Multimedia Services Research Articles

Intrusion detection by machine learning for multimedia platform.

The multimedia service company, Netflix, increased the number of new subscribers during the Coronavirus pandemic age. Intrusion detection systems for multimedia platforms can prevent the platform from network attacks. An intelligent intrusion detection system is proposed for the security IP Multimedia Subsystem (IMS) based on machine learning technology. For increasing the accuracy of the classifiers, it is vital to select the critical features to construct the intrusion detection system. Two-class classifiers, including the Decision Tree, Support Vector Machine, and Naive Bayesian, are selected to evaluate intrusion detection accuracy. According to the three classifiers’ accuracy values, the most critical features are selected based on the features’ ranking orders. Six critical features are selected:Service, dst_host_same_srv_rate, Flag, Protocol Type, Dst_host_rerror_rate, and Count. Numerical comparison with state_of_the_art shows that critical features improve intrusion detection accuracy, which can be better than the deep learning method.

Artificial intelligent system for multimedia services in smart home environments

Internet of Things (IoT) has introduced new applications and environments. Smart Home provides new ways of communication and service consumption. In addition, Artificial Intelligence (AI) and deep learning have improved different services and tasks by automatizing them. In this field, reinforcement learning (RL) provides an unsupervised way to learn from the environment. In this paper, a new intelligent system based on RL and deep learning is proposed for Smart Home environments to guarantee good levels of QoE, focused on multimedia services. This system is aimed to reduce the impact on user experience when the classifying system achieves a low accuracy. The experiments performed show that the deep learning model proposed achieves better accuracy than the KNN algorithm and that the RL system increases the QoE of the user up to 3.8 on a scale of 10.

Power Budget Analysis of a Distributed 5G EPON Network

This work studies the power-budget analysis of a fully distributed ring-based EPON(Ethernet Passive Optical Network) architecture that enables the support of a converged PON-5G access networking transport infrastructure that is capable to seamlessly backhaul both mobile and wireline multimedia traffic and services.

A NETWORK PERFORMANCE COMPARISON OF WEBRTC AND SIP AUDIO AND VIDEO COMMUNICA TIONS

Multimedia services are one of the internet needs with high data traffic network count since 2019. Two of the multimedia services, Web Real-Time Communications (WebRTC) and Session Initiation Protocol (SIP), have been widely used in applications for conducting video conferencing. The main objective of this research is to analyze network performance by an application with a client-server for audio and video communications developed with WebRTC and SIP protocols. The SIP system uses the FreePBX server, and the softphone application uses Bria. Whereas WebRTC uses JavaScript with servers on Ubuntu using Node.js. The analysis application uses a star topology and runs on a local network using Wi-Fi. After testing, the results show that the throughput, jitter, and packet loss of WebRTC are better than SIP. This result is caused by several factors including the type of codec, the type of platform, and the way of signaling and routing of each protocol.

Self-Healing Group Key Distribution Facilitating Source Authentication Using Block Codes

Secure group key distribution is essential for many group-oriented applications such as sensor networks, multimedia broadcast services, and Internet of Things (IoT) scenarios. There are several challenges and requirements in designing secure group key distribution. Among them, computational efficiency, communication efficiency, adaptability to dynamic group membership change, robustness to various security threats, self-healing capacities, and source authentication are desirable. It is very challenging to design an efficient group distribution that satisfies all the requirements and challenges. Based on block codes, we propose an efficient self-healing group key distribution that facilitates both message source authentication and secure group key distribution, where the source identification and authentication can facilitate intrusion detection and identification. Both the privacy of the group key and the authentication of message sources are computationally secure. To the best of our knowledge, it is the first codes-based scheme that satisfies all the above requirements and facilitates message source authentication. The merits of the proposed scheme include the following: (1) it is highly efficient in terms of computation and communication, (2) it provides self-healing capacities for unstable environments, (3) it is very robust to various security threats and attacks, (4) it facilitates both message source authentication and secure group key distribution, and (5) it greatly improves the communication performance, compared to the state-of-the-art schemes. The security properties are analyzed, and the performance evaluations confirm its efficiency and practicality.

THE SAME GOES FOR ORGANIZING ELEMENTARY SCHOOL NATIVE LANGUAGE CLASSES SPECIFICITY

The article in the section describes the advantages and problems of non-traditional lessons in language lessons for primary school, the use of modern teaching techniques in educational systems, the definition of methods of teaching students who provide multimedia services.

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.

Performance enhancement for visible light communication based ADO-OFDM

The increasing demand for bandwidth through modern applications and multimedia services has led to high-speed wireless communications. Optical wireless communications (OWC) encourages solutions that provide a higher data rate due to the large bandwidth available. In this paper, performance enhancement approaches are studied and simulated for visible light communication (VLC) as a case study. The orthogonal frequency division multiplexing (OFDM) systems are used to investigate Intensity modulation/direct detection (IM/DD) to improve the performance of VLC. The IM/DD in OWC requires positive real OFDM symbols, so there are many approaches to satisfy this requirement. This paper proposes a model of Asymmetrically Clipped DC-Biased Optical (ADO-OFDM) to use in OWC/VLC environment. The proposed system has avoided the use of the noise cancellation technology that is used in traditional ADO-OFDM. The results show that the ADO-OFDM has the best spectral efficiency than DC-biased optical (DCO-OFDM) and Asymmetrically clipped optical (ACO-OFDM). Also, it has better optical efficiency than DCO-OFDM with the equally overall bit error rate (BER) at the same signal-to-noise ratio. Hamming channel coding/decoding with different code lengths is applied in various optical OFDM schemes for BER improvements. Furthermore, we simulate and analyze these optical OFDM systems with many modulation orders.

Investigating indirect impacts of TCP connection on IMS network

The IP Multimedia Subsystem (IMS) is recently expected to have the major architecture framework to be involved in the Next Generation Network. IMS works to bridge the multimedia communication among variety of applications over Internet. IMS bears its multimedia signals and stream through different means of transport protocols; TCP, UDP, and SCTP. TCP is a connection-oriented protocol that provides reliable data delivery and congestion control. To setup connection with TCP, IMS entities requires extra operations to complete, that operation process called (worker process) costs the multimedia server extra overload and delay. This paper investigates the indirect impacts of TCP connection that resulted from the Call Session Control Function (CSCF) servers when it deal with video communication. Two parameters are evaluated in experiment which are CPU usage and response time with two different scenarios. The experimental shows that outbound scenario performs better than the inbound scenario due to the extra operations required to setup new TCP connection for inbound

Augmenting Speech Quality Estimation in Software-Defined Networking Using Machine Learning Algorithms.

With the increased number of Software-Defined Networking (SDN) installations, the data centers of large service providers are becoming more and more agile in terms of network performance efficiency and flexibility. While SDN is an active and obvious trend in a modern data center design, the implications and possibilities it carries for effective and efficient network management are not yet fully explored and utilized. With most of the modern Internet traffic consisting of multimedia services and media-rich content sharing, the quality of multimedia communications is at the center of attention of many companies and research groups. Since SDN-enabled switches have an inherent feature of monitoring the flow statistics in terms of packets and bytes transmitted/lost, these devices can be utilized to monitor the essential statistics of the multimedia communications, allowing the provider to act in case of network failing to deliver the required service quality. The internal packet processing in the SDN switch enables the SDN controller to fetch the statistical information of the particular packet flow using the PacketIn and Multipart messages. This information, if preprocessed properly, can be used to estimate higher layer interpretation of the link quality and thus allowing to relate the provided quality of service (QoS) to the quality of user experience (QoE). This article discusses the experimental setup that can be used to estimate the quality of speech communication based on the information provided by the SDN controller. To achieve higher accuracy of the result, latency characteristics are added based on the exploiting of the dummy packet injection into the packet stream and/or RTCP packet analysis. The results of the experiment show that this innovative approach calculates the statistics of each individual RTP stream, and thus, we obtain a method for dynamic measurement of speech quality, where when quality decreases, it is possible to respond quickly by changing routing at the network level for each individual call. To improve the quality of call measurements, a Convolutional Neural Network (CNN) was also implemented. This model is based on two standard approaches to measuring the speech quality: PESQ and E-model. However, unlike PESQ/POLQA, the CNN-based model can take delay into account, and unlike the E-model, the resulting accuracy is much higher.

An Elastic System Architecture for Edge Based Low Latency Interactive Video Applications

5G and edge computing have brought great changes to video industry. Interactive video is becoming an emerging application form of multimedia service, which provides attraction beyond typical scenarios like cloud gaming and remote virtual reality (VR), and puts forward great challenges in resource capacity, response latency, and function flexibility to its service system. In this paper, we propose an elastic system architecture with low latency features to accommodate generic interactive video applications on near user edges. To increase system flexibility, we firstly design a dynamic Directed Acyclic Graph (dDAG) model for efficient task representation. Secondly, based on the model, we present the elastic architecture together with its scalable workflow pipeline. Thirdly, we propose a set of novel latency measurement metrics to analyze and optimize the performance of an interactive video system. Based on the proposed approaches, we disassemble a real world free-viewpoint synthesis application and benchmark its performance with the metrics. Extensive experimental results show the flexibility of our system to handle the stochastic human interactions during a video service session, with less than 5 ms additional scheduling latency introduced. End to end latency is kept within 43 ms for complex functions, and 28 ms for simpler scenarios, which satisfies the restrictions of most interactive video applications provided by an edge. Client of the architecture serves as a pure video player, which is also friendly to power limited terminals such as 5G phones. Efficiency and stability analyses of the system show superiorities over existing work, and also reveal potential optimization directions for future research.

Resource Allocation for Millimeter-Wave Train-Ground Communications in High-Speed Railway Scenarios

With the development of wireless communication, higher requirements arise for train-ground wireless communications in high-speed railway (HSR) scenarios. The millimeter-wave (mm-wave) frequency band with rich spectrum resources can provide users in HSR scenarios with high performance broadband multimedia services, while the full-duplex (FD) technology has become mature. In this paper,we study train-ground communication system performance in HSR scenarios with mobile relays (MRs) mounted on rooftop of train and operating in the FD mode. We formulate a nonlinear programming problem to maximize network capacity by allocation of spectrum resources. Then, we develop a sequential quadratic programming (SQP) algorithm based on the Lagrange function to solve the bandwidth allocation optimization problem fortrack-side base station (BS) and MRs in this mm-wave train-ground communication system. Extensive simulation results demonstrate that the proposed SQP algorithm can effectively achieve high network capacity for train-ground communication in HSR scenarios while being robust to the residual self-interference (SI).

Automatic Topics Segmentation for News Video by Clustering of Histogram of Orientation Gradients Faces

TV stream is a major source of multimedia data. The proposed method aims to enable a good exploitation of this source of video by multimedia services social community, and video-sharing platforms In this work, we propose an approach to the automatic topics segmentation of news video. The originality of the approach is the use of Clustering of Histogram of Orientation Gradients (HOG) faces as prior knowledge. This knowledge is modeled as images which governs the structuring of TV stream content. This structuring is carried out on two levels. The first consists in the identification of anchorperson by Single-Linkage Clustering of HOG faces. The second level aims to identify the topics of news program due to the large audience because of the pertinent information they contain. Experiments comparing the proposed technique to similar works were carried out on the TREC Video Retrieval Evaluation (TRECVID) 2003 database. The results show significant improvements to TV news structuring exceeding 96 %.

Performance evaluation of inter-cell interference prediction in massive MIMO

This paper presents inter-cell interference prediction in massive multiple input multiple output. The rapid demand for widespread multimedia services notwithstanding the deployment of 4G in Lagos, Nigeria and the urgent need to upgrade to 5G networks with downlink and uplink data capacities of not less than 300 and 60 Mbps, respectively for at least 95% penetration rate at any instantaneous time; there is a possibility of experiencing crosstalk and adjacent inter-cell interference within the receiving antennas. 5G inter-cell interference prediction scheme that employs LTE performance index using locally sourced data from Huawei Nigeria limited was presented. The performances of the currently deployed LTE network were evaluated by employing performance metrics such as uplink and downlink capacities and recommending a possible inter-cell interference mitigation technique to be implemented in the deployment of 5G network in Lagos. The identified key performance metrics used include over the air emulation, carrier to interference plus noise ratio, peak RLC throughput, coverage probability, and the map-based model. Hence, ICIC static coordination algorithm, which comprise NOICIC, Hard FFR, PFR, SFR and SFFR were analyzed. With static ICIC algorithm, the coverage probability was 78% for receiving more than 20 kbps, with cell-edge users using resources of centre-users and with edge-users of neighbouring cells using different resource block; therefore reducing interference and consequently increasing throughput when there is static ICIC coordination. Implementing the static ICIC schemes on the 5G network when deployed in Lagos will improve the average downlink throughput over what is currently attainable with the 4G network in use at the moment

TripRes

The Internet of Vehicles (IoV) connects vehicles, roadside units (RSUs) and other intelligent objects, enabling data sharing among them, thereby improving the efficiency of urban traffic and safety. Currently, collections of multimedia content, generated by multimedia surveillance equipment, vehicles, and so on, are transmitted to edge servers for implementation, because edge computing is a formidable paradigm for accommodating multimedia services with low-latency resource provisioning. However, the uneven or discrete distribution of the traffic flow covered by edge servers negatively affects the service performance (e.g., overload and underload) of edge servers in multimedia IoV systems. Therefore, how to accurately schedule and dynamically reserve proper numbers of resources for multimedia services in edge servers is still challenging. To address this challenge, a traffic flow prediction driven resource reservation method, called TripRes, is developed in this article. Specifically, the city map is divided into different regions, and the edge servers in a region are treated as a “big edge server” to simplify the complex distribution of edge servers. Then, future traffic flows are predicted using the deep spatiotemporal residual network (ST-ResNet), and future traffic flows are used to estimate the amount of multimedia services each region needs to offload to the edge servers. With the number of services to be offloaded in each region, their offloading destinations are determined through latency-sensitive transmission path selection. Finally, the performance of TripRes is evaluated using real-world big data with over 100M multimedia surveillance records from RSUs in Nanjing China.

A Review of Antenna Array Technologies for Point-to-Point and Point-to-Multipoint Wireless Communications at Millimeter-Wave Frequencies

With the introduction of 5G communication systems operating in the mm-wave frequency range, new opportunities in terms of multimedia services and applications will become available. For this to happen, several technical challenges from an antenna standpoint need to be addressed. The achievements of high-gain characteristics and agile beamforming with wide-scan capabilities are the main targets of the ongoing research on mm-wave antenna arrays. In this paper, an up-to-date overview of antenna array technology for wireless communications at mm-wave frequencies is given. Particular focus is put on the review of the state-of-the art and most advanced antenna array concepts for point-to-point and point-to-multipoint radio links at said frequencies. Various figures of merit are assessed for a comprehensive analysis and bench marking of the technical solutions investigated in the presented survey.

Coverless Steganography Based on Motion Analysis of Video

With the rapid development of interactive multimedia services and camera sensor networks, the number of network videos is exploding, which has formed a natural carrier library for steganography. In this study, a coverless steganography scheme based on motion analysis of video is proposed. For every video in the database, the robust histograms of oriented optical flow (RHOOF) are obtained, and the index database is constructed. The hidden information bits are mapped to the hash sequences of RHOOF, and the corresponding indexes are sent by the sender. At the receiver, through calculating hash sequences of RHOOF from the cover video, the secret information can be extracted successfully. During the whole process, the cover video remains original without any modification and has a strong ability to resist steganalysis. The capacity is investigated and shows good improvement. The robustness performance is prominent against most attacks such as pepper and salt noise, speckle noise, MPEG-4 compression, and motion JPEG 2000 compression. Compared with the existing coverless information hiding schemes based on images, the proposed method not only obtains a good trade-off between hiding information capacity and robustness but also can achieve higher hiding success rate and lower transmission data load, which shows good practicability and feasibility.

SDN Enabled QoE and Security Framework for Multimedia Applications in 5G Networks

The technologies for real-time multimedia transmission and immersive 3D gaming applications are rapidly emerging, posing challenges in terms of performance, security, authentication, data privacy, and encoding. The communication channel for these multimedia applications must be secure and reliable from network attack vectors and data-contents must employ strong encryption to preserve privacy and confidentiality. Towards delivering secure multimedia application environment for 5G networks, we propose an SDN/NFV (Software-Defined-Networking/Network-Function-Virtualization) framework called STREK , which attempts to deliver highly adaptable Quality-of-Experience (QoE), Security, and Authentication functions for multi-domain Cloud to Edge networks. The STREK architecture consists of a holistic SDNFV dataplane, NFV service-chaining and network slicing, a lightweight adaptable hybrid cipher scheme called TREK, and an open RESTful API for applications to deploy custom policies at runtime for multimedia services. For multi-domain/small-cell deployments, the key-generation scheme is dynamic at flow/session-level, and the handover authentication scheme uses a novel method to exchange security credentials with the Access Points (APs) of neighborhood cells. This scheme is designed to improve authentication function during handover with low overhead, delivering the 5G ultra-low latency requirements. We present the experiments with both software and hardware-based implementations and compare our solution with popular lightweight cryptographic solutions, standard open source software, and SDN-based research proposals for 5G multimedia. In the microbenchmarks, STREK achieves smaller hardware, low overhead, low computation, higher attack resistance, and offers better network performance for multimedia streaming applications. In real-time multimedia use-cases, STREK shows greater level of quality distortion for multimedia contents with minimal encryption bitrate overhead to deliver data confidentiality, immunity to common cryptanalysis, and significant resistance to communication channel attacks, in the context of low-latency 5G networks.

State-Of-The-Art In Video Processing: Compression, Optimization And Retrieval

Video compression plays a vital role in the modern social media networking with plethora of multimedia applications. It empowers transmission medium to competently transfer videos and enable resources to store the video efficiently. Nowadays high-resolution video data are transferred through the communication channel having high bit rate in order to send multiple compressed videos. There are many advances in transmission ability, efficient storage ways of these compressed video where compression is the primary task involved in multimedia services. This paper summarizes the compression standards, describes the main concepts involved in video coding. Video compression performs conversion of large raw bits of video sequence into a small compact one, achieving high compression ratio with good video perceptual quality. Removing redundant information is the main task in the video sequence compression. A survey on various block matching algorithms, quantization and entropy coding are focused. It is found that many of the methods having computational complexities needs improvement with optimization.

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.