Practical design of a proxy agent to facilitate adaptive video streaming service across wired/wireless networks

Thanks to the growing of the wireless networks, the video streaming application becomes a ubiquitous joyful service. In a wireless communication network environment, the service traffic spans across the wired and wireless domains. In this article, we propose a practical design of a proxy agent - SPONGE (Stream Pooler Over a Network Graded Environment) sitting between the wireless User Equipments (UEs) and the video streaming server to facilitate the adaptive video streaming service across wired/wireless networks. To make the wireless streaming service more efficient, an input video session would be encoded as multiple qualities of video streams so that UEs with a similar receiving condition can share streams with the same service quality via SPONGE. SPONGE can alleviate the direct load on the original stream broadcasting server. Meanwhile, it can make each UE get an adaptive streaming service according to the network conditions of the UE by a reduced network condition feedback latency. Our theoretical analysis and simulation results show that SPONGE can help wireless streaming users get a smooth and better playback quality by a quick and accurate reaction to the network condition.     

Adaptive interface selection over cloud-based split-layer video streaming via multi-wireless networks

As mobile devices such as tablet PCs and smartphones proliferate, the online video consumption over a wireless network has been accelerated. From this phenomenon, there are several challenges to provide the video streaming service more efficiently and stably in the heterogeneous mobile environment. In order to guarantee the QoS of real-time HD video services, the steady and reliable wireless mesh is necessary. Furthermore, the video service providers have to maintain the QoS by provisioning streaming servers to respond the clients’ request of different video resolution. In this paper, we propose a reliable cloud-based video delivery scheme with the split-layer SVC encoding and real-time adaptive multi-interface selection over LTE and WiFi links. A split-layer video streaming can effectively scale to manage the required channels on each layer of various client connections. Moreover, split-layer SVC model brings streaming service providers a remarkable opportunity to stream video over multiple interfaces (e.g. WiFi, LTE, etc.) with a separate controlling based on their network status. Through the adaptive interface selection, the proposed system aims to ensure the maximizing video quality which the bandwidth of LTE/WiFi accommodates. In addition, the system offers cost-effective streaming to mobile clients by saving the LTE data consumption. In our system, an adaptive interface selection is developed with two different algorithms, such as INSTANT and EWMA methods. We implemented a prototype of mobile client based on iOS particularly by using iPhone5S. Moreover, we also employ the split-layer SVC encodes in streaming server-side as the add-on module to SVC reference encoding tool in a virtualized environment of KVM hypervisor. We evaluated the proposed system in an emulated and a real-world heterogeneous wireless network environments. The results show that the proposed system not only achieves to guarantee the highest quality of video frames via WiFi and LTE simultaneous connection, but also efficiently saves LTE bandwidth consumption for cost-effectiveness to client-side. Our proposed method provides the highest video quality without deadline misses, while it consumes 50.6% LTE bandwidth of ‘LTE-only’ method and 72.8% of the conventional (non-split) SVC streaming over a real-world mobile environment.     

开放型网络英语教学系统中流媒体QoS的研究

采用设置本地端缓冲服务器的方法提高流传榆质量．在开放型网络英语教学系统中应用流媒体提供QoS的管理功能,解决音视频流缓冲问题,并提供相应机制支持网络环境下的流媒体QoS。实验结果表明,流体系结构较好实现网络教学环境下的流媒体播放,保证音视频流的QoS。采用此流体系结构能较好地实现对流的管理和控制。从而保证多媒体课件的传输质量。     

开放型网络英语教学系统中流媒体QoS的研究

采用设置本地端缓冲服务器的方法提高流传输质量,在开放型网络英语教学系统中应用流媒体提供QoS的管理功能,解决音视频流缓冲问题,并提供相应机制支持网络环境下的流媒体QoS。实验结果表明,流体系结构较好实现网络教学环境下的流媒体播放,保证音视频流的QoS。采用此流体系结构能较好地实现对流的管理和控制,从而保证多媒体课件的传输质量。     

A study of adaptive forward error correction for wireless collaborative computing

This paper addresses the problem of reliably multicasting Web resources across wireless local area networks (WLANs) in support of collaborative computing applications. An adaptive forward error correction (FEC) protocol is described, which adjusts the level of redundancy in the data stream in response to packet loss conditions. The proposed protocol is intended for use on a proxy server that supports mobile users on a WLAN. The software architecture of the proxy service and the operation of the adaptive FEC protocol are described. The performance of the protocol is evaluated using both experimentation on a mobile computing testbed as well as simulation. The results of the performance study show that the protocol can quickly accommodate worsening channel characteristics in order to reduce delay and increase throughput for reliable multicast channels.     

Disseminating streaming data in a dynamic environment: an adaptive and cost-based approach

In a distributed stream processing system, streaming data are continuously disseminated from the sources to the distributed processing servers. To enhance the dissemination efficiency, these servers are typically organized into one or more dissemination trees. In this paper, we focus on the problem of constructing dissemination trees to minimize the average loss of fidelity of the system. We observe that existing heuristic-based approaches can only explore a limited solution space and hence may lead to sub-optimal solutions. On the contrary, we propose an adaptive and cost-based approach. Our cost model takes into account both the processing cost and the communication cost. Furthermore, as a distributed stream processing system is vulnerable to inaccurate statistics, runtime fluctuations of data characteristics, server workloads, and network conditions, we have designed our scheme to be adaptive to these situations: an operational dissemination tree may be incrementally transformed to a more cost-effective one. Our adaptive strategy employs distributed decisions made by the distributed servers independently based on localized statistics collected by each server at runtime. For a relatively static environment, we also propose two static tree construction algorithms relying on apriori system statistics. These static trees can also be used as initial trees in a dynamic environment. We apply our schemes to both single- and multi-object dissemination. Our extensive performance study shows that the adaptive mechanisms are effective in a dynamic context and the proposed static tree construction algorithms perform close to optimal in a static environment.     

Enabling broadcast of user-generated live video without servers

We are witnessing the unprecedented popularity of User-Generated-Content (UGC) on the Internet. While YouTube hosts pre-recorded video clips, in near future, we expect to see the emergence of User-Generated Live Video, for which any user can create its own temporary live video channel from a webcam or a hand-held wireless device. Hosting a large number of UG live channels on commercial servers can be very expensive. Server-based solutions also involve various economic, copyright and content control issues between users and the companies hosting their content. In this paper, leveraging on the recent success of P2P video streaming, we study the strategies for end users to directly broadcast their own live channels to a large number of audiences without resorting to any server support. The key challenge is that end users are normally bandwidth constrained and can barely send out one complete video stream to the rest of the world. Existing P2P streaming solutions cannot maintain a high level of user Quality-of-Experience (QoE) with such a highly constrained video source. We propose a novel Layered P2P Streaming (LPS) architecture, to address this challenge. LPS introduces playback delay differentiation and constructs virtual servers out of peers to boost end users’ capability of driving large-scale video streaming. Through detailed packet-level simulations and PlanetLab experiments, we show that LPS enables a source with upload bandwidth slightly higher than the video streaming rate to stream video to tens of thousands of peers with premium quality of experience.     

基于P2P的用户生产内容视频资源查找策略

现有用户生产内容(UGC)类视频系统通常采用C/S架构设计,导致了视频服务器极大的带宽压力。提出一种采用对等网(P2P)的在线短视频查找策略——FastSearch,其目的是利用视频资源之间的关联关系进行视频资源定位,以显著提高点播节点之间的视频分享效率并降低对视频服务器的带宽需求。实验表明FastSearch具备良好的视频数据源节点查找能力,集成了该查找策略的短视频系统能有效减少对视频服务器的带宽消耗。     

An Adaptive Live Streaming Mechanism for Heterogeneous Vehicular Networks

With the popularity of vehicular networks, how to maintain high quality of the seamless live streaming service is a great challenge. In this work, an adaptive seamless live streaming dissemination system for heterogeneous vehicular networks to tackle this challenging issue is presented. First, differential service is presented in this work to ensure that paid users can satisfy the live steaming service. Based on users’ service-level agreement, an adaptive bandwidth allocation policy is proposed in this work to attain seamless handoff. In addition, because vehicles enter into the areas of hotspots, we also present a mechanism not only to prevent the insufficient bandwidth in advance, but also to make sure the paid users have higher priority than free users to obtain the seamless streaming service. When an unavoidable congestion occurs, we compress the streaming videos with a Region of Interest approach based on the content and characters of the video in order to maintain the service quality of paid users and reduce the required bandwidth for the streaming services. A series of simulation results show that our mechanism achieves better performance in terms of bandwidth utilization, packet loss ratio, and blocking probability. The capability of self-adaption in volatile real-time vehicular environment assists in the effectiveness and practicability of our proposed approach.     

An efficient playout smoothing mechanism for layered streaming in P2P networks

Layered video streaming in peer-to-peer (P2P) networks has drawn great interest, since it can not only accommodate large numbers of users, but also handle peer heterogeneity. However, there’s still a lack of comprehensive studies on chunk scheduling for the smooth playout of layered streams in P2P networks. In these situations, a playout smoothing mechanism can be used to ensure the uniform delivery of the layered stream. This can be achieved by reducing the quality changes that the stream undergoes when adapting to changing network conditions. This paper complements previous efforts in throughput maximization and delay minimization for P2P streaming by considering the consequences of playout smoothing on the scheduling mechanisms for stream layer acquisition. The two main problems to be considered when designing a playout smoothing mechanism for P2P streaming are the fluctuation in available bandwidth between peers and the unreliability of user-contributed resources—particularly peer churn. Since the consideration of these two factors in the selection and scheduling of stream layers is crucial to maintain smooth stream playout, the main objective of our smoothing mechanism becomes the determination of how many layers to request from which peers, and in which order. In this work, we propose a playout smoothing mechanism for layered P2P streaming. The proposed mechanism relies on a novel scheduling algorithm that enables each peer to select appropriate stream layers, along with appropriate peers to provide them. In addition to playout smoothing, the presented mechanism also makes efficient use of network resources and provides high system throughput. An evaluation of the performance of the mechanism demonstrates that the proposed mechanism provides a significant improvement in the received video quality in terms of lowering the number of layer changes and useless chunks while improving bandwidth utilization.     

Design and implementation of MP3-music on demand system using streaming technology

The success of the Internet and the use of broadband in homes have caused a gradual shift in traffic on the Internet from data to multimedia communication. Multimedia applications typically include a large quantity of video/audio information. Streaming technology is normally adopted to handle the transmission of multimedia traffic and thus reduce the buffer requirement on the client side and the service request/response time. This work focuses on the transmission of MP3 music which has a constant bit rate characteristic. The design of both the server side and the client side of the MP3-music on demand (MoD) system with streaming technology, is considered to meet the quality of service (QoS) requirements of MP3 music. A stream buffering technique is used and an adaptive rate control mechanism is applied in combination with a client feedback packet to prevent stream buffer overflow or underflow on the client side, and thereby accommodate the network delay, jitter, and timing deviation between the server machine and the client host. A server self-timing revision scheme is used to reduce the network overhead of the feedback mechanism. The adaptive rate control mechanism is developed and verified using a computer simulation. Finally, for completeness a MoD system is constructed with a low-cost embedded network system to which an Altera FPGA is applied to provide cut-through data movement and an adaptive rate control mechanism is realized to evaluate QoS.     

Minimizing bandwidth requirements for on-demand data delivery

Two recent techniques for multicast or broadcast delivery of streaming media can provide immediate service to each client request, yet achieve considerable client stream sharing which leads to significant server and network bandwidth savings. The paper considers: 1) how well these recently proposed techniques perform relative to each other and 2) whether there are new practical delivery techniques that can achieve better bandwidth savings than the previous techniques over a wide range of client request rates. The principal results are as follows: First, the recent partitioned dynamic skyscraper technique is adapted to provide immediate service to each client request more simply and directly than the original dynamic skyscraper method. Second, at moderate to high client request rates, the dynamic skyscraper method has required server bandwidth that is significantly lower than the recent optimized stream tapping/patching/controlled multicast technique. Third, the minimum required server bandwidth for any delivery technique that provides immediate real-time delivery to clients increases logarithmically (with constant factor equal to one) as a function of the client request arrival rate. Furthermore, it is (theoretically) possible to achieve very close to the minimum required server bandwidth if client receive bandwidth is equal to two times the data streaming rate and client storage capacity is sufficient for buffering data from shared streams. Finally, we propose a new practical delivery technique, called hierarchical multicast stream merging (HMSM), which has a required server bandwidth that is lower than the partitioned dynamic skyscraper and is reasonably close to the minimum achievable required server bandwidth over a wide range of client request rates     

面向网格的时移电视系统研究

基于网格技术提出了时移电视服务系统(GridTVOD,Time-shifted TV on demand based on grid).在GridTVOD系统中,系统组织基于Globus MDS,将视频服务器和服务节点组织为流媒体服务网格,视频数据传输采用P2P和Patching相结合,用户作为网格节点,在享受服务时,也作为服务端为其它节点提供服务.整个系统具有如下特点:1)采用流合并机制,有效地减少媒体服务器提供的基流数;2)采用分布式控制协议,系统具有良好的可扩展性;3)利用网格技术,为系统组织提供安全、有效的保障.     

Server side,play buffer based quality control for adaptive media streaming

Existing media streaming protocols provide bandwidth adaptation features in order to deliver seamless video streams in an abrupt bandwidth shortage on the networks. For instance, popular HTTP streaming protocols such as HTTP Live Streaming (HLS) and MPEG-DASH are designed to select the most appropriate streaming quality based on client side bandwidth estimation. Unfortunately, controlling the quality at the client side means the effectiveness of the adaptive streaming is not controlled by service providers, and it harms the consistency in quality-of-service. In addition, recent studies show that selecting media quality based on bandwidth estimation may exhibit unstable behavior in certain network conditions. In this paper, we demonstrate that the drawbacks of existing protocols can be overcome with a server side, buffer based quality control scheme. Server side quality control solves the service quality problem by eliminating client assistance. Buffer based control scheme eliminates the side effects of bandwidth based stream selection. We achieve this without client assistance by designing a play buffer estimation algorithm. We prototyped the proposed scheme in our streaming service testbed which supports pre-transcoding and live-transcoding of the source media file. Our evaluation results show that the proposed quality control performs very well both in simulated and real environments.     

A Cyclic Interface for the Presentation of Multiple Music Files

This paper proposes a novel cyclic interface for browsing through a song database. The method, which sums multiple audio streams on a server and broadcasts only a single summed stream, allows the user to hear different parts of each audio stream by cycling through all available streams. Songs are summed into a single stream based on a combination of spectral entropy and local power of each song's waveform. Perceptual parameters of the system are determined based on experiments conducted on 20 users, for three, four, and five songs. Results illustrate that the proposed methodology requires less listening time as compared to traditional list-based interfaces when the desired audio clip is among one of the audio streams. Applications of this methodology include any search system which returns multiple audio search results, including music query by example. The proposed methodology can be used for real-time searching with an ordinary internet browser.      

Towards a structure-aware failure semantics for streaming media communication models

Failure semantics in communication models for distributed systems deal with the impossibility of achieving an exactly once invocation semantics in failure-prone environments. For remote procedure invocation models, failure semantics such as at-least-once and at-most-once specify guarantees about the number of executions of an invocation as well as its completeness even under the assumption that communication and server failures may occur.While such failure semantics are quite successful for remote procedure call models they have significant weaknesses when applied to streaming media communication. The main reasons are fundamental differences in the basic communication model as well as case-dependency and granularity of failure treatment in media streams, resulting in awkward abstractions as well as inefficient implementations.This paper is a step towards an adaptive failure semantics for streaming media communication. We argue that in order to achieve simplicity and economy, failure semantics must dynamically exploit application-level knowledge as well as knowledge from lower system layers, the three corner stones being media stream structure, timing constraints and resource availability.The paper focuses on structure-awareness as one of these three corner stones. It discusses the role of importance of a media stream fragment, develops a function to quantify importance, and discusses its computability. Experimental results evaluating importance based failure handling conclude the work.     

面向新媒体广播的慢录剪辑服务器

随着流媒体技术的飞速发展和完善,传统流媒体广播服务器已经不能满足大众们的收听需求。为提高传统流媒体服务器的整体性能,通过对传统流媒体服务器功能和结构的分析研究,设计和实现了慢录剪辑服务器系统,将慢录剪辑功能从传统流媒体服务器中分离出来。通过采用模块化设计方法,设计并实现各相应功能模块,确保了对媒体流的实时接收,完成了对接收的媒体流进行正确的剪辑、同步备份,实现了慢录剪辑服务器工作的高稳定性和同步的及时性。采用以理论分析和实验论证相结合的方法,表明所设计慢录剪辑服务器的工作稳定性和有效性均满足要求。     

Modeling users on the World Wide Web based on cognitive factors,navigation behavior and clustering techniques

This paper focuses on modeling users’ cognitive styles based on a set of Web usage mining techniques on user navigation patterns and clickstream data. Main aim is to investigate whether specific clustering techniques can group users of particular cognitive style using measures obtained from psychometric tests and content navigation behavior. Three navigation metrics are proposed and utilized to find identifiable groups of users that have similar navigation patterns in relation to their cognitive style. The proposed work has been evaluated with two user studies which entail a psychometric-based survey for extracting the users’ cognitive styles, combined with a real usage scenario of users navigating in a controlled Web 2.0 environment. A total of 106 participants of age between 17 and 25 participated in the study providing interesting insights with respect to cognitive styles and navigation behavior of users. Studies like the reported one can be useful for modeling users and assist adaptive Web 2.0 environments to organize and present information and functionalities in an adaptive format to diverse user groups.     

Buffer-assisted on-demand multicast for VOD applications

Multicast communications is widely used by streaming video applications to reduce both server load and network bandwidth. However, receivers in a multicast group must access the multicast stream simultaneously, and this restriction on synchronous access diminishes the benefit of multicast because users in a video-on-demand service usually issue requests asynchronously, i.e., at anytime. In this paper, we not only formulate this streaming problem but also propose a new multicast infrastructure, called buffer-assisted on-demand multicast, to allow receivers accessing a multicast stream asynchronously. A timing control mechanism is integrated on intermediate routing nodes (e.g., routers, proxies, or peer nodes in a peer-to-peer network) to branch time-variant multicast sub-streams to corresponding receivers. Besides, an optimal routing path and the corresponding buffer allocations for each request must be carefully determined to maximize the throughput of the multicast stream. We prove that the time complexity to solve this routing problem over general graph networks is NP-complete, and then propose a routing algorithm for overlay networks to minimize server load. Simulation results demonstrate that buffer-assisted on-demand multicast outperforms many popular streaming methods.