Multimedia Services Research Articles

User-Perceived Capacity: Theory, Computation, and Achievable Policies

User-perceived throughput is a novel performance metric attracting a considerable amount of recent attention because it characterizes the quality of the experience in mobile multimedia services. For instance, it gives a data rate of video streaming with which a user will not experience any lag or outage in watching video clips. However, its performance limit remains open. In this paper, we are interested in the achievable upper bound of user-perceived throughput, also referred to as the user-perceived capacity, and how to achieve it in typical wireless channels. We find that the user-perceived capacity is quite limited or even zero with channel state information at the receiver (CSIR) only. When both CSIR and channel state information at the transmitter (CSIT) are available, the user-perceived throughput can be substantially improved by power or even rate adaptation. A constrained Markov decision process (CMDP)-based approach is conceived to compute the user-perceived capacity with joint power–rate adaptation. It is rigorously shown that the optimal policy obeys a threshold-based rule with time, backlog, and channel gain thresholds. With power adaptation only, the user-perceived capacity is equal to the hard-delay-constrained capacity in our previous work and achieved by joint diversity and channel inversion.

MNCATM: A Multi-Layer Non-Uniform Coding-Based Adaptive Transmission Method for 360° Video

With the rapid development of multimedia services and smart devices, 360-degree video has enhanced the user viewing experience, ushering in a new era of immersive human–computer interaction. These technologies are increasingly integrating everyday life, including gaming, education, and healthcare. However, the uneven spatiotemporal distribution of wireless resources presents significant challenges for the transmission of ultra-high-definition 360-degree video streaming. To address this issue, this paper proposes a multi-layer non-uniform coding-based adaptive transmission method for 360° video (MNCATM). This method optimizes video caching and transmission by dividing non-uniform tiles and leveraging users’ dynamic field of view (FoV) information and the multi-bitrate characteristics of video content. First, the video transmission process is formalized and modeled, and an adaptive transmission optimization framework for a non-uniform video is proposed. Based on this, the optimization problem required by the paper is summarized, and an algorithm is proposed to solve the problem. Simulation experiments demonstrate that the proposed method, MNCATM, outperforms existing transmission schemes in terms of bandwidth utilization and user quality of experience (QoE). MNCATM can effectively utilize network bandwidth, reduce latency, improve transmission efficiency, and maximize user experience quality.

MDC2: An Integrated Communication and Computing Framework to Optimize Edge-Assisted Caching for Improved Multimedia Services in UAV-Based IoT Networks

MDC²: An Integrated Communication and Computing Framework to Optimize Edge-Assisted Caching for Improved Multimedia Services in UAV-Based IoT Networks

W-band photonic-aided reconfigurable multichannel vector mm-wave transmission enabled by the digital subcarrier multiplexing technique.

As multimedia service demands rise, radio-over-fiber (RoF) systems necessitate a flexible wireless resource allocation in multi-user scenarios. Optical wavelength division multiplexing (WDM) can meet multi-user application scenarios but has the problems of high hardware cost and complexity. In this Letter, we propose a photonic-aided reconfigurable multichannel vector millimeter-wave (mm-wave) transmission scheme in the RoF system enabled by the digital subcarrier multiplexing (DSCM) technique. The scheme can flexibly adjust the number and frequency spacing of subcarriers as well as the bandwidth and modulation format allocated to each subcarrier, and it can be applied to multi-user scenarios without increasing the cost and complexity of hardware implementation. The off-line experiments verify the system transmission performance with different numbers, bandwidth, and frequency spacing of subcarriers, fully verifying the feasibility of the scheme. Furthermore, the Letter delves into the effects of the subcarrier number, bandwidth, and frequency spacing on overall system performance, highlighting the potential of this scheme for flexible and cost-effective wireless resource allocation in RoF systems.

Simplifying IP multimedia systems by introducing next-generation networks with scalable architectures

The IP Multimedia Subsystem (IMS) is essential to providing multimedia services over IP networks. However, maintaining its scalability in the face of increasing demand and changing next-generation networks is still a significant concern. In light of growing loads and service diversity, scalable solutions are required, as this article explores the shortcomings of the IMS designs in use today. To present an innovative, scalable architecture for IMS that integrates cutting-edge computer science techniques, enabling effective service delivery in next-generation networks. By bridging the gap between the static nature of previous IMS designs and the dynamic demands of contemporary telecommunications, this article hopes to deliver results. A mixed-method approach was utilized, integrating evaluations of architectural flexibility with network loads and service needs analysis. In order to evaluate the suggested designs' performance to current benchmarks, the study used simulations to predict the architectures' performance under various scenarios. Compared to conventional IMS frameworks, the suggested design showed outstanding scalability, enabling a tenfold increase in simultaneous connections and services. It notably improved fault tolerance and service delay and increased flexibility for network modifications and service diversification. Next-generation network demands are met by IMS designs that use modern computer science methodologies to improve scalability and flexibility significantly. More practical, scalable, and reliable service delivery methods will be possible thanks to the foundation our work creates for future research into dynamic, resilient telecommunications infrastructures.

Multimodal Recommender Systems: A Survey

The recommender system (RS) has been an integral toolkit of online services. They are equipped with various deep learning techniques to model user preference based on identifier and attribute information. With the emergence of multimedia services, such as short videos, news and etc. , understanding these contents while recommending becomes critical. Besides, multimodal features are also helpful in alleviating the problem of data sparsity in RS. Thus, M ultimodal R ecommender S ystem (MRS) has attracted much attention from both academia and industry recently. In this paper, we will give a comprehensive survey of the MRS models, mainly from technical views. First, we conclude the general procedures and major challenges for MRS. Then, we introduce the existing MRS models according to four categories, i.e., Modality Encoder , Feature Interaction , Feature Enhancement and Model Optimization . Besides, to make it convenient for those who want to research this field, we also summarize the dataset and code resources. Finally, we discuss some promising future directions of MRS and conclude this paper. To access more details of the surveyed papers, such as implementation code, we open source a repository.

Channel Allocation in mobile multimedia network using artificial neural networks

Capital asset control systems may enhance network performance, reduce congestion, and optimise resource allocation with the use of artificial intelligence. Using machine learning models like decision trees and neural networks allows for more informed and adaptive admission control options. These models can precisely predict how the network's quality of service (QoS) will be affected by accepting a new call. Exploring AI-enhanced CAC schemes requires a thorough analysis of various machine learning methods and their potential applications to real-time network management. To ensure that AI-based CAC implementations are actually possible in resource-limited mobile situations, it is crucial to consider their computational complexity and resource requirements. Accuracy and computational efficiency are two competing goals, and this study examines both. Finding a happy medium that can meet the stringent requirements of mobile multimedia networks is the driving force behind this research. Also covered in this study is the possibility of mixing AI-powered CAC with cutting-edge tech like 5G networks and cloud computing. Collectively, these technology and artificial intelligence (AI) have to open up new opportunities for situationally-conscious, dynamic admission manipulate. As a result, mobile multimedia networks might be a lot more efficient and adaptable. An exploration of CAC schemes is provided in this article, which draws attention to the potential game-changing impact of AI-based methods for mobile multimedia network optimisation. The increasing demand for multimedia services is creating new challenges, yet these challenges may be amenable to artificial intelligence integration into CAC systems. More adaptive and intelligent network management solutions would be possible as a result.

IMPLEMENTASI APLIKASI MULTIMEDIA DAN PENGOLAHAN DATA LAYANAN PADA KANTOR URUSAN AGAMA KECAMATAN PASAR JAMBI

Pasar Jambi District Religious Affairs Office, Jambi City, Jambi Province. The function of the Pasar Jambi District Religious Affairs Office is to carry out marriage registration, reconciliation, mosque construction, zakat, endowments and other social services. This research is to build a Multimedia Application Service for the Pasar Jambi District Religious Affairs Office. The Service Multimedia Application is a comprehensive overview of marriage registration which includes information, registration, announcements, services, facilities and infrastructure as a back-up for the Pasar District KUA Service Multimedia Application. Therefore, profile and service data must be available, complete and accountable. Through thesis activities, Nurdin Hamzah University tried to create a multimedia service application at KUA Pasar which is located in Jambi Province in an effort to create a Multimedia Application for Wedding Services at KUA Pasar Jambi. Based on the identification of the problem, therefore, the objectives of this thesis research activity are: 1) create a profile of the KUA Pasar and 2) a Multimedia Application for Wedding Services that can be accessed computerized and programmed using the Visual Studio Code programming language, MySQL database, XAMPP, Capcut and Medibang Paint. The requirements for the KUA Service Multimedia Application System are: 1) The input required in creating the system is service video data, 2) The processes required for creating the system are the main page process, the history page process, the structure page process, and the vision and mission page process and 3) The output required is a video of KUA services.

QoIoTX: A QoE-Aware IoT Service Discovery Framework

Quality of Experience QoE is a research area that evaluates performance based on subjective and objective metrics for the use of a product or a service. Currently, the substantial majority of QoE works mainly focus on multimedia services. However, the introduction of Internet of Things IoT has brought a new level of complexity into the field of QoE evaluation. With the evolution of new IoT technologies such as machine to machine communication and artificial intelligence, utilizing additional evaluation factors alongside the traditional ones is a crucial demand. This paper proposes QoIoTX, a QoE-based service discovery framework that can be utilized to evaluate the QoE of IoT service/application on the fly considering multiple parameters about data, network, users, and services. It extends the conventional QoE and goes beyond its legacy evaluation phases. Also, provides a novel alternative approach to evaluate the IoT services subjectively rather than using the traditional approaches that do not cope with the rapidly evolving services. Although each of the identified QoE factors is measured on a different scale and may involve different units of measurement, the proposed work can effectively evaluate the QoE through providing a single value that represents the acceptability degree of each service.

Assessing the quality of experience in wireless networks for multimedia applications: A comprehensive analysis utilizing deep learning-based techniques

In the context of the burgeoning progression of wireless network technology and the corresponding escalation in the demand for mobile Internet-based multimedia transmission services, the task of preserving and augmenting user satisfaction has emerged as an imperative concern. This necessitates a sophisticated and accurate evaluation of multimedia service quality within the sphere of wireless networks. To systematically address the nuanced issue of user experience quality, the present study introduces a novel method for evaluating multimedia Quality of Experience (QoE) in wireless networks, employing an advanced deep learning model as the underlying analytical framework. Initially, the research undertakes the task of modeling the video session process, giving due consideration to the status of each temporal interval within the session's architecture. Subsequently, the challenge of QoE prediction is dissected and investigated through the lens of recurrent neural networks (RNNs), culminating in the proposition of an all-encompassing QoE prediction model that harmoniously integrates video information, Quality of Service (QoS) data, user behavior analytics, and facial expression analysis. The empirical segment of this research serves to validate the efficacy of the suggested video QoE evaluation method, engaging both quantitative and qualitative comparison metrics with contemporaneous state-of-the-art QoE models, employing the RTVCQoE dataset as the empirical foundation. The experimental findings illuminate that the QoE model elucidated in this study transcends competing models in performance metrics such as PLCC, SRCC, and KRCC. Consequently, this investigation stands as a seminal contribution to academic literature, furnishing an exacting and dependable QoE evaluation methodology. Such a contribution augments the user experience landscape in multimedia services within wireless networks, and instigates further scholarly exploration and technological innovation in the mobile Internet domain.

Edge caching and computing of video chunks in multi-tier wireless networks

This paper proposes a video caching and transcoding strategy for delay-constrained content delivery in multi-tier wireless networks. Particularly for multimedia services whose content can be encoded into multiple quality versions and consists of multiple chunks, we present an approach of caching chunks of an identical file separately in different network layers with different qualities. Given this caching policy, a complete file can be retrieved by receiving its chunks from different network tiers; therefore, a video transcoding and delivery method is jointly designed with caching to maximize the expected content quality with a strict delay constraint. Motivated by that caching is proactively conducted in advance of many user requests, the joint optimization problem is decomposed into caching and transcoding subproblems. The optimal transcoding policy and its transcoded qualities at different network tiers are analytically found by linear programming for a given cache state. Using the closed-form transcoded qualities, the caching policy is optimized to maximize the expected content quality with respect to randomness of user locations and channel gains. Due to the difficulty of expectation, the caching policy of each network layer is independently obtained by water-filling first, and an alternating optimization method is used to find the joint optimal caching policy satisfying the cache size constraints. Simulation results show that the proposed scheme succeeds in delivering content of 5% to 10% higher expected quality to users than comparison schemes which do not use partitioning for caching. Simultaneously, our approach meets the delay requirement and effectively manages the trade-offs arising from the varying storage and computational capacities within hierarchies, as well as video diversity.

Mobile phone text messaging for medication adherence in secondary prevention of cardiovascular disease.

Mobile phone text messaging for medication adherence in secondary prevention of cardiovascular disease.

Network Ideological and Political Education System for College Students Based on Multimedia Service Architecture

Today, the network society has become an integral part of human society, and the network life marked by digitization, informatization and networking has become a new state of existence; a new society marked by interactivity, virtuality and innovation A mode of operation has been created. A network, in simple terms, is to connect, and can be called a computer network. Such highest degree of social informatization in my country. It is a new idea designed by making full use of computer networks, multimedia technology and modern communication technology and closely combining the cognitive hotspots of contemporary college students. way of political education. In response to the above problems, this article uses deep learning technology to develop an intelligent education system based on detection technology. The system takes identifying whether the standard is met as the main goal, and gives comprehensive evaluation and improvement suggestions for the quality of action completion. It gets rid of the constraints of the venue.

Novel Resource Allocation Technique for DVB-RCS Compliant Satellite Terminals

Satellite communication is advantageous for several reasons such as broad coverage, small installation time of remote user sites, and network services in inhospitable terrains, where installing terrestrial infrastructure is costly. With the advent of broadband multimedia satellites such as Ku and Ka band satellites, multimedia services to the satellite terminals are gaining momentum. Digital Video Broadcast Return Channel via Satellite (DVB-RCS) is an open standard developed by ETSI which has further standardized, commercialized and solved the problem of inter-operability of Ku Band satellite terminals. Satellite bandwidth is scarce therefore treated as precious resource. In the present paper, authors aim to develop and realize the resource allocation techniques in return link channel for DVB-RCS compliant satellite terminals. The paper provides method for giving preference to real time application in terms of early processing of allocation request generated against the real time traffic to reduce delay and also provides method to avoid parallel connection arises due to transmission of terminal on more than one frequency at a time. Authors have realised DVB-RCS resource allocation technique and have given simulation results.

Cloud media video encoding: review and challenges

AbstractIn recent years, Internet traffic patterns have been changing. Most of the traffic demand by end users is multimedia, in particular, video streaming accounts for over 53%. This demand has led to improved network infrastructures and computing architectures to meet the challenges of delivering these multimedia services while maintaining an adequate quality of experience. Focusing on the preparation and adequacy of multimedia content for broadcasting, Cloud and Edge Computing infrastructures have been and will be crucial to offer high and ultra-high definition multimedia content in live, real-time, or video-on-demand scenarios. For these reasons, this review paper presents a detailed study of research papers related to encoding and transcoding techniques in cloud computing environments. It begins by discussing the evolution of streaming and the importance of the encoding process, with a focus on the latest streaming methods and codecs. Then, it examines the role of cloud systems in multimedia environments and provides details on the cloud infrastructure for media scenarios. After doing a systematic literature review, we have been able to find 49 valid papers that meet the requirements specified in the research questions. Each paper has been analyzed and classified according to several criteria, besides to inspect their relevance. To conclude this review, we have identified and elaborated on several challenges and open research issues associated with the development of video codecs optimized for diverse factors within both cloud and edge architectures. Additionally, we have discussed emerging challenges in designing new cloud/edge architectures aimed at more efficient delivery of media traffic. This involves investigating ways to improve the overall performance, reliability, and resource utilization of architectures that support the transmission of multimedia content over both cloud and edge computing environments ensuring a good quality of experience for the final user.

Immersive Multimedia Service Caching in Edge Cloud with Renewable Energy

Immersive service caching, based on the intelligent edge cloud, can meet delay-sensitive service requirements. Although numerous service caching solutions for edge clouds have been designed, they have not been well explored. Moreover, to the best of our knowledge, there is no work to consider the immersive service caching scheme under the supply of renewable energy. In this article, we investigate the service caching problem under the renewable energy supply to minimize service latency while making full use of renewable energy. Specifically, we formulate the service caching and renewable energy harvesting problem, which considers the dynamic renewable energy, unknown service requests, and limited capacity of the edge cloud. To solve this problem, we propose an effective algorithm, called OSCRE. Our algorithm first uses Lyapunov optimization to convert the time-average problem into time-independence optimization and thus realizes optimal renewable energy harvesting. Then, it realizes the service caching scheme using data-driven combinatorial multi-armed bandit learning. The simulation results show that the OSCRE scheme can save service latency while making sufficient use of renewable energy.

Performance Comparison of VVC, AV1, HEVC, and AVC for High Resolutions

Over the years, there has been growing interest in multimedia services, especially in the video domain, where firms and subscribers require higher resolutions, framerates, and sampling precision. This results in a huge amount of data that needs to be processed, stored, and transmitted. As a result, researchers face the challenge of developing new compression standards that can reduce the amount of data while maintaining the same quality. In this paper, the compression performance of the latest and most commonly used video codecs, namely H.266/VVC, AV1, H265/HEVC, and H.264/AVC was examined. The test set included seven sequences of various content at 8K, Ultra HD (UHD), and Full HD (FHD) resolutions, encoded to bitrates ranging from 1 to 15 Mbps for FHD and UHD resolutions and from 5 to 50 Mbps for 8K resolution. Objective quality metrics, such as peak signal-to-noise ratio (PSNR), the structural similarity index (SSIM), and video multi-method assessment fusion (VMAF) were used to measure codec performance. The results showed that H.266/VVC outperformed all other codecs, namely H.264/AVC, H.265/HEVC, and AV1, in terms of the Bjøntegaard delta (BD) model. The average bitrate savings were approximately 78% for H.266/VVC, 63% for AV1, and 53% for H.265/HEVC relative to H.264/AVC, 59% for H.266/VVC and 22% for AV1 compared to H.264/AVC, and 46% for H.266/VVC relative to AV1 (all for 8K resolution). The results also showed that codec performance varied depending on resolution, with higher resolutions showing greater efficiency for newly developed codecs, such as H.266/VVC and AV1. This confirms the fact that the H.266/VVC and AV1 codecs were primarily developed for videos at high resolutions, such as 8K and/or UHD.

A Prediction-Based Traffic Scheduling Framework for Multimedia Services in Dynamic Networks

A Prediction-Based Traffic Scheduling Framework for Multimedia Services in Dynamic Networks

A method to increase video streaming speed and efficiency of storage video using multithreading and Random Access Memory

There are numerous vital applications for online video storage and network transmission today. With exceptional scalability and browser and device compatibility, Hypertext Transfer Protocol (HTTP) live streaming (HLS) is today's most popular video and audio transmission protocol. In the article, the authors proposed a method of using multithreading and Random Access Memory (RAM) to store and transmit videos to help the server achieve higher speed, improve video transmission speed and video storage efficiency. The results of this research will help multimedia server developers evaluate the appropriate balance of resource usage while still ensuring the quality of online video transmission with a large number of videos and viewers.

Using QoE Metric as a Decision Criterion in Multimedia Heterogeneous Network Optimization: Challenges and Research Perspectives

This article explores the growing importance of the QoE (Quality of Experience) metric as a fundamental criterion in the optimization of heterogeneous multimedia networks. We explore the benefits of using QoE, such as improving user experience, efficient resource management, and adaptation to network conditions. However, this paradigm presents technical challenges, including accurately measuring QoE and managing the complexity of heterogeneous networks. To address these challenges, we highlight promising research prospects, such as the development of advanced algorithms, real-time measurement of QoE, and the integration of machine learning. Ultimately, the use of QoE in the optimization of heterogeneous multimedia networks contributes to a substantial improvement in the quality of multimedia services offered to end users.