Multimedia Communication Applications Research Articles

Decoder-ROI based Versatile Video Coding for Multi-Object Tracking Vision Task

The video encoding standards High Efficiency Video Coding (HEVC) and, more recently, Versatile Video Coding (VVC) have introduced significant advancements in multimedia communication applications, such as video conferencing, broadcasting, and notably, E-learning. However, recent developments in artificial intelligence (AI) and big data have given rise to an urgent need for a specialized video encoding model designed specifically for image and video analysis applications using machine vision. In this paper, we propose a novel video encoding approach that effectively combines the ROI Coding algorithm and the VVC encoding model. The proposed method identifies regions of interest within video frames through fundamental and deep features. Based on this, we propose an adaptive compression method for each frame block, ensuring both the execution performance of machine learning applications and minimal data encoding requirements. To achieve new coding scheme without adding bitrate, New feature extraction approach are utilizing only decoded information (Decoder-ROI). The results demonstrate that the Decoder-ROI achieved significant compression rate improvement when compared to standard and relevant VCM schemes. Furthermore, ROI exploitation contributes to a 3.25\% reduction in encoding time compared to the baseline VVC encoding standard.

Design of A New Hexagonal Patch Antenna Array

In satellite TV broadcasting, the general public's enthusiasm for this multimedia communication application is unprecedented, and demand is growing all the time. To meet this growing need for satellite reception, future generations of equipment will call for increasingly powerful yet discreet antennas. Our research focused on the design of a 2x1 planar antenna array with hexagonal-shaped patches operating in the Ku-band, basically at the frequency of 11.7 GHz. The original-shaped radiating element is designed using a methodical approach based on printed antenna theory and simulations.

Re-shaping the Gaming Industry after 5G

Abstract: The fifth generation of wireless communications (5G) is a revolutionary technology that plays a key role in the development of all sectors, including multimedia and entertainment. These systems have become an existential part of our society, industry, science, and more. On the other hand, intensive research is underway in many aspects of the 5th generation wireless communication network. This network has features with a higher mobile data volume, typical user data rate, number of connected devices, and lower end-to-end latency. There is a growing demand for the development and design of 5G multimedia and entertainment communication applications, technologies, and theories. In the context of 5G wireless communication networks, new theories and technologies support a variety of multimedia applications such as entertainment, gaming and social media, audio and video, medical imaging, surveillance videos, business transactions, and Internet-based streams of things. This paper focuses on the possibilities and outcomes of how 5G makes drastic changes in the gaming sector. Keywords: 5G, gaming, lower end-to-end latency, higher mobile data volume, typical user data rate

FPGA based generic RO TRNG architecture for image confusion

True Random Number Generator (TRNG) has become a central element of today’s secure communication. TRNGs developed through FPGA implementation have a significant role in a number of applications in multimedia communication. Ring Oscillator (RO) has been adopted extensively for developing device-independent TRNG structures. The proposed design is a generic TRNG architecture based on an arrangement of ROs with post-processing. This TRNG was initially tested on Altera Cyclone II FPGA which consumed only 64 inverters to produce good randomness. Also, the device-independent capability of this design has been verified by implementing it on other two FPGA families Xilinx Artix – 7 and Microsemi Smart Fusion2. True randomness was also verified by conducting restart experiment, and the statistical properties of TRNG were evaluated through entropy analysis and NIST SP 800–22 tests. The proposed TRNG yields 26.640650 Mbps as throughput with a sampling clock of 27 MHz. Going beyond the regular key generation utility, the evolving random bits of TRNG were packed suitably to perform confusion of grayscale images producing a near-zero correlation of pixels, thereby extending the application of TRNG to image encryption.

DASH-QoS: A scalable network layer service differentiation architecture for DASH over SDN

As one of the key technologies residing in the future Internet concepts, Software Defined Networking (SDN) makes it possible to develop application-centric flow routing strategies. Thanks to the benefits offered by the SDN architecture, the performance of multimedia communication applications can be improved by developing application-centric flow routing strategies. Recently, MPEG-DASH standard which allows rate adaptation over HTTP has become popular. In this work, we present an architecture that provides increase in received quality of DASH clients running over an SDN domain. Within this architecture, we propose an optimization model which determines the streaming paths of the video packets of the clients. We also define different types of user classes and provide a guaranteed service and fairness among the users of the same class. Furthermore, we created a heuristic algorithm to facilitate the scalability of the solution. The simulation results show that, by considering the output of the optimization model and dynamically changing the routing paths in an ISP, the video quality offered to the DASH clients is significantly improved and a certain level of service guarantee is provided.

Design of Low Power Vedic Multiplier Based Reconfigurable Fir Filter for DSP Applications

Recent advances in mobile computing and multimedia applications demand high - performance and low - power VLSI digital signal processing (DSP) systems. One of the most widely used operations in DSP is finite - impulse response (FIR) filtering. In the existing method FIR filter is designed using array multiplier, which is having higher delay and power dissipation. The proposed method presents a programmable digital finite impulse response (FIR) filter for high - performance applications. One of the most widely used operations in DSP is finite - impulse response (FIR) filtering. In the existing method FIR filter is designed using array multiplier, which is having higher delay and power dissipation. The proposed method presents a programmable digital finite impulse response (FIR) filter for high performance applications. The FIR filter performs the weighted summations of input sequences and is widely used in video convolution functions, signal preconditioning, and various communication applications. Recently, due to the high - performance requirement and increasing complexity of DSP and multimedia communication application. In this work, , FIR filter multipliers are extensively characterized with power simulations, providing a methodology for the perturbation of the coefficients of baseline filters at the algorithm level to trade-off reduced power consumption for filter quality. The proposed optimization technique does not require any hardware overhead and it enables the possibility of scaling the power consumption of the filter at runtime.

Autonomous multimedia cluster computing based on Cooperative Cognition data behavior measurement under multi cloud computing

In order to meet the needs of multimedia communication in multi cloud environment and improve the experience quality of mobile multimedia users, based on multi cloud computing, based on Cooperative cognitive data behavior measurement, this paper proposes an autonomous multimedia cluster computer system and its architecture. First of all, dispersed edge clouds are distributed and integrated, and cooperate to provide multimedia storage and computing functions. In cloudy environment, a hierarchical access service point is designed between edge cloud and core cloud. On this basis, a multimedia cluster computing system suitable for cloudy environment is built. Secondly, a mulch-dimensional mapping mechanism is built between the link management interface array and the task scheduling array in the edge cloud array. Mulch-dimensional multimedia data and real-time task scheduling cooperation cognition, and core cloud are used to interact with DP vectors with dedicated channels. On this basis, we propose an autonomous computer system based on Cooperative Cognition and multimedia data behavior measure. Finally, it is analyzed by three groups of experiments. The resource utilization of the multimedia cluster computing system, the behavior measurement accuracy based on the cooperative cognitive multimedia data behavior measure and the performance of the proposed autonomous multimedia cluster computing (AMC-CCC) in large-scale real-time multimedia communication applications. The results show that the proposed AMC-CCC mechanism has excellent performance in multimedia QoS, resource management and data behavior measurement.

Collaborative content dissemination based on game theory in multimedia cloud

With the development of multimedia clouding applications and broadband technology, multimedia group communication applications, such as multi-point video conference, major news and events live, internet-on-demand TV, network video monitoring and so on, continue to emerge. However, limited network bandwidth, burst of incoming service requests, and imbalance of content dissemination seem to be the most important factors that affect users’ experience. To this end, this paper proposes a collaborative content dissemination method based on game theory in multimedia cloud. In order to obtain the optimal number of service user in each group, integrated utility value of each user is calculated, and the improved particle swarm optimization algorithm is used. Moreover, the matching problem between service users and non-service users is formulated into game theory. In order to avoid the blindness and selfishness of non-service users to choose the service users, an evolutionary game is aimed at achieving the stability by learning the connection from the non-service users. A Stackelberg game is aimed at obtaining optimal pricing policy and bandwidth allocation of service users. The numerous experiment results show that the proposed method can effectively improve users’ experience of those who have weak system capabilities, reduce the average time of the content dissemination and decrease the total cost of the multimedia cloud user.

Learning-based approach for layered adaptive video streaming over SDN

Software-defined networking is a recently emerging paradigm that decouples the control and data planes of computer networks. It allows for the implementation of application-specific routing algorithms, and the advantages that the SDN architecture enables can be used to enhance the performance of multimedia communication applications. In this paper, we propose an adaptive video streaming system with a learning-based approach, running over SDN. In the proposed video streaming system, we use a novel learning model to determine the optimal time to re-route the traffic flows and to change the bitrate of the video. The learning model aims to minimize the packet loss rate, quality changes and controller cost while adapting the flow routes and video quality. We have tested the performance of the learning-based approach by comparing it to traditional Internet routing and the greedy approach. The results show that the proposed system significantly outperforms the traditional Internet routing approach and the greedy approach in terms of quality of experience (QoE) and network cost under different network scenarios.

Guest Editorial: Ubiquitous Multimedia Systems and Applications

The technologies of computing and communications have undergone a series of evolutionary innovation over the past decades and improved the quality of human life significantly. Ubiquitous computing and communications is a revolutionary paradigm that aims to provide pervasive and reliable computing solutions and communication services anytime and anywhere. This emerging technology is built upon the rapid research and development advances in a wide range of key areas including wireless and sensor networks, mobile and distributed computing, embedded systems, agent technologies, autonomic communication and information security. Ubiquitous computing and communications has drawn significant interests from both academia and industry and continues to attract tremendous research efforts due to its promising new business opportunity in information technology and engineering. This special issue is devoted to papers addressing research challenges and advances towards the design, implementation and evaluation of ubiquitous multimedia computing and communications technologies, systems and applications. This special issue contains six papers, which are briefly introduced as follows. Exposure fusion is an efficient way for producing high-quality images for common low dynamic range (LDR) output devices from multiple differently exposed LDR images of the same scene, which has significant potential to be applied in the ubiquitous multimedia area. In the paper entitled BA Novel Method for Fusion of Differently Exposed Images Based on Spatial Distribution of Intensity for Ubiquitous Multimedia^ (10.1007/s11042-013-1660-0), Multimed Tools Appl (2015) 74:2743–2744 DOI 10.1007/s11042-015-2458-z

Introductory survey for wireless infrared communications

Wireless infrared communications can be defined as the propagation of light waves in free space using infrared radiation whose range is 400–700 nm. This range corresponds to frequencies of hundreds of terahertz, which is high for higher data rate applications. Wireless infrared is applied for higher data rates applications such as wireless computing, wireless video and wireless multimedia communication applications. Introduced by Gfeller, this field has grown with different link configurations, improved transmitter efficiency, increased receiver responsivity and various multiple access techniques for improved quality. Errors are caused because of background light, which causes degradation overall system performance. Error correction techniques are used to remove the errors caused during transmission. This study provides a brief account on field theory used for error correction in wireless infrared systems. The results are produced in terms of bit error rate and signal-to-noise ratio for various bit lengths to show the ability of encoding and decoding algorithms.

Challenges of Interactive Multimedia Data Mining in Social and Behavioral Studies for latest Computing &Communication of an Ideal Applications

Now a day's entire world became a single village because due to the technology of computer science it brings whole globe peoples in front of each other on a single place like a village another thing computer is quite different with human being due its dynamic characteristics like speed, versatility, accuracy, storage and due to these super specialty characteristics computer has got variety of applications and challenges and booms of demands in every field of life. And hence the demands and market of Growing and emerging Multimedia computing and communication applications also increased since last few years. So the advancement in computing, carrying towards its modern and smart technology, large amount of (Audio, Video) that is multimedia data is being required and collected in highly research labs for various scientific purposes in various scientific fields, specifically in social and behavioral research studies and so new ideas and knowledge is being collect and extracted from raw multimedia data which poses a computing challenges of data mining techniques can often only search and extract pre-defined patterns or knowledge from complex heterogeneous data. In this paper our approach is to take in cash the human perception power system and the strength of computer algorithms. so this results into turning of the visualized and lead to the next round of visual exploration and analysis. And from the raw data ideology will come out the current status of analysis can be

Age Dependent Face Recognition using Eigenface

Face recognition is the most successful form of human surveillance. Face recognition technology, is being used to improve human efficiency when recognition faces, is one of the fastest growing fields in the biometric industry. In the first stage, the age is classified into eleven categories which distinguish the person oldness in terms of age. In the second stage of the process is face recognition based on the predicted age. Age prediction has considerable potential applications in human computer interaction and multimedia communication. In this paper proposes an Eigen based age estimation algorithm for estimate an image from the database. Eigenface has proven to be a useful and robust cue for age prediction, age simulation, face recognition, localization and tracking. The scheme is based on an information theory approach that decomposes face images into a small set of characteristic feature images called eigenfaces, which may be thought of as the principal components of the initial training set of face images. The eigenface approach used in this scheme has advantages over other face recognition methods in its speed, simplicity, learning capability and robustness to small changes in the face image.

Optimal-constrained multicast sub-graph over coded packet networks

Network coding is a technique which can be used to improve the performance of multicast communications by performing encoding operations at intermediate nodes. In real-time multimedia communication applications, there are usually several weights associated with links, such as cost, delay, jitter, loss ratio, security, and so on. In this paper, we consider the problem of finding an optimal multicast sub-graph over coded packet networks, where the longest end-to-end weight from the source to each destination does not exceed an upper bound. First, a mixed integer programming model is proposed to formulate the problem which is NP-hard. Then, a column-generation approach is described for this problem, in which the problem is decomposed into a master linear programming problem and several integer programming sub-problems. Moreover, two methods based on linear and Lagrangian relaxation are proposed to compute a tight lower bound of the optimal solution value. Computational results show that the proposed algorithm provides an efficient way for solving the problem, even for relatively large networks.

QoE-Driven Channel Allocation Schemes for Multimedia Transmission of Priority-Based Secondary Users over Cognitive Radio Networks

With the fast growing of multimedia communication applications, cognitive radio networks have gained the popularity as they can provide high wireless bandwidth and support quality-driven wireless multimedia services. In multimedia applications such as video conferences over the cognitive radio, the Quality of Experience (QoE) that directly measures the satisfaction of the end users cannot be easily realized due to the limited spectrum resources. The opportunistic spectrum access cognitive radio (CR) is an efficient technology to address this issue. However, the unstable channels allocated to the multimedia secondary users (SUs) can be re-occupied by the primary users (PUs) at any time, which makes the CR difficult to meet the QoE requirements. Therefore, it is important to study how to allocate frequency or spectrum resources to SUs according to their QoE requirements. This paper proposes a novel QoE-driven channel allocation scheme for SUs and cognitive radio networks (CRN) base station (BS). The historical QoE data under different primary channels (PCs) are collected by the SUs and delivered to a Cognitive Radio Base Station (CRBS). The CRBS will allocate available channel resources to the SUs based on their QoE expectations and maintain a priority service queue. The modified ON/OFF models of PCs and service queue models of SUs are jointly investigated for this channel allocation scheme. The performance of multimedia transmission of images and H.264 videos under our CR channel allocation scheme is studied, the results show that the proposed channel allocation approach can significantly improve the QoE of the priority-based SUs over the cognitive radio networks.

A domain‐specific modeling approach to realizing user‐centric communication

SUMMARYAdvances in communication devices and technologies are dramatically expanding our communication capabilities and enabling a wide range of multimedia communication applications. The current approach to develop communication‐intensive applications results in products that are fragmented, inflexible, and incapable of responding to changing end‐users' communication needs. These limitations have resulted in the need for a new development approach of building communication applications that are driven by end‐users and that support the dynamic nature of communication‐based collaboration. To address this need, the Communication Virtual Machine (CVM) technology has been developed to support rapid specification and automatic realization of user‐centric communication applications based on a domain‐specific modeling approach. The CVM technology consists of a domain‐specific modeling language (DSML), the Communication Modeling Language (CML), that is used to create communication models, and a semantic rich platform, the CVM, that realized the created communication models. In this paper, we report on our experiences of applying a systematic approach to engineering CML and the synthesis of CML models in CVM. Based on a feature model describing the taxonomy of the user‐centric communication domain in a network independent manner, we develop the meta‐model of CML and its different concrete syntaxes. We also present a behavioral specification (dynamic semantics) of CML that enables the dynamic synthesis of user‐centric communication models into an executable form called communication control script. We validated the CML semantics using Kermeta, a meta‐programming environment for engineering DSMLs, and evaluated the practicality of our approach using a CVM prototype and a set of experiments. Copyright © 2011 John Wiley & Sons, Ltd.

Multicast routing with bandwidth and delay constraints based on genetic algorithms

Many multimedia communication applications require a source to send multimedia information to multiple destinations through a communication network. To support these applications, it is necessary to determine a multicast tree of minimal cost to connect the source node to the destination nodes subject to delay constraints on multimedia communication. This problem is known as multimedia multicast routing and has been proved to be NP-complete. The paper proposes a genetic algorithm for solving multimedia multicast routing, which find the low-cost multicasting tree with bandwidth and delay constraints. In the proposed algorithm, the k shortest paths from the source node to the destination nodes are used for genotype representation. The simulation results show that the proposed algorithm is able to find a better solution, fast convergence speed and high reliability. It can meet the real-time requirement in multimedia communication networks. The scalability and the performance of the algorithm with increasing number of network nodes are also quite encouraged.

Age Estimation, A Gabor PCA-LDA Approach

Automatic human age estimation has considerable potential applications in human computer interaction and multimedia communication. In this paper the Gabor wavelet and its characteristics as a powerful mathematical and biological tool, was used for feature extraction. A combination of Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) was used to reduce dimension and enhance class separability. Finally Euclidean distance was used to classify the images into one of three major groups. These groups are: Group1 (0 to 3 years), Group2 (5 to 10 years) and Group3 (20 to 80 years). The robustness and accuracy of the proposed system was tested on the FG-NET [1] and MORPH [2] public face aging databases. This system was able to achieve 90% accuracy.

Monitoring and management of peer-to-peer systems

The peer-to-peer paradigm has had large success in content distribution and multimedia communication applications on the Internet. In a peer-to-peer network, the participating nodes create an infrastructure to provide a desired functionality and offer their resources to host an application in a distributed manner.

Fast Mode Decision Algorithm for Scalable Video Coding Using Bayesian Theorem Detection and Markov Process

The <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">newest</i> video coding standard called scalable video coding (SVC) provides broad applications in multimedia communications. SVC encoder consumes great computational complexity when compared to previous video coding standards. This paper presents a fast mode decision algorithm that speeds up the SVC encoding process through probabilistic analysis. The mode of the enhancement layer is first predicted by statistical analysis. Afterward, Bayesian theorem is utilized to detect whether the prediction mode of the current macroblock is the best or not. The mode is further predicted and refined by the Markov process. Experimental results show that the proposed algorithm significantly reduces computational complexity with negligible peak signal-to-noise ratio degradation and bitrate increase in the enhancement layers.