we present an initial attempt toward efficient streaming of 3D videos over a peer-to-peer network. We show that the inherent multi-stream nature of 3D video makes playback synchronization more difficult, which is particularly acute with the existence of multiple senders in a peer-to-peer overlay. We address this by a novel 2-stream 2-stage buffer design, together with weighted data scheduling and light-weight synchronization. We further discuss a series of key practical issues toward implementing our peer-to-peer 3D video streaming system, including the weight modeling for data segments, the interactions with the RTP/RTCP protocol stack, and the inter-operability with monoscopic video as well as extension to multi-view video. We have evaluated the performance of our system under different end-system and network configurations with typical 3D video streams. The simulation results demonstrate the superiority of our system in terms of both scalability and streaming quality.     

A peer-to-peer architecture for media streaming

Given that the Internet does not widely support Internet protocol multicast while content-distribution-network technologies are costly, the concept of peer-to-peer could be a promising start for enabling large-scale streaming systems. In our so-called Zigzag approach, we propose a method for clustering peers into a hierarchy called the administrative organization for easy management, and a method for building the multicast tree atop this hierarchy for efficient content transmission. In Zigzag, the multicast tree has a height logarithmic with the number of clients, and a node degree bounded by a constant. This helps reduce the number of processing hops on the delivery path to a client while avoiding network bottlenecks. Consequently, the end-to-end delay is kept small. Although one could build a tree satisfying such properties easily, an efficient control protocol between the nodes must be in place to maintain the tree under the effects of network dynamics. Zigzag handles such situations gracefully, requiring a constant amortized worst-case control overhead. Especially, failure recovery is done regionally with impact on, at most, a constant number of existing clients and with mostly no burden on the server.     

Cross-layer design of ad hoc networks for real-time video streaming

Cross-layer design breaks away from traditional network design where each layer of the protocol stack operates independently. We explore the potential synergies of exchanging information between different layers to support real-time video streaming. In this new approach information is exchanged between different layers of the protocol stack, and end-to-end performance is optimized by adapting to this information at each protocol layer. We discuss key parameters used in the cross-layer information exchange along with the associated cross-layer adaptation. Substantial performance gains through this cross-layer design are demonstrated for video streaming.     

GOP-based channel rate allocation using genetic algorithm for scalable video streaming over error-prone networks.

In this paper, we address the problem of unequal error protection (UEP) for scalable video transmission over wireless packet-erasure channel. Unequal amounts of protection are allocated to the different frames (I- or P-frame) of a group-of-pictures (GOP), and in each frame, unequal amounts of protection are allocated to the progressive bit-stream of scalable video to provide a graceful degradation of video quality as packet loss rate varies. We use a genetic algorithm (GA) to quickly get the allocation pattern, which is hard to get with other conventional methods, like hill-climbing method. Theoretical analysis and experimental results both demonstrate the advantage of the proposed algorithm.