Multimedia Services In Networks Research Articles

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

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

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

Thinned Smart Antenna of a Semi-circular Dipole Array for Massive MIMO Systems

Massive MIMO (multiple-input multiple-output) is a multi-user MIMO technology that can provide high-speed multimedia services in 5G wireless networks using sub-6 GHz and millimeter wave bands. The massive MIMO (MMIMO) installs array antennas in the base stations, using hundreds of transceivers with other RF modules. One of the drawbacks of the MMIMO system is its huge power consumption, and the beamforming network with RF modules for a large number of antennas is the main contributor to the power consumption. In this paper, a novel beamforming method is proposed for the low power consumption of an MMIMO system. The proposed thinned smart antenna (TSA) of a semi-circular array produces a secure beam toward the user’s terminal with reduced interference. By thinning the antenna array, some of the antenna elements are kept off, resulting in less power consumption, while the array pattern remains the same as a fully populated array with a reduced side lobe level (SLL). The sub-6 GHz band of 5 GHz is used for the design of thinned array antennas. The genetic algorithm (GA) is used to determine the array sequence in thinning, and the adaptive signal processing algorithms least mean square (LMS), recursive least square (RLS), and sample matrix inversion (SMI) are used for the beamforming of the TSA, and the corresponding algorithms are GA-LMS, GA-RLS, and GA-SMI. The power saving of 40% to 55% is achieved using TSA. The maximum SLL reductions of 13 dB, 12 dB, and 14 dB are achieved for TSA using GA-LMS, GA-RLS, and GA-SMI algorithms, respectively.

Preface

The 2023 6th International Symposium on Big Data and Applied Statistics (ISBDAS 2023) was held in Shanghai, China from March 10th to 12th, 2023. The purpose of ISBDAS 2023 was to discuss the present status and future perspectives of big data and applied statistics technology. The following topics were selected in order to cover most of the scientific program and highlight an area where new ideas have emerged over recent years:(1) Big Data Mining and Visualization;(2) Big Data Security and Privacy;(3) Computational Mathematics;(4) Probability Theory;(5) Statistical Methodology, etc.There were about 60 participants. In addition to the keynote speeches, we had many talks selected from the contributed papers. There were invited, oral, and poster sessions. This proceedings contains the papers presented in invited and selected talks together with those presented in poster sessions.At the Conference, the participants discussed a wide range of issues affecting the theoretical and computational aspects of research problems in the big data and applied statistics technology. Besides, we had a comprehensive overview of this fascinating field and of future scenarios thanks to the participation of leaders of the most important projects. Professor Zhihui Lv from Fudan University, China performed a keynote speech and shared with us his own research experience and professional view. His main research fields include: network multimedia technology, cloud computing and service computing technology, big data architecture, edge computing, blockchain distributed system, network security technology, cloud data center management technology. And still another speaker was Jingsong Yang, a Professor at Shanghai Jiao Tong University, China. As a third-level researcher, he has undertaken more than 20 national, provincial and international cooperation projects, and has made many innovative achievements in the mechanism of marine microwave remote sensing, remote sensing technology and application, and remote sensing equipment development.We wish to acknowledge our host institutions, sponsors, and the many people whose work made this Conference possible. We would like to express our gratitude to the members of the International Technical Program Committee and those of the Organizing Committee for their efforts which made this Workshop successful. Particularly we would like to present our great thanks to the editors and other colleagues of Journal of Physics: Conference Series for their patience and kind assistance in publishing this paper volume.The Committee of ISBDAS 2023list of Committee Member is available in this pdf.

Smart algorithm in wireless networks for video streaming based on adaptive quantization

SummaryNowadays, smart multimedia network services have become crucial in the healthcare system. The network parameters of Quality of Service (QoS) are widely affecting the efficiency and accuracy of multimedia streaming in wireless environments. This paper proposes an adaptation framework model, which makes a relation between the QP (quantization parameter) in H.264 and H.265 codecs and the QoS of 5G wireless technology. Besides, the effect of QP and packet loss have been studied because of their impact on video streaming. Packet loss of 5G wireless network characteristic is emulated to determine the impact of QP on the received video quality using objective and subjective quality metrics such as PSNR (peak signal to noise ratio), SSIM (structure similarity), and DMOS (differential mean opinion score). In this research, a Testbed is implemented to stream the encoded video from the server to the end users. The application model framework has automatically evaluated the QoE (Quality of Experience). Accordingly, the model detects the defect of network packet loss and selects the optimum QP value to enhance the QoE by the end‐users. The application has been tested on low and high video motions with full high definition (HD) resolution (1920 × 1080) which were taken from ( https://www.xiph.org/downloads/). Test results based on the objective and subjective quality measurements indicate that an optimal QP = 35 and QP = 30 have been chosen for low and high motion respectively to satisfy user QoE requirements.

Cooperative Edge Caching Based on Temporal Convolutional Networks

With the rapid growth of networked multimedia services in the Internet, wireless network traffic has increased dramatically. However, the current mainstream content caching schemes do not take into account the cooperation of different edge servers, resulting in deteriorated system performance. In this paper, we propose a learning-based edge caching scheme to enable mutual cooperation among different edge servers with limited caching resources, thus effectively reducing the content delivery latency. Specifically, we formulate the cooperative content caching problem as an optimization problem, which is proven to be NP-hard. To solve this problem, we design a new learning-based cooperative caching strategy (LECS) that encompasses three key components. Firstly, a temporal convolutional network driven content popularity prediction model is developed to estimate the content popularity with high accuracy. Secondly, with the predicted content popularity, the concept of content caching value (CCV) is introduced to weigh the value of a content cached on a given edge server. Thirdly, an novel dynamic programming algorithm is developed to maximize the overall CCV. Extensive simulation results have demonstrated the superiority of our approach. Compared with the state-of-the-art caching schemes, LECS can improve the cache hit rate by 8.3%-10.1%, and reduce the average content delivery delay by 9.1%-15.1%.

A Hybrid Network User Satisfaction-Based Downlink Scheduling in LTE-A Network

To provide high-quality wireless network multimedia services, the 4G/5G network media access control (MAC) layer has adopted the concept of the quality of service (QoS) with different traffic classification service requirements. To efficiently allocate the limited radio resources for achieving a good balance in QoS, throughput and fairness are necessary for the wireless network MAC scheduling issues. While many conventional scheduling schemes only considered one factor: rate or delay, network users might actually have different rate and delay requirements in concert. Herein, a hybrid network user satisfaction-based downlink scheduling approach, namely, max rate delay urgency first (MRDUF), is developed. The MRDUF approach simultaneously considers rate and delay requirements and adopts a hybrid strategy comprising time- and frequency-domain schedulers using two schemes, namely, the first come first serve (FCFS) and max throughput (MT), for the LTE-A downlink environment. Simulation study results have shown that our proposed approach outperforms the conventional scheduling schemes, including MT, proportional fair (PF), blind equal throughput (BET), and earliest deadline first (EDF). The benefit of MRDUF in terms of fairness of satisfaction of rate and delay is demonstrated by the simulation study.

Link Scheduling Algorithm to Mitigate Worst-Case Interference Problems for LTE-A

As the number of apps increases, the traffic of multimedia services in wireless networks grows exponentially. Because of the proportional fair algorithm's shortcomings in terms of achieving Quality of Service (QoS) requirements such as delay and packet loss, it is not extensively employed in modern wireless communication. This study provides a scheduling method based on the QoS utility function, with a parameter added to improve the priority mechanism in order to overcome such flaws. Our scheduling algorithm can match the QoS criteria of real-time traffic, according to simulation results, and the overall system transmission performance has increased significantly.

GCS: Collaborative video cache management strategy in multi-access edge computing

With the rapid development of multimedia services in wireless mobile networks, the video data traffic has increased exponentially. Traditional video traffic service based on cloud computing caused a large amount of traffic load and longer access delay, which severely reduces the quality of service (QoS) of users. Multi-Access Edge Computing (MEC) can directly serve user requests so as to greatly reduce the traffic load and shorten access delay. At present, distributed caching is widely used in the caching deployment of base stations (BSs). However, the caching capacity of a single BS is generally particularly limited, which will degrade the performance of wireless mobile network. In this paper, a collaborative caching scheme in the heterogeneous MEC networks is designed, and the edge caching of macro base station (MBS) and small base stations (SBSs) is utilized to bring storage resources closer to users. In addition, an optimization problem of content caching is formulated to minimize the total delay cost of all users requesting content in the MEC networks. In order to solve this problem, cache management strategy (GCS) is proposed, which consists of greedy cache placement strategy and greedy cache update strategy. Finally, numerical simulations demonstrate that the GCS scheme effectively improves the cache hit rate, and significantly reduces the average delay and backhaul traffic load.

Optimized Dynamic Routing in Multimedia Vehicular Networks

Intelligent transport system is one of thriving research domain and in particular multimedia vehicular networks gains more attention. The deployment of multimedia services in vehicle ad-hoc networks (VANETs) provides real time support to users and provides better traffic management with high safety measures. Most of the vehicles has multimedia applications such as weather sensors, real time map applications etc., and it requires adequate resources to process. Resource allocation to a static network is simple and various routing models are evolved. In case of dynamic network like VANETs, routing is still in progress in order to obtain a better model. Routing directly related to quality of services of network and user, it is essential to develop a better dynamic routing strategy for multimedia wireless networks. The proposed work aims to provide an optimized dynamic routing strategy for multimedia networks. For efficient routing, k-means clustering is used to organize the clusters and exchanges the routing information and inverted ant colony optimization is used to obtain the optimal path for multimedia access. Proposed model is experimentally verified and compared to conventional ant colony optimization and grey wolf optimization in terms of parameters such as end to end delay, throughput, target used, average computation time and efficiency.

Green Cloud Multimedia Networking: NFV/SDN Based Energy-Efficient Resource Allocation

The rapid growth of communications and multimedia network services such as Voice over Internet Protocol (VoIP) have caused these networks to face a crisis in resources from two perspectives: 1. Lack of resources and, as a result, overload; 2. Redundancy of resources and, as a result, energy loss. Cloud computing allows the scale of resources to be reduced or increased on demand. Many of the gains obtained from the cloud computing come from resource sharing and virtualization technology. On the other hand, the emerging concept of Software-Defined Networking (SDN) can provide a global view of the entire network for integrated resource management. Network Function Virtualization (NFV) can also be used to virtually implement a variety of network devices and functions. In this paper, we present an energy-efficient framework called GreenVoIP to manage the resources of virtualized cloud VoIP centers. By managing the number of VoIP servers and network equipment, such as switches, this framework not only prevents overload but also supports green computing by saving energy. Finally, GreenVoIP is implemented and evaluated on real platforms, including Floodlight, Open vSwitch, and Kamailio. The results suggest that the proposed framework can minimize the number of active devices, prevent overloading, and provide service quality requirements.

Crowd V-IoE: Visual Internet of Everything Architecture in AI-Driven Fog Computing

Fog computing has emerged as a unifying platform to provide computing, communication, and storage for a variety of mobile applications. That helps achieve high bandwidth, high intelligence, low latency, and low energy consumption in handling massive networking devices and emerging rich multimedia services in 5G networks. Current prominence and future promises are changing from the Internet of Things (IoT) to the Internet of Everything (IoE), which is a union of people, process, data, and things. However, the development of fog radio access networks (F-RANs) is challenged by the diversity of IoE, ultra-high-definition videos on demand from users, and low-latency requirement of heterogeneous IoT devices. In this article, we present an architecture of visual IoE (V-IoE) in F-RANs. We systemically analyze the key challenges of V-IoE from the perspective of F-RANs, and propose a crowd V-IoE architecture. Through experimental results, we demonstrate that our proposed architecture exhibits better performance with lower bandwidth requirement, lower energy consumption, and lower latency in F-RANs. Finally, we conclude with a discussion of potential directions.

Intelligent multicast routing for multimedia over cognitive radio networks: a probabilistic approach

Cognitive radio (CR) technology has been demonstrated as one of the key technologies that can provide the needed spectrum bands for supporting the emerging spectrum-hungry multimedia applications and services in next-generation wireless networks. Multicast routing technique plays a significant role in most of wireless networks that require multimedia data dissemination to a group of destinations through single-hop or multi-hop communication. Performing multimedia multicasting over CR networks can significantly improve the quality of multimedia transmissions by effectively exploiting the available spectrum, reducing network traffic and minimizing communication cost. An important challenge in this domain is how to perform a multi-cast transmissions over multiple hops in a dynamically varying CR environment while maintaining high-quality received video streaming to all multi-case CR receivers without affecting the performance of legacy primary radio networks (PRNs). In this paper, we investigate the problem of multicast multimedia streaming in multi-hop CR networks (CRNs). Specifically, we propose an intelligent multicast routing protocol for multi-hop ad hoc CRNs that can effectively support multimedia streaming. The proposed protocol consists of path selection and channel assignment phases for the different multi-cast receivers. It is based on the shortest path tree (SPT) that implements the expected transmission count metric (ETX). The channel selection is based on the ETX, which is a function of the probability of success (POS) over the different channels that depends on the channel-quality and availability. Simulation results verify the significant improvement achieved by the proposed protocol compared to other existing multicast routing protocols under different network conditions.

Secure Beamforming in Full-Duplex Two-Way Relay Networks With SWIPT for Multimedia Transmission

With the advent of 5G, multimedia services in wireless communication networks will grow dramatically. So far, many researches have focused on improving security, throughput and channel capacity to support multimedia services. In this paper, a new system model of full-duplex (FD) two-way amplify-and-forward (AF) relay network with simultaneous wireless information and power transfer is presented, where two FD legitimate nodes with two single-antenna communicate with each other via energy-constrained AF relay with multiple antennas, and there is a half-duplex node with single antenna who intends to eavesdrop. This paper targets to maximize the secrecy sum rate of the system by designing the transmit beamforming vector of relay under power constraint and zero-forcing constraint, where two energy harvesting protocols, namely, power splitting and time switching are considered. However the maximization problem is a non-convex optimization, and it is very complex to solve. Therefore a linear method is used to find the lower bound of the secrecy sum rate and the non-convex problem is transformed into a convex optimization problem. After that, an iterative algorithm based on difference-of-convex programming is proposed to solve this convex optimization problem. The simulation results show the good convergence of the proposed iterative algorithm and also the superiority of secrecy sum rate of our proposed scheme compared with two traditional schemes.

Stochastic Optimization for Green Multimedia Services in Dense 5G Networks

The manyfold capacity magnification promised by dense 5G networks will make possible the provisioning of broadband multimedia services, including virtual reality, augmented reality, and mobile immersive video, to name a few. These new applications will coexist with classic ones and contribute to the exponential growth of multimedia services in mobile networks. At the same time, the different requirements of past and old services pose new challenges to the effective usage of 5G resources. In response to these challenges, a novel Stochastic Optimization framework for Green Multimedia Services named SOGMS is proposed herein that targets the maximization of system throughput and the minimization of energy consumption in data delivery. In particular, Lyapunov optimization is leveraged to face this optimization objective, which is formulated and decomposed into three tractable subproblems. For each subproblem, a distinct algorithm is conceived, namely quality of experience--based admission control, cooperative resource allocation, and multimedia services scheduling. Finally, extensive simulations are carried out to evaluate the proposed method against state-of-art solutions in dense 5G networks.

Coded color shift keying with frequency domain equalization for low complexity energy efficient indoor visible light communications

The adaptive tri-chromatic color shift keying (CSK) modulation standardized in IEEE 802.15.7 and the advanced quad-chromatic CSK are unable to utilize their entire spectral efficiency range over dispersive indoor VLC channels and incur large power penalties without the use of channel equalization and forward error correction. This degrades the energy efficiency and limits the throughput capability of CSK schemes to approximately half of the data-rates specified in the IEEE standard for multimedia services in wireless personal area networks. To comply with the desire for low latency and minimal implementation complexity in the CSK standardization framework, we consider an industry standard binary convolutional code and frequency domain equalization (FDE) which provide one-shot data packet processing. Our results show that when operating over hybrid indoor visible light communication (VLC) links, the FDE based rate-adaptive coded modulation CSK scheme achieves a significant 11 dB SNR gain over an uncoded, unequalized system.

Performance assessment of three-dimensional video codecs in mobile terminals

Understanding the most relevant factors influencing the end user experience is key to design and manage multimedia services in mobile networks. Thus, user demand can be dealt with efficient strategies of resource management. In this paper, a comprehensive analysis is carried out to evaluate the Quality of Experience (QoE) obtained by three-dimensional (3D) video codecs in mobile terminals. The analysis covers the most widespread 3D video coding formats, namely the frame-compatible Side-by-Side (SbS) and Multiview Video Coding (MVC) schemes. The analysis considers both subjective and objective measurements over compression strategies that combine bit rate reduction and frame-rate dropping. Subjective tests are done by presenting 3D video sequences with different coding parameters to users who judge image quality, depth perception and visual comfort. For this purpose, a mobile phone with autostereoscopic screen is used. Then, mean opinion scores are compared with objective measurements obtained by a video quality measurement tool. Results show that MVC outperforms SbS in terms of image quality. However, when internal parameter settings are set to very restrictive configurations, the impairment of the original image are similar for both codecs. Likewise, results show that the reduction of the video bit rate is the key parameter controlling video quality, and that the use of frame-rate dropping is not enough to counteract the impairment introduced by bit rate reduction. Finally, it is confirmed that a simple QoE indicator for 3D video can be obtained from objective measurements.

A Survey of Emerging Concepts and Challenges for QoE Management of Multimedia Services

Quality of Experience (QoE) has received much attention over the past years and has become a prominent issue for delivering services and applications. A significant amount of research has been devoted to understanding, measuring, and modelling QoE for a variety of media services. The next logical step is to actively exploit that accumulated knowledge to improve and manage the quality of multimedia services, while at the same time ensuring efficient and cost-effective network operations. Moreover, with many different players involved in the end-to-end service delivery chain, identifying the root causes of QoE impairments and finding effective solutions for meeting the end users’ requirements and expectations in terms of service quality is a challenging and complex problem. In this article, we survey state-of-the-art findings and present emerging concepts and challenges related to managing QoE for networked multimedia services. Going beyond a number of previously published survey articles addressing the topic of QoE management, we address QoE management in the context of ongoing developments, such as the move to softwarized networks, the exploitation of big data analytics and machine learning, and the steady rise of new and immersive services (e.g., augmented and virtual reality). We address the implications of such paradigm shifts in terms of new approaches in QoE modeling and the need for novel QoE monitoring and management infrastructures.

More than I ever wanted or just good enough? User expectations and subjective quality perception in the context of networked multimedia services

This article addresses the overall relevance and the influence of user expectations in the context of perceptual quality evaluation of technical systems, and how information about individual expectations can be integrated into research on Quality of Experience (QoE). Based on a literature survey on expectations in the fields of psychology, service quality and consumer satisfaction theory, an existing conceptual QoE perception model is extended by explicitly including desired and adequate expectations in the quality perception process. A direct expectation assessment paradigm is proposed that uses dedicated questionnaires. Further, it is shown how expectation-related knowledge can be used to increase the accuracy of quality prediction models. In addition, experimental setups are presented that enable controlled triggering of expectations in user studies. It is discussed how the role of expectations for QoE can be investigated in future research as well as how to further validate the proposed methods.

Cross-layer resource allocation based on equivalent bandwidth in OFDMA systems

A quality of service (QoS) guaranteed cross-layer resource allocation algorithm with physical layer, medium access control (MAC) layer and call admission control (CAC) considered simultaneously is proposed for the full IP orthogonal frequency division multiple access (OFDMA) communication system, which can ensure the quality of multimedia services in full IP networks. The algorithm converts the physical layer resources such as sub-carriers, transmission power, and the QoS metrics into equivalent bandwidth which can be distributed by the base station in all three layers. By this means, the QoS requirements in terms of bit error rate (BER), transmission delay and dropping probability can be guaranteed by the cross-layer optimal equivalent bandwidth allocation. The numerical results show that the proposed algorithm has higher spectrum efficiency compared to the existing systems.