Multimedia Streaming Services Research Articles

An efficient software defined network controller based routing adaptation for enhancing QoE of multimedia streaming service

An efficient software defined network controller based routing adaptation for enhancing QoE of multimedia streaming service

Design of a 5G Multimedia Broadcast Application Function Supporting Adaptive Error Recovery

The demand for mobile multimedia streaming services has been steadily growing in recent years. Mobile multimedia broadcasting addresses the shortage of radio resources but introduces a network error recovery problem. Retransmitting multimedia segments that are not correctly broadcast can cause service disruptions and increased service latency, affecting the quality of experience perceived by end users. With the advent of networking paradigms based on virtualization technologies, mobile networks have been enabled with more flexibility and agility to deploy innovative services that improve the utilization of available network resources. This paper discusses how mobile multimedia broadcast services can be designed to prevent service degradation by using the computing capabilities provided by multiaccess edge computing (MEC) platforms in the context of a 5G network architecture. An experimental platform has been developed to evaluate the feasibility of a MEC application to provide adaptive error recovery for multimedia broadcast services. The results of the experiments carried out show that the proposal provides a flexible mechanism that can be deployed at the network edge to lower the impact of transmission errors on latency and service disruptions.

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

D2D-assisted user-centric adaptive video transmission in next generation cellular networks

Next-generation cellular networks need to provide seamless connectivity with higher data rates, increased capacity, and enhanced network coverage. As multimedia service demands in various heterogeneous devices grow rapidly compared to the underlying network’s capacity and bandwidth, the adaptation in multimedia streaming services is essential for providing satisfactory Quality of Experience (QoE). This paper develops a Device-to-Device (D2D)-assisted Utility-based Adaptive Multimedia (video) Streaming scheme (UAMS) using D2D communication in a 5th Generation (5G) cellular network where low-battery users may extend their streaming duration by spending lower reception energy with the help of D2D-assisted communication. The adaptation algorithm considers four utility functions: quality, power consumption, packet error ratio, and remaining battery of the user devices to adapt the bitrate dynamically and augment viewers’ experience. We formulate an optimization problem to maximize the joint utility function to provide the best adaptive multimedia content selected for transmission to the end-users either directly or via D2D Relay Nodes (DRNs) in every scheduling interval. We use a graph theoretic approach for choosing the best DRNs. Extensive simulations show the efficacy of the proposed scheme in terms of saved battery energy, churn rate, and QoE metrics compared to a few well-known existing schemes in the literature that do not use D2D communication.

Editors’ Note

Editorial| September 01 2022 Editors’ Note Journal of Popular Music Studies (2022) 34 (3): 1–5. https://doi.org/10.1525/jpms.2022.34.3.1 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn MailTo Guest Access Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Editors’ Note. Journal of Popular Music Studies 1 September 2022; 34 (3): 1–5. doi: https://doi.org/10.1525/jpms.2022.34.3.1 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentJournal of Popular Music Studies Search As we write this Editors’ Note, global multimedia streaming service Netflix has just laid off approximately 150 employees, including a significant number of people working for the company’s social media and editorial platforms geared toward diversity—specifically, the channels Most, which centers LGBTQ+ stories; Golden, which promotes content related to the “pan-Asian diaspora;” the Latinx community-focused Con Todo; and the Black-audience-oriented Strong Black Lead. These firings also come on the heels of Netflix’s letting go of several women of color writers at its fandom subsidiary, Tudum. All of this is, of course, occurring as Netflix continues to produce transphobic content while still publicly declaring a commitment to “diversity.” For us (and for many), these events tap into a much broader set of sociopolitical concerns facing our contemporary world, namely the racialized/gendered/sexualized dynamics of labor and tech, the politics of representation, and the neoliberal logics of diversity and inclusion. We, thus, open... You do not currently have access to this content.

SDN and NFV for QoE-driven multimedia services delivery: The road towards 6G and beyond networks

The concept for developing the future mobile communication systems has been explored in recent years with a vision towards 5G and 6G systems. Meeting performance targets such as higher data rate transmission, lower end-to-end latency, higher capacity, lower cost, and satisfied Quality of Experience (QoE) for delivered services is the key for the success of 5G and 6G networks. Within these performance targets and associated enabling technologies, QoE and the overall management of multimedia services is the one which has been less well addressed for 5G in the past. This paper provides a comprehensive and ground-breaking discussion regarding QoE management in the context of future softwarized 5G/6G networks. We introduce a generalized QoE provisioning ecosystem for emerging multimedia streaming services in softwarized 5G/6G and beyond networks. We explore potential network softwarization and communication technologies that will enable the end-user’s QoE in 5G/6G. We further provide promising use case scenarios regarding (a) QoE-driven management of multimedia services over multi-access cloud/edge softwarized and virtualized 5G networks, (b) QoE monitoring for large traffic variations in business, residential and public areas in 5G networks, along with a Machine Learning (ML)-based softwarized controller for QoE provisioning over 5G/6G networks. We build on the achievements of 5G networks to provide the roadmap towards the development of 6G and beyond networks in terms of requirements, use case scenarios and service classes. We also present potential technologies that will be dominant through 2025–2030 in shaping the vision of 6G and beyond networks including (a) self-driving 3D network architecture, (b) network management, automation and orchestration, and (c) pervasive artificial intelligence. Moreover, we provide challenges and research directions in 6G and beyond wireless communication systems. The paper provides the first roadmap towards the management, orchestration and monitoring of multimedia 3D services in 6G and beyond networks. The comprehensive goal of this paper is to encourage researchers from the industry and academia to work together towards the realization of softwarized 6G and beyond networks while tackling the critical research challenges regarding the management of emerging 3D multimedia services and applications. The comments made by the authors in this paper are expectations on 6G, and the standardization of 6G where these aspects will be decided in 6G networks and beyond, will be started soon by different standardization bodies and fora.

Content Delivery Scheme Based on Network Selection for Power Saving

In this study, we present content delivery scheme based on network selection for power saving. There are two main communication technologies such as Wi-Fi and mobile telecommunication (4G, 5G) in smartphones. Power consumption is one of the important factors in smartphones. Wi-Fi network consumes low power compared to mobile telecommunication in multimedia streaming. The proposed scheme transmits the multimedia content data first when the Wi-Fi signal is strong. In this manner, it can reduce the energy consumption of a smartphone. Therefore, the proposed content delivery scheme is expected to be useful for providing multimedia streaming services with low-power consumption.

Novel Architecture of Content Delivery Network Based on Big Data for Power Saving

This paper proposes an architecture of content delivery network (CDN) based on big data for power saving. There are two types of video content: hot content and cold content. When video content is accessed frequently, it is called hot content. Conversely, when video content is accessed infrequently, it is called cold content. In CDN, there is an origin server and a CDN cache server. A CDN cache server has a replicated content and provides its content to the end users nearby. Therefore, the user can receive the requested content from the closest proximity for fast content. The proposed architecture in this paper powers off the cold content server in CDN cache server when the number of cold content requests decreases. Hence, the proposed architecture for content delivery services based on power saving is expected to be useful for providing multimedia streaming services with low power consumption for content providers.

Location-proximity-based clustering method for peer-to-peer multimedia streaming services with multiple sources.

Social distancing to reduce the spread of coronavirus disease 2019 (COVID-19) made a huge increase in the global OTT market, and OTT service providers get millions of new subscribers. Recently OTT service providers are extending their service to video broadcasting. As a one type of video broadcasting, this paper covers multimedia streaming with multiple sources. Multimedia streaming with multiple sources has multiple sources, and receivers can select one specific source to watch the video from the source. Sources include cameras capturing different angles of same event or location, cameras in geographical locations, etc. For delivering video to rapidly increasing number of users, multimedia streaming with multiple sources system needs efficient and scalable delivery method. Tree-based Peer-to-peer (P2P) networking has been investigated as the delivery solution of multimedia streaming with multiple sources, and set-top boxes or mobile apps of OTT service can be used as peers connecting the subscriber of OTT service. However, the scalability of the tree-based P2P networking is limited by the out-degree of a tree that branches linearly with the number of users. Hence, this study proposes clustering peers based on the location proximity of the peers to enhance the scalability of the P2P multimedia streaming with multiple sources. By clustering peers, one or more peers can be grouped into a virtual peer with an aggregated uplink/downlink capacity. This paper describes P2P multimedia streaming with multiple sources and algorithms for the proposed clustering method. Two applications which are one-view multiparty video conferencing and multi-view video streaming are introduced, and considerations for applying the proposed method to the applications are also discussed. The experimental results show that location-proximity-based clustering is effective in achieving a scalable P2P multimedia streaming with multiple sources by reducing the out-degree of a tree for the introduced applications. The proposed clustering leads improvement in the maximum achievable video bit rate, the average viewing video bit rate, and perceived delay.

The MBSFN-based eMBMS using the method of Incremental Allocation of Radio Resource between Unicast and Multicast (IARR-UM)

The evolved Multimedia Broadcast Multicast Service (eMBMS) using the Multicast Broadcast Single Frequency Network (MBSFN) technique was designed for having multimedia streaming services using the multicast/broadcast way over the cellular network. Since (1) the unit of resource allocation in eMBMS-MBSFN is a subframe, (2) the code rate of an eMBMS-MBSFN session is based on the lowest Modulation and Coding Scheme (MCS) among involved User Equipments (UEs) of the eMBMS-MBSFN session and (3) the resource allocation for eMBMS-MBSFN cannot be so instantly and dynamically adjusted based on the status of involved UEs, triggering eMBMS-MBSFN in the inappropriate time and allocating inappropriate resource to eMBMS, for which a framework of how to set the configuration of the allocated resource for eMBMS-MBSFN has been defined in the standard, may cause (1) the radio resources to be wasted and (2) the low streaming quality and code rate. Based on the MBMS operation on Demand (MooD) concept, this work proposed the Incremental Allocation of Radio Resource between Unicast and Multicast (IARR-UM) method to dynamically allocate radio resources to eMBMS based on the current Radio Access Network’s (RAN’s) congestion situation such that some suitable multimedia streaming services are switched to eMBMS and others still use unicast communication. To effectively use eMBMS to mitigate RAN’s congestion, the proposed IARR-UM method (1) dynamically increases/decreases the amount of radio resources allocated to eMBMS, i.e., modifying the configuration of the allocated resource for eMBMS-MBSFN using the standard’s framework, based on the situation of RAN’s congestion, (2) uses the Knapsack algorithm to select a subset of suitable multimedia streaming services to be eMBMS sessions according to the given amount of radio resources allocated to eMBMS, and then (3) design a Common Subframe Allocation (CSA) pattern that can have the lower amount of redundant radio resources allocated to eMBMS. The results of the performance evaluation shown that the proposed method can (1) provide UEs with appropriate radio resources and (2), although the throughput may be reduced in some cases, effectively reduce (increase) the UEs’ invalid packet rates (data rates), especially in the higher density of UEs’ situation.

Design and Implementation of the Evaluation Framework for Decentralized Multimedia Streaming Services

Design and Implementation of the Evaluation Framework for Decentralized Multimedia Streaming Services

A Business Processes Model for the Integration of Over-The-Top Platforms in Communications Service Providers Operations

The problem between Over-the-Top (OTT) and Communications Service Provider (CSP), namely for multimedia streaming services, is not new and has been a topic much discussed in the TM Forum. At time of writing, a technical solution that would benefit both parties has not yet been presented. With the existing model (no operational integration), both OTTs and CSPs are dissatisfied. This paper proposes a technical solution that can be beneficial to both parties and can potentially solve the existing conflicts. The solution presents the high-level design of Business Processes to integrate OTT Service Platforms in CSP Operations. Some hypothetical, but close to reality scenarios were defined in order to show how the model could be applied. The design of the model incorporates information and suggestions collected from Portuguese CSPs. To evaluate the accuracy of the design methodology, a set of interviews were conducted with industry experts in the sector, who evaluated each process model of the solution. A set of surveys from end users of those types of services was also conducted, in order to understand their opinions about the ideas used for the construction of the model.

Intense: In-Depth Studies on Stall Events and Quality Switches and Their Impact on the Quality of Experience in HTTP Adaptive Streaming

With the recent growth of multimedia traffic over the Internet and emerging multimedia streaming service providers, improving Quality of Experience (QoE) for HTTP Adaptive Streaming (HAS) becomes more important. Alongside other factors, such as the media quality, HAS relies on the performance of the media player’s Adaptive Bitrate (ABR) algorithm to optimize QoE in multimedia streaming sessions. QoE in HAS suffers from weak or unstable internet connections and suboptimal ABR decisions. As a result of imperfect adaptiveness to the characteristics and conditions of the internet connection, stall events and quality level switches could occur and with different durations that negatively affect the QoE. In this paper, we address various identified open issues related to the QoE for HAS, notably (i) the minimum noticeable duration for stall events in HAS; (ii) the correlation between the media quality and the impact of stall events on QoE; (iii) the end-user preference regarding multiple shorter stall events versus a single longer stall event; and (iv) the end-user preference of media quality switches over stall events. Therefore, we have studied these open issues from both objective and subjective evaluation perspectives and presented the correlation between the two types of evaluations. The findings documented in this paper can be used as a baseline for improving ABR algorithms and policies in HAS.

QoEMultiSDN: Management of Multimedia Services using MPTCP/SR in Softwarized and Virtualized Networks

5G networks are set to empower new user experiences for multimedia streaming services by offering high data rates and low latency. The rapid growth of multimedia services, such as video streaming services over future softwarized 5G networks, poses great challenges for both service providers and network operators regarding service provisioning with high Quality of Experience (QoE). Network evolution towards Software Defined Networking (SDN) and Network Function Virtualization (NFV) provides new opportunities to develop innovative ways to address the challenges. In this paper, we present a novel QoE-aware management scheme based on SDN/NFV by utilizing Multi-Path-TCP/Segment-Routing (MPTCP/SR) techniques and exploring information from both the network and client. The new scheme, entitled QoEMultiSDN, provides an optimized end-to-end QoE for multimedia service delivery. QoEMultiSDN employs two novel strategies to achieve this: (a) QoE-based multisource routing and QoE optimization, and (b) multipath protection and dynamic link-failure-free mechanisms. We implemented the proposed scheme over SDN through Dynamic Adaptive Streaming over HTTP (DASH) experiments using Mininet, POX and OpenDaylight controllers, and compared its performance with MPTCP and regular TCP. Experimental results indicate that the QoEMultiSDN outperforms others in terms of system throughput, failure recovery time and the QoE of the end-user.

A Security Analysis on OpenSIPS

IP Telephony, Internet Telephony, Digital Phone or often also called VoIP (Voice Over Internet Protocol) is a technology that allows long-distance voice conversations with the Internet. The increasing number of VoIP users and other IP-based multimedia streaming services naturally raises security issues. Many users are likely to lose their privacy in communication. To overcome this security problem a security system must be implemented. Implementing a security system will use VPN Gateway using SSL and TLS encryption on the VoIP server. The VPN Gateway method is used to build a private network so that only certain users can use the private network. The TLS method is used to secure a user signaling session to the server. From the test results obtained that the VoIP server that uses VPN Gateway and TLS on the server can overcome the attacks e.g., eavesdropping, attacking authentication, teardown session, and denial of service.

On Leveraging Machine and Deep Learning for Throughput Prediction in Cellular Networks: Design, Performance, and Challenges

The highly dynamic wireless communication environment poses a challenge for many applications (e.g., adaptive multimedia streaming services). Providing accurate TP can significantly improve performance of these applications. The scheduling algorithms in cellular networks consider various PHY metrics, (e.g., CQI) and throughput history when assigning resources for each user. This article explains how AI can be leveraged for accurate TP in cellular networks using PHY and application layer metrics. We present key architectural components and implementation options, illustrating their advantages and limitations. We also highlight key design choices and investigate their impact on prediction accuracy using real data. We believe this is the first study that examines the impact of integrating network-level data and applying a deep learning technique (on PHY and application data) for TP in cellular systems. Using video streaming as a use case, we illustrate how accurate TP improves the end user's QoE. Furthermore, we identify open questions and research challenges in the area of AI-driven TP. Finally, we report on lessons learned and provide conclusions that we believe will be useful to network practitioners seeking to apply AI.

HDA Video Transmission Scheme for DASH

In recent years, with the development of Internet communication technology, more and more people tend to get information through the network. And people prefer multimedia video streaming services. Traditional streaming media technology cannot meet people's needs because of its limitations. Recently, HTTP-based Dynamic Adaptive Streaming Over HTTP (DASH) has emerged as a new approach. In this paper, we consider two hybrid digital and analog video transmission schemes for DASH and propose three methods of enhancing the video quality of experience (QoE) of DASH users. First of all, considering the importance of data to video quality, we propose an energy-aware recombination method of reorganizing and packaging data and define the priority of the generated DASH layer in transmission. Second, we design an adaptive bitrate allocation algorithm to improve bandwidth utilization and video quality. Finally, we propose a retransmission mechanism to address the situation in which the digital stream at the receiving end cannot be decoded due to channel distance errors. Experiments show that our two schemes are superior to traditional DASH schemes.

Quality of Experience for Streaming Services: Measurements, Challenges and Insights

Over the last few years, the evolution of network and user handsets’ technologies, have challenged the telecom industry and the Internet ecosystem. Especially, the unprecedented progress of multimedia streaming services like YouTube, Vimeo and DailyMotion resulted in an impressive demand growth and a significant need of Quality of Service (QoS) (e.g., high data rate, low latency/jitter, etc.). Mainly, numerous difficulties are to be considered while delivering a specific service, such as a strict QoS, human-centric features, massive number of devices, heterogeneous devices and networks, and uncontrollable environments. Thenceforth, the concept of Quality of Experience (QoE) is gaining visibility, and tremendous research efforts have been spent on improving and/or delivering reliable and added-value services, at a high user experience. In this paper, we present the importance of QoE in wireless and mobile networks (4G, 5G, and beyond), by providing standard definitions and the most important measurement methods developed. Moreover, we exhibit notable enhancements and controlling approaches proposed by researchers to meet the user expectation in terms of service experience.

QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey

We provide in this paper a tutorial and a comprehensive survey of QoE management solutions in current and future networks. We start with a high level description of QoE management for multimedia services, which integrates QoE modelling, monitoring, and optimization. This followed by a discussion of HTTP Adaptive Streaming (HAS) solutions as the dominant technique for streaming videos over the best-effort Internet. We then summarize the key elements in SDN/NFV along with an overview of ongoing research projects, standardization activities and use cases related to SDN, NFV, and other emerging applications. We provide a survey of the state-of-the-art of QoE management techniques categorized into three different groups: a) QoE-aware/driven strategies using SDN and/or NFV; b) QoE-aware/driven approaches for adaptive streaming over emerging architectures such as multi-access edge computing, cloud/fog computing, and information-centric networking; and c) extended QoE management approaches in new domains such as immersive augmented and virtual reality, mulsemedia and video gaming applications. Based on the review, we present a list of identified future QoE management challenges regarding emerging multimedia applications, network management and orchestration, network slicing and collaborative service management in softwarized networks. Finally, we provide a discussion on future research directions with a focus on emerging research areas in QoE management, such as QoE-oriented business models, QoE-based big data strategies, and scalability issues in QoE optimization.

Pengukuran Performa Algoritma Kendali Kongesti Active Queue Manajemen (AQM) Pada Jaringan Backbone Multicast Berbasis Protocol Multicast PIM-DM

UDP is a data transmission protocol on the Internet that allows data to be sent in realtime and become a development base of various services such as IPTV, VOIP, VOD, and video conferencing. The multicast network was a solution to provide better service to many public needs with the concept of simplicity and efficiency. Dense traffic situation triggering a packet loss and delay that not tolerated by some services, especially multimedia streaming service, while UDP does not guarantee the quality of service so that the necessary traffic management method that serves as a traffic controller to the congestion in the network. This study analyzes the performance of technology based on Active Queue Management (AQM) congestion control in a multicast backbone network based on Protocol Independent Multicast – Dense Multicast using Droptail, Deficit Round Robin (DRR), and Random Early Detection (RED) algorithm, which is simulated using NS2. The simulation results show that the congestion control algorithm, DRR provides the best performance with a balanced value of mean delay, mean throughput, and the mean loss. RED is a congestion control algorithm which has the best queue management mechanism but not able to suppress the mean loss in each scenario tested because RED has a small amount of buffer size, Droptail not an appropriate algorithm for multicast networks implemented in, the absence of an interrupt mechanism trigger data services will have a tendency towards a particular data packet.