Quality Of Streaming Services Research Articles

The Impact of App Football Live Streaming Service Quality on User Loyalty: Multiple Mediating Roles based on Different OnlineWatching Motivations

The Impact of App Football Live Streaming Service Quality on User Loyalty: Multiple Mediating Roles based on Different OnlineWatching Motivations

Retraction Note: Maximizing quality of multimedia streaming services in heterogeneous wireless networks using optimal multi-server technique

Retraction Note: Maximizing quality of multimedia streaming services in heterogeneous wireless networks using optimal multi-server technique

Adaptive Wireless Video Streaming: Joint Transcoding and Transmission Resource Allocation

The emerging mobile edge computing (MEC) technology has been recently applied to improve adaptive bitrate (ABR) streaming service quality under time-varying wireless channels. In this paper, we consider a heterogeneous multi-user MEC-enabled video streaming network with time-varying wireless channels in sequential time frames. In particular, we aim to design an online joint transcoding and transmission resource allocation algorithm to maximize the ABR streaming user’s quality of experience (QoE) subject to the bandwidth and CPU constraints. The algorithm is “online” in the sense that the bitrate and resource allocation decisions made at each frame depend only on the observation of past events. We formulate the problem as a mixed integer non-linear programming (MINLP) that jointly determines bitrate adaptation, bandwidth allocation, and CPU cycle assignment. To cope with the challenge arising from the coupling decisions of adjacent frames, we propose a low-complexity online algorithm, named OCCA. Specifically, by introducing queueing model constraints, we transform the offline non-conex MINLP problem into a multi-frame problem. Then, we analytically decouple the multi-stage(frame) problem to multiple per-frame convex subproblems that can be solved with high robustness and low computational complexity. We perform simulations with realistic scenarios to evaluate the performance of the proposed algorithm. Results manifest that compared with state-of-the-art approaches, our proposed algorithm can provide 97.84% (on average) extra QoE.

The Impacts of Service Quality, Perceived Value, and Social Influences on Video Streaming Service Subscription

ABSTRACT This study investigates the factors affecting U.S. consumers’ willingness to continue and subscribe to video streaming services. Three explanatory factors, video streaming service quality, perceived value, and social influences, are proposed to predict consumer subscription. By surveying 834 online video streaming users in the U.S., the analysis results show that five predictors from these three aspects best predict consumers’ willingness to continue and subscribe to video streaming services, including service system reliability, compatibility, perceived enjoyment, perceived controllability, and normative pressure (social norms). Theoretical and practical implications are discussed to help deepen our understanding of paid media subscriptions in a highly competitive market environment.

Customer-in-Loop Adaptive Supply Chain Migration Model to Enable IoT

Poised to smart citizenry engagement, an unprecedented deluge of high quality streaming services induce a major data traffic challenge in Fourth Generation (4G) bandwidth and coverage, the upcoming smart city expectations cannot be ignored, eventually. The bottlenecks in ever exploiting benefits such as e-Life, to name a few at Mobile Equipment Providers (MEP) tiers, are complemented at Device Dependent Device Independent (D3I) configurations inherent at various tiers of Mobile Service Providers (MSP). While enabling a Supply Chain Management (SCM) augments a unique system support involving the MSPs and MEPs for desired Customer Relationship Management (CRM), Ad hoc Resource Planning (ARP), which we found prevalent in migration scenario from 4G to 5G technology deployment. Despite its complexity both in term of one-to-many and many-to-one across diverse MSP and MEP options, SCM operational objectives sets forth a unique challenge, hence is the main objective for our work presented here. In this paper, we presented a framework to enhance the 4G legacy in mobile service provider capacity for smart city Machine-to-Machine (M2M) backbone. The migration process is assessed with proposed strategic, technical and operational indicators, which demonstrate its adaptability and flexibility while integrating in conventional 4G deployments, especially taking into account radio devices and applications. Web-enabled Software Define Radio devices and applications are used to index the migration cost and support SCM planning and execution. We identify, the decentralization of mobile service providers infrastructure plays a major role in reducing the embedded complexity which often appears as primary bottleneck. MSP as a key player in the elasticity of migration, we presented a platform to support large as well as low MEP-MSP co-deployments. Pareto multi-criteria optimization is used to find the strategic indicators which are primary Transformation Steering Factors (TSF), valid in both device dependent or device independent M2M migration. We expose our result for achieving TSF, while rolling interoperability and reconfiguration of device deployed in a typical volatile inter-MSP or intra-MSPs tiers. Pareto Migration Indicators (MI) are optimized successively progressing across the transformation schemes; relative to base-line MSP services, hence enabling a lucrative choice while elasticity of provider-centric cost depends adaptively on technology legacy and M2M access of User Equipment (UE).

Adaptive Customer-In-Loop Supply Chain Management For 5G Migration

Despite the ever exploiting benefits in Fourth Generation (4G) Telecom such as e-Life from Etisalat-UAE, vendors’ economical limitation for providing high quality streaming services in limited bandwidth and coverage expectation cannot be ignored. A unique systems support involving the Customer Relationship, Resource Planning, and Supply Chains exist in both Mobile Service Providers and Mobile Equipment Providers. Despite its complexity, the operational objectives of SCM planning may vary greatly from MSP to MSP and MEP to MEP, hence is the main objective for our work presented here. In this paper, we explore the strategic, technical and operational indicators, while migrating legacy 4G MSP deployments into 5G to conform the e-governess needs.

RETRACTED ARTICLE: Maximizing quality of multimedia streaming services in heterogeneous wireless networks using optimal multi-server technique

User expectations pertaining to multimedia data is huge. Issues in streaming like slow start and buffering hinder the quality of received content. Many authors have addressed the buffering issues. Their solutions in order to avoid buffering focussed on reducing the received multimedia quality in an attempt to avoid buffering. In this proposed work, quality issues in multimedia streaming have been focussed upon in WLAN-4G networks. A modified cat swarm optimization algorithm for optimal server selection (MCSO-SS) has been proposed to maximize the multimedia quality in terms of quality of service (QoS) and quality of experience (QoE). The proposed technique has been tested in a heterogeneous wireless environment that includes WLAN and 4G cellular networks. Experimental results prove that our proposed MCSO-SS based streaming technique increases the received multimedia content quality compared to existing techniques in terms of QoS (delay, throughput, service failure rate), and QoE (PSNR, SSIM).

Estimating the Optimal Buffer Size on Mobile Devices for Increasing the Quality of Video Streaming Services

Estimating the Optimal Buffer Size on Mobile Devices for Increasing the Quality of Video Streaming Services

Implementation and Analysis of Real-Time Streaming Protocols.

Communication media have become the primary way of interaction thanks to the discovery and innovation of many new technologies. One of the most widely used communication systems today is video streaming, which is constantly evolving. Such communications are a good alternative to face-to-face meetings, and are therefore very useful for coping with many problems caused by distance. However, they suffer from different issues such as bandwidth limitation, network congestion, energy efficiency, cost, reliability and connectivity. Hence, the quality of service and the quality of experience are considered the two most important issues for this type of communication. This work presents a complete comparative study of two of the most used protocols of video streaming, Real Time Streaming Protocol (RTSP) and the Web Real-Time Communication (WebRTC). In addition, this paper proposes two new mobile applications that implement those protocols in Android whose objective is to know how they are influenced by the aspects that most affect the streaming quality of service, which are the connection establishment time and the stream reception time. The new video streaming applications are also compared with the most popular video streaming applications for Android, and the experimental results of the analysis show that the developed WebRTC implementation improves the performance of the most popular video streaming applications with respect to the stream packet delay.

Low Cost Cloud-Assisted Peer to Peer Live Streaming

Recently, Peer-to-Peer (P2P) live streaming assisted by the cloud computing has attracted considerable attention to improve the reliability of the P2P such as the resilience to peer churn and the shortage of upload capacity. The cost of cloud-assistance is comprised of the number of requests issued to the cloud and the amount of data fetched from the cloud. In this paper, we propose three techniques to reduce the cost of such a cloud-assistance.More concretely, in the proposed method, 1) each peer which lost its parent in the overlay can find a new parent by referring to the information registered in the cloud, 2) several peers which proactively fetch chunks from the cloud are dynamically invested, and 3) the number of requests issued to the cloud is reduced by allowing peers to fetch a collection of chunks using a single request. The performance of the proposed method is evaluated by simulation. The simulation results indicate that it reduces the cost of conventional scheme by 46% while guaranteeing the quality of live streaming service.

Analisis Quality Of Service Video Streaming Pada Ethernet Over Internet Protocol Dengan Metode Priority Queueing Dan Per Connection Queue

There is increasing number of Indonesian people untilizing video streaming application in ther daily life. Video streaming can be used for farious activities such as distant learning, or as a monitoring facility. Public network (internet) has some suscepbtiilities on the scurity of the data being transmitted. To  overcome this,  Tunneling network technology is  used.  In  QOS  video streaming  analysis  on  EOIP  protocol the  process  start  with  system  designing,  hardware installation, video server installation of EOIP, PQ method implementation, PCQ methot implementation, data retival end data analisys. In this research, the followings are anallyzed: video streaming QOS (Quality of Service) on EOIP (Ethernet Over Internet Protocol) by means of PQ (Priority Queuing) and PCQ (Per Connection Queue), covering QOS parameter i.e. Delay, Jitter and Throughput. The result show that on the video streaming with PQ(Priority Queuing) and (Per Connection Queue) there is a discrepancy of QoS. PQ method is supportive towards QOS for the highest priority client. This is because streaming server can give priority service for client having the highest priority, so as to have a better QOS. PCQ method is very supportive towards QOS among clients because streaming server can distribute service to several clients doing streaming activity simultaneously.

Smart Streaming for Online Video Services

Bandwidth cost is a significant concern for online video service providers. Today's video streaming systems mostly use HTTP streaming, with users accessing video segments as HTTP requests. A frequently used strategy is to serve all user requests as fast as possible, as if the user is downloading a file. The downloading rate can often far exceed the playback rate, when the system is below the peak load. This is known as progressive downloading. Since users may quit before viewing the complete video, however, much of the downloaded video can be “wasted.” By studying and exploiting the predictability of users' departure behavior , the authors developed a smart streaming strategy that can significantly improve overall streaming service quality under given server bandwidth. The improvement is achieved by avoiding the waste based on predicted user departure behavior. The proposed smart streaming technique is evaluated by modeling, analysis, and simulation, as well as experimentation using a prototype implementation.

DASH 기반 VBR 비디오 스트리밍 서비스의 QoE 향상을 위한 품질 적응 기법

There are many current researches that are looking to improve the quality of HTTP adaptive streaming services. However, the existing schemes have a serious problem of QoE (Quality of Experience) degradation because few consider VBR video transmission. To cope with this problem, in this paper, we proposed a novel media quality adaptation scheme called CB-DASH (Content and Buffer-aware DASH). The proposed scheme controlled the video quality considering the VBR characteristics of video and the client's buffer state. Through the simulation, we proved that our scheme accomplished a more accurate estimated bandwidth than the conventional DASH and improved the QoE of streaming service.

A buffer-aware HTTP live streaming approach for SDN-enabled 5G wireless networks

With increasing interest in the concept of 5G wireless networks and the popularization of mobile devices, users gradually watch videos through mobile devices in streaming mode rather than off-line mode. However, the latency and lags of mobile networks will reduce the quality of service. In HTTP live streaming services, when there are multiple sources for the same content stored in the streaming servers, the suited quality content is able to be selected for playing according to the networking bandwidth conditions between servers and user equipment, and the users can obtain appropriate streaming quality automatically. However, the selection policy is difficult to be approved between 5G wireless communication networks and SDNs. In this study a buffer-aware HTTP live streaming approach is proposed, which evaluates the weights of media segments to decide the transmitting priorities based on the current playing time and adjust the appropriate transmission path through the decision making network controller according to the utilization and stability of the routers and switches in SDN. Finally, the experimental results proved that the approach is able to correct the overall streaming source sequence with the buffer status to effectively upgrade overall streaming service quality, as well as maintain a certain level of streaming quality for SDN-enable 5G wireless networks.

A Server-based Flow Allocation Scheme for Streaming Services in Data Center Networks

Abstract Streaming services provided by data centers (DCs) have become increasingly popular. The quality of streaming services greatly depends on network conditions, though, such as available bandwidth and delay time characteristics. To realize high quality stream- ing services, selecting an appropriate access network among available ones is necessary. However, in wireless LANs, a station (STA) simply selects an access point (AP) with the maximum received signal strength to connect to the Internet. Therefore, the service quality will deteriorate when access from STAs is concentrated in a specific AP. In this paper, we propose a server-based flow allocation scheme based on collectable information in DC networks to enable high quality streaming services. This scheme collects information, including the packet loss rate of existing flows as well as the available bandwidth of access networks, and then allocates a streaming flow to an appropriate access network based on the collected information. We show the effectiveness of this approach through simulation evaluations.

A novel server selection approach for mobile cloud streaming service

Mobile cloud streaming has become very popular recently. However, the centralized datacenter structure may lead to high service delay, especially for real time and high bandwidth streaming services. Deploying cloud edge servers may improve the quality of mobile streaming services in theory, but it cannot well adapt to the user mobility. To deal with this problem, this paper puts forward our MACSS, a mobility-aware framework for mobile cloud streaming services, which provides dynamic and optimized server selection functions to support user mobility comprehensively. Then we further propose CQS3, a novel quality-aware scheme that frequently redirects user requests to the “best” server according to comprehensive service quality grade. Simulation results show that CQS3 scales well and guarantees comparable delay performance. In addition, CQS3 can significantly improve PSNR comparing with CSS and is well adapted to user mobility and channel variation.

Quality of service management for IPTV services support in VANETs: a performance evaluation study

In order to deliver a qualitative Internet Protocol Television (IPTV) service over vehicular ad hoc networks (VANETs), a quality of service (QoS) mechanism is needed to manage the allocate of network resources to the diverse IPTV application traffic demands. Unlike other mobile network, VANETs have certain unique characteristic that presents several difficulties in providing an effective QoS. Similarly, IPTV requires a constant stream for QoS which at the moment is quite difficult due to the inherent VANET characteristics. To provide an effective QoS that will meet the IPTV application service demands, VANETs, must satisfy the compelling real-time traffic streaming QoS requirement (i.e., minimum bandwidth allocation, packet loss and jitter). In this report, we evaluate via simulation the feasibility of deploying quality IPTV services over VANETs, by characterizing the association between the IPTV streaming quality determining factors (i.e., throughput, delay, loss, jitter) and the IPTV quality degradation, with respect to node density and node velocity. Furthermore, we used an objective QoS metric (Media-Delivery-Index) to identify, locate and address the loss or out-of-order packet. We outline how, using these information's can support in shaping network parameters to optimize service flows. The implementation assures a priority for handling IPTV traffic, such that maximise the usage of VANETs resources, and opens the possibility that loss and delay can be minimised to a degree that could guarantee quality IPTV service delivery among vehicle in a vehicular network system.

DASH 기반 멀티미디어 스트리밍 서비스에서 사용자 체감품질 향상을 위한 비트율 적응 기법

Dynamic adaptive streaming over HTTP (DASH)는 최근 주목받고 있는 스트리밍 기술이다. DASH 클라이언트는 연속적으로 가용 네트워크 대역폭을 측정하고, 이를 기반으로 향후 다운받을 비디오 세그먼트의 비트율을 결정한다. 본 고에서는 최소 재생 버퍼 레벨을 보존하여 가변적인 네트워크 환경에서도 사용자 체감 품질 저하를 야기하는 재생 끊김 현상, 재생 중 비디오 품질의 급격한 변화 등을 효율적으로 방지하는 비트율 적응 알고리즘인 QoE-enhanced adaptation algorithm over DASH (QAAD)를 제안한다. 또한 DASH 테스트베드 상에 QAAD와 재생 버퍼를 고려한 기존의 알고리즘 (즉, QDASH[9])을 구현하여 실험적으로 성능을 비교 및 분석하였다. 네트워크 환경이 급변하는 환경에서 실험을 수행한 결과, QDASH는 재생 끊김 현상 및 비디오 화질의 잦은 변화가 발생하는 반면, QAAD는 재생 끊김 없이 안정적인 비디오 화질을 제공하는 것을 확인할 수 있었다. Dynamic adaptive streaming over HTTP (DASH) is the most recent and promising technology to support high quality streaming services. In dynamic adaptive streaming over HTTP (DASH), a client consecutively estimates the available network bandwidth and decides the transmission rate for the forthcoming video chunks to be downloaded. In this paper, we propose a novel rate adaptation algorithm called quality of experience QoE-enhanced adaptation algorithm over DASH (QAAD), which preserves the minimum buffer length to avoid interruption and minimizes the video quality changes during the playback. We implemented a DASH test bed and conducted extensive experiments. Experimental results demonstrate that under fluctuating network conditions, QAAD provides seamless streaming with stabilized video quality while the previous buffer-aware algorithm (i.e., QDASH[9]) frequently changes the video quality and undergoes the interruption.

QoS-aware data forwarding architecture for multimedia streaming services in hybrid peer-to-peer networks

In recent years, the computing paradigm changes dramatically because a wide range of computing devices are deployed rapidly. These changes of computing environment mean that the computing paradigm has been moved to the computing paradigm based on cloud & grid computing from PC oriented client/server computing paradigm. It also means that hybrid peer-to-peer network technologies have very important roles in this paradigm shift. But so far, these changing of the computing circumstances can not be provided a satisfaction in terms of quality of service, and it is also the same in the hybrid peer-to-peer networks. In particular, although the quality of service mechanism which reflects the changing of these paradigm has to be introduced to the networks, a study of QoS provisioning mechanism is yet, insufficient. In this paper, Qos-Aware Data Forwarding Architecture (QDFA) is proposed to guarantee QoS of multimedia streaming services in hybrid peer-to-peer networks. The proposed QDFA performs end-to-end synchronization processes to provide QoS of multimedia streaming services. In the synchronization processes, QDFA measures accurate time based on IEEE 1588, and sets the synchronized paths. when transmits the packet to the synchronized paths, the proposed QDFA based on the synchronized time bypasses the packet to the next hop without processing delay. The proposed QDFA guarantees multimedia streaming service quality in hybrid peer-to-peer networks through these mechanisms. To prove the excellence of the proposed QDFA, it is compared with other packet forwarding scheme through OPNET.

Numeric Analysis for Relationship-Aware Scalable Streaming Scheme

Frequent packet loss of media data is a critical problem that degrades the quality of streaming services over mobile networks. Packet loss invalidates frames containing lost packets and other related frames at the same time. Indirect loss caused by losing packets decreases the quality of streaming. A scalable streaming service can decrease the amount of dropped multimedia resulting from a single packet loss. Content providers typically divide one large media stream into several layers through a scalable streaming service and then provide each scalable layer to the user depending on the mobile network. Also, a scalable streaming service makes it possible to decode partial multimedia data depending on the relationship between frames and layers. Therefore, a scalable streaming service provides a way to decrease the wasted multimedia data when one packet is lost. However, the hierarchical structure between frames and layers of scalable streams determines the service quality of the scalable streaming service. Even if whole packets of layers are transmitted successfully, they cannot be decoded as a result of the absence of reference frames and layers. Therefore, the complicated relationship between frames and layers in a scalable stream increases the volume of abandoned layers. For providing a high-quality scalable streaming service, we choose a proper relationship between scalable layers as well as the amount of transmitted multimedia data depending on the network situation. We prove that a simple scalable scheme outperforms a complicated scheme in an error-prone network. We suggest an adaptive set-top box (AdaptiveSTB) to lower the dependency between scalable layers in a scalable stream. Also, we provide a numerical model to obtain the indirect loss of multimedia data and apply it to various multimedia streams. Our AdaptiveSTB enhances the quality of a scalable streaming service by removing indirect loss.