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Summary In the present‐day scenario, multimedia technology serves as a vital medium for communication, facilitating the exchange of information among individuals across various sectors such as education, mass media, banking, and healthcare. In our proposal for a centralized system to store patient data, we aim to enhance healthcare services by enabling doctors to access the medical history of every patient seamlessly. To ensure hassle‐free services, we have devised a for authenticated key sharing protocol leveraging cryptographic hash functions for the Internet of Things healthcare system. A key advantage of our approach is that patients need not undergo medical tests repeatedly, unless it is deemed necessary due to diagnostic requirements. We have provided informal proof of the protocol's ability to safeguard against security threats. Furthermore, we have conducted simulations using the Scyther simulation tool to verify the strength of our protocol, affirming its safety and effectiveness. Our performance analysis section demonstrates significantly improved complexities compared to existing protocols, further emphasizing the reliability and efficiency of our proposed solution. [ABSTRACT FROM AUTHOR]

IP mobility support is based on terminal behavior, recognizing mobility and maintaining a continuous communication session. The existing mobile IP location registration sends a message to one or more routers during a handoff within a domain by using a multicast address to process messages continuously. This implementation requires persistent message processing among all routers to determine new multicast address assignments. To solve this problem, we propose a method that enables the mobile user to obtain a QoS guarantee when the mobile device moves to an overlapping area under the mobile IP. Therefore, dynamic mobility management includes location updates under the mobile IP, and transmission of packets from the expected access points. When a handoff occurs while the mobile device is connected, the mobile host dynamically adapts to the mobility characteristics of the mobile node and transmits missed packets. In addition, by first using a location router, handoff latency reduction and packet loss requirements between domains in the overlapping mobile network environment are resolved. Second, the proposed algorithm has low-control traffic in the mobile network, allowing quick handoffs. Although instantaneous throughput is reduced during handoffs, tunneling is reduced by 10-30%, even after a handoff, by retransmitting packets missed by the mobile host, while location-registration-update times are reduced by 20-80%. [ABSTRACT FROM AUTHOR]

Abstract The emergence of novel AI technologies and increasingly portable wearable devices have introduced a wider range of more liberated avenues for communication and interaction between human and virtual environments. In this context, the expression of distinct emotions and movements by users may convey a variety of meanings. Consequently, an emerging challenge is how to automatically enhance the visual representation of such interactions. Here, a novel Generative Adversarial Network (GAN) based model, AACOGAN, is introduced to tackle this challenge effectively. AACOGAN model establishes a relationship between player interactions, object locations, and camera movements, subsequently generating camera shots that augment player immersion. Experimental results demonstrate that AACOGAN enhances the correlation between player interactions and camera trajectories by an average of 73%, and improves multi‐focus scene quality up to 32.9%. Consequently, AACOGAN is established as an efficient and economical solution for generating camera shots appropriate for a wide range of interactive motions. Exemplary video footage can be found at https://youtu.be/Syrwbnpzgx8.

The emergence of novel AI technologies and increasingly portable wearable devices have introduced a wider range of more liberated avenues for communication and interaction between human and virtual environments. In this context, the expression of distinct emotions and movements by users may convey a variety of meanings. Consequently, an emerging challenge is how to automatically enhance the visual representation of such interactions. Here, a novel Generative Adversarial Network (GAN) based model, AACOGAN, is introduced to tackle this challenge effectively. AACOGAN model establishes a relationship between player interactions, object locations, and camera movements, subsequently generating camera shots that augment player immersion. Experimental results demonstrate that AACOGAN enhances the correlation between player interactions and camera trajectories by an average of 73%, and improves multi‐focus scene quality up to 32.9%. Consequently, AACOGAN is established as an efficient and economical solution for generating camera shots appropriate for a wide range of interactive motions. Exemplary video footage can be found at https://youtu.be/Syrwbnpzgx8. [ABSTRACT FROM AUTHOR]

The secure authentication of user data is crucial in various sectors, including digital banking, medical applications and e-governance, especially for images. Secure communication protects against data tampering and forgery, thereby bolstering the foundation for informed decision-making, whether managing traffic, enhancing public safety, or monitoring environmental conditions. Conventional visual cryptographic protocols offer solutions, particularly for color images, though they grapple with challenges such as high computational demands and reliance on multiple cover images. Additionally, they often require third-party authorization to verify the image integrity. On the other hand, visual cryptography offers a streamlined approach. It divides images into shares, where each pixel represented uniquely, thus allowing visual decryption without complex computations. The optimized multi-tiered authentication protocol (OMTAP), which is integrated with the visual sharing scheme (VSS), takes secure image sharing to the next level. It reduces share count, prioritizes image fidelity and transmission security, and introduces the self-verification of decrypted image integrity through asymmetric key matrix generators, thus eliminating external validation. Rigorous testing has confirmed OMTAP's robustness and broad applicability, thereby ensuring that decrypted images maintain their quality with a peak signal-to-noise ratio (PSNR) of 40 dB and full integrity at the receiver's end.

Abstract Today, a directional wireless multimedia sensor network is a popular environment for solving the task assignment problem. Achieving long‐term frontal monitoring of moving objects is a crucial challenge for scholars in this field. Utilizing directional sensors equipped with energy harvesting is an effective technique to enhance network performance. In this way, the energy of nodes is no longer limited to batteries and can result in better frontal monitoring. In this method, each sensor categorizes tasks based on its own energy, allowing the determination of task execution nodes through bidding. The present study proposes a distributed algorithm for directional task assignment, EN‐DADA, based on energy harvesting. The task was first classified to determine the candidate node set that could execute the task, and then the task assignment was determined according to the monitoring income of each node in the candidate node set. The comparative analysis confirmed that the proposed method had advantages in terms of task revenue and network lifetime when using the same energy harvesting model.

In the last years multimedia strategies have played a significant role in communicating environmental sustainability policies aimed at affecting changes on a local, regional, and global scale. This article would like to stress the use of animation as a successful multimedia communication tool for promoting responsible consumer choices and sustainable production methods. After a quick overview on the issue of sustainable consumption and production behaviors and the description of relevant examples of animated campaigns produced for supporting organizations, the article reports a didactic experience and describes animated artifacts designed by students to promote the Italian project SfruttaZero, that engages migrants and precarious farmers in the production of local products with the multiple aim to build a fair working environment and to foster a culture of sustainable consumption. [ABSTRACT FROM AUTHOR]

Today, a directional wireless multimedia sensor network is a popular environment for solving the task assignment problem. Achieving long‐term frontal monitoring of moving objects is a crucial challenge for scholars in this field. Utilizing directional sensors equipped with energy harvesting is an effective technique to enhance network performance. In this way, the energy of nodes is no longer limited to batteries and can result in better frontal monitoring. In this method, each sensor categorizes tasks based on its own energy, allowing the determination of task execution nodes through bidding. The present study proposes a distributed algorithm for directional task assignment, EN‐DADA, based on energy harvesting. The task was first classified to determine the candidate node set that could execute the task, and then the task assignment was determined according to the monitoring income of each node in the candidate node set. The comparative analysis confirmed that the proposed method had advantages in terms of task revenue and network lifetime when using the same energy harvesting model. [ABSTRACT FROM AUTHOR]

The user datagram protocol is the most widely used protocol for streaming multimedia data over the Internet. Like other protocols at the network and transport layers, it uses the Internet Checksum (IC) to detect channel errors. The consequence of this is that each corrupted packet is dropped, which can degrade the quality of service perceived by a user. In this paper, the authors present a solution to this problem based on integer codes capable of correcting single and double adjacent errors. The presented codes are a generalization of the IC, which makes them easy to implement in software. [ABSTRACT FROM AUTHOR]

The shift toward fragmented and ubiquitous use of multimedia poses several challenges to our understanding and assessment of multimedia exposure and its effects. This article focuses on multimedia advertising exposure and its impact on consumer behavior. It presents the development of Multimedia Ad Exposure Scale (MMAES) – an instrument designed to measure short-term effects of online multimedia ad exposure in terms of engagement, psychological reactance, awareness and attitude, and purchase intention. The main research challenge has been to identify core dimensions that can reliably measure such exposure, particularly in the context of ad-supported video streaming. The development of MMAES is presented through its conceptualization, operationalization, and an observational study conducted via crowdsourcing. The target group is young adults (ages 18-24, N = 360), digital natives who engage with ad-supported video streaming more than any other user group. Exploratory factor analysis revealed a well-defined four-factor structure of MMAES. The results of the validity and reliability measures show good content and construct validity as well as good overall reliability and very good internal consistency of MMAES. Overall, the results show that MMAES is a reliable instrument for measuring the short-term effects of multimedia ad exposure and its weak ground truth. [ABSTRACT FROM AUTHOR]

Abstract The user datagram protocol is the most widely used protocol for streaming multimedia data over the Internet. Like other protocols at the network and transport layers, it uses the Internet Checksum (IC) to detect channel errors. The consequence of this is that each corrupted packet is dropped, which can degrade the quality of service perceived by a user. In this paper, the authors present a solution to this problem based on integer codes capable of correcting single and double adjacent errors. The presented codes are a generalization of the IC, which makes them easy to implement in software.

Video streaming takes the largest share of internet traffic today, and MPEG dynamic adaptive streaming over HTTP (DASH) has become dominant among other video streaming standards and protocols. According to the DASH standard, multimedia content is encoded in different quality levels with different bitrates located on the server, and users can request multimedia content of any available bitrate. The user side determines the desired bitrate in the unit called adaptation bitrate (ABR) logic. Many ABR algorithms have been proposed to improve the quality of experience (QoE). The main criteria for determining QoE are average bitrate, number of switches between resolutions, and number of buffer underflows. This paper presents a hybrid DASH adaptation algorithm that uses the following input values: current buffer occupancy level, network throughput value calculated on the last downloaded DASH segment, and Takagi-Sugeno-Kang model output that represents expected throughput in the next segment download iteration. We compared the proposed algorithm with several other algorithms and the results show that it outperforms others in average bitrate and number of bitrate switches. Furthermore, our algorithm prevented all buffer underflows.

In order to improve the quality of wireless English multimedia communication, according to the characteristics of space multimedia communication environment and communication equipment, this paper proposes a wireless English synchronous QoS control algorithm with low complexity and easy implementation. Using RTCPSRRTP timestamp and NTP absolute timestamp, the wireless English RTP timestamp is mapped to the same absolute reference clock (sender system time) respectively, and the wireless English synchronization detection decision rule is established according to the synchronization QoS performance requirements between wireless English media. Wireless English synchronization control system model at the receiver. At the receiving end, the wireless English stream is the main media stream and the video stream is the slave media stream. The synchronization detection and judgment is implemented in real time before the video frame is played. The synchronization between audio and video media is realized by corresponding synchronization control of wireless English playback. State space model reflects all the information of system dynamic behavior and is a complete description of system behavior. The state space model has a wide range of applications. It is not only suitable for SISO linear constant systems, but also suitable for nonlinear systems, time-varying systems, MIMO systems and stochastic systems. The more outstanding advantage is that the state space model adopts local calculation and uses the state variables inside the system to describe its dynamic characteristics. This property of local calculation not only greatly simplifies the mathematical expression of multi-dimensional system, but also facilitates the analysis and research of the system. The air link rate of the wireless transceiver is set to 512Kbps. The video is encoded based on H.264 and the audio is encoded based on G.729 Speech coding standard. Compared with the wireless English media synchronization control algorithm based on RTP / RTCP, the results show that the RMSE value after adopting the synchronization algorithm in this paper is reduced by 60.09% and 77.69% at most; Compared with the wireless English media synchronization control algorithm based on RTP / RTCP, the synchronization performance of this algorithm is better than the wireless English media synchronization control algorithm. The RMSE value is reduced by 2% on average and 5.2% at most. In addition, the synchronization control algorithm between wireless English media performs synchronization control by losing frames or pausing decoding before video decoding at the receiver, which affects the quality of wireless English video decoding and reconstruction.

Broadcasting plays a vital role in the consensus mechanisms of blockchain systems, since the consensus of each block must wait until the previous block is received by (nearly) all the nodes in the blockchain systems. Therefore, optimizing the performance of broadcasting can significantly improve the performance of the blockchain system. However, compared with other traditional P2P applications such as file downloading or video delivery, the broadcasting in blockchain has two new requirements, namely low redundancy and low propagation latency, which all the existing mechanisms (e.g. flooding, structural DHT etc.) can not meet well. In this paper, we propose Swift, a new broadcasting mechanism for blockchain systems. It optimizes the P2P topology construction and broadcast algorithm in the structured network based on unsupervised learning and greedy algorithm, effectively reducing the propagation latency of the blockchain P2P network while avoiding the waste of redundant bandwidth. We implemented a prototype of Swift and evaluated its performance on a testbed network that consists of 1000 blockchain nodes. The experimental findings show that Swift can reduce propagation latency by 19.8% with similar bandwidth consumption, generating an 18% increase in the throughput performance of the blockchain. Finally, with the increase in connections, Swift can simultaneously achieve low latency and maintain a relatively stable redundant bandwidth waste, instead of linearly increasing in flooding. [ABSTRACT FROM AUTHOR]

Abstract The recent trends in wireless network sensor technology are moving towards multimedia applications. Multimedia sensor nodes are difficult to communicate, but communication is necessary. Multimedia service offers both video monitoring and voice over wireless sensor networks. This causes severe problems with usage of data, power, bandwidth, energy usage and wireless sensor network deployment costs. The key restriction for the expansion of a network is the energy conservation. The nodes are distributed in the field to collect audio, video and density information so as to collect the information from sensors. The network of wireless sensors provides different layer nodes depending on their power level. In this work, Enhanced Greedy Forwarding with efficient Multi‐path and Dynamic Routing (EGFMDR) protocol was proposed and the results were compared with existing state‐of‐the‐art protocols like Ad‐hoc On‐demand Distance Vector and DYMO. Depending on how powerful they are, multi‐stage architectures were employed in various areas such as observation, military, media and traffic surveillance. They retain the effectiveness of wireless sensor network in multimedia applications. Service quality protocol parameters were analysed, and from the simulation results attained, the proposed EGFMDR protocol displays reduced end‐to‐end delay, lesser packet loss ratio and increased energy efficiency.

The emerging 360-degree video has a good practical prospect in video broadcasting due to its more immersive experience than traditional videos. To maintain a high fidelity with panoramic vision, 360-degree video adopts a significantly increased resolution than planar videos, which also inevitably leads to higher encoding complexity. In this paper, we propose a flexible complexity optimization method for 360-degree video coding, in which the encoder is capable of adapting to different complexity constraints in diversified broadcasting scenarios. In particular, the proposed method is realized with a latitude-based computation complexity allocation. Firstly, it investigates the Coding Unit (CU) partition variation along the latitude (i.e., vertical axis) and divides each video frame into Largest CU (LCU)-based latitude regions. Then, it formulates the complexity allocation problem from the global complexity target to all latitude regions, by considering the intraframe dependencies and Rate-Distortion (RD) models. Finally, it calculates the solution to this complexity allocation problem and further employs it in 360-degree video coding. Comprehensive experiments on the standard dataset reveal the superiority of our method, which achieves a flexible computational time reduction from 14.53% to 68.36% whilst maintaining a high visual quality of compressed videos. [ABSTRACT FROM AUTHOR]

There emerges a strong trend recently to create an intelligent and controllable wireless transmission environment by installing reconfigurable intelligent surfaces (RIS) on the surface of diverse. We research the use of RIS in 5G multicast TV applications in this paper. In particular, the shape-adaptive RIS is developed to relay 5G multicast TV signals and achieve extra RIS gain. To optimize the shape bending in RIS model, we employ the algorithm of Deep Deterministic Policy Gradient (DDPG), a reinforcement learning technique that combines both Q-learning and Policy gradients. Our simulation results show that RIS can considerably enhance the SINR of worst users and improve the system’s overall Modulation and Coding Scheme (MCS) level for 5G mobile broadcasting services. [ABSTRACT FROM AUTHOR]

Currently, an increasing number of technical systems are equipped with multiple cameras. Limited by cost and size, they are often restricted to a single hardware encoder. The combination of all views into a single superframe allows for streaming all camera views at the same time, but it prevents individual rate/quality adaptations on those camera views. We propose a preprocessing filter concept that allows for individual rate/quality adaptation while using a single encoder. Additionally, we create a preprocessor model that estimates the required preprocessing filter parameters from the specified encoding parameters. This means our approach can be used with any existing multi-view adaptation scheme designed for controlling multiple encoders. We design both an analytical and a Machine Learning-based bitrate model. Because both models perform equally well, we suggest using either one as the core part of our preprocessor model. Both models are specifically designed for estimating the influence of the quantization parameter, frame rate, frame size, group of pictures length, and a Gaussian low-pass filter on the video bitrate. Furthermore, the rate models outperform state-of-the-art bitrate models by at least 22% regarding the overall root mean square error. Our bitrate models are the first of their kind to consider the influence of a Gaussian low-pass filter. We evaluate the preprocessing approach by streaming six camera views in a teledriving scenario with a single encoder and compare it to using six individual encoders. The experimental results demonstrate that the preprocessing approach achieves bitrates similar to the individual encoders for all views. While achieving a comparable rate and quality for the most important views, our approach requires a total bitrate that is 50% smaller than when using a single encoder approach without preprocessing. [ABSTRACT FROM AUTHOR]

Pedestrian Dead Reckoning (PDR) is a good alternative positioning method in Global Navigation Satellite Systems (GNSS)-challenged environments. It has the advantage in terms of infrastructure-independent, while the disadvantage is that, the estimated errors grow rapidly with time. The Digital Terrestrial Multimedia Broadcasting (DTMB) signals have strong transmission power, which contributes to better urban propagation and building penetration than GNSS signals. So, in this paper, an enhanced PDR algorithm aided with DTMB signals is proposed. In the study, a complete software-defined radio receiver is developed to estimate the Doppler speed and range information from DTMB signals. To reduce the accumulated errors of the PDR, the Extended Kalman Filter (EKF) algorithm is carried out to fuse the information of Doppler speed and ranging from the DTMB signals, as well as the information of walking speed and heading from the PDR. The results of the field tests showed that the 95% positioning error of the proposed algorithm is less than 3.94 m, while the PDR only is less than 9.19 m, which suggests the effectiveness of the proposed method to provide continuous positioning by fusing DTMB signals with PDR. [ABSTRACT FROM AUTHOR]

Due to the great demand of throughput and reliability for multimedia applications in Fifth Generation (5G) networks, many broadcasting systems adopt the Millimeter Wave (mmWave) technology to address the lack of the spectrum resources. As one of 5G-PPP projects, Internet of Radio Light (IoRL) project adopts 40GHz mmWave band to support a high-speed and stable Ultra-High-Definition (UHD) television broadcasting service in the indoor environment. Because of the high frequency property, mmWave bands usually suffers from the high path loss and the penetration loss. Thus, in order to overcome these issues, directional antennas are employed to provide additional power gain while increasing transmission distance. However, the mmWave with directional antennas brings additional problems, such as limited transmission angle and more multipath effects. Therefore, in this paper, for better understanding of impact factors on the signal quality and transmission coverage of the directional 40GHz mmWave band in the indoor environment, a measurement campaign is introduced in detail and the channel characteristics are measured and analysed in varying cases. The mainly concerned characteristics are path loss, shadow fading, average Power Delay Profile (PDP), Root-Mean-Square (RMS) delay spread, arrival rate and coherence bandwidth. All Measured characteristic values are summarised in three tables at the end of this paper. Besides of these, as a reference of channel analysis and a metric of signal quality and effective coverage, Error Vector Magnitude (EVM) of received signal in each case is measured and discussed. Moreover, a simulation is performed based on a statistical channel model to validate the measured results. [ABSTRACT FROM AUTHOR]

Subcarrier assignment and power allocation for device-to-device (D2D) video transmission using a filter bank multicarrier waveform in a Rayleigh fading environment are investigated. We analyze the co-channel interference between D2D pairs, and propose a cross-layer algorithm with a subcarrier assignment outer loop and a power allocation inner loop, which aims to optimize the overall video quality. Unlike the non-convexity in physical layer power allocation for maximizing the total throughput, the cross-layer power allocation problem is convex under certain conditions, so a high quality solution for power allocation can be efficiently found. Simulation results demonstrate a higher overall video quality by the proposed cross-layer algorithm compared with baseline algorithms.

Despite the recent advances in broadband penetration and accessibility, broadcasting networks continue to be the most efficient way for delivering media content to large areas independently of the user density. Nevertheless, a convergence of broadcasting services into the broadband networks is foreseen. In this context, Layered Division Multiplexing (LDM) allows the joint provision of unicast, multicast, and broadcast services in mobile cells infrastructure. Despite the success of LDM in broadcasting infrastructure, its practical application in Long Term Evolution networks providing Evolved Multimedia Broadcast Multicast Services (LTE eMBMS) and 5G-MBMS is more difficult. In this paper, we experimentally quantify the cell-interference and its impact on the network performance and Quality of Service. Our experiments reveal that the inter-cell interference margin for LTE eMBMS is about 3 dB higher compared to traditional LTE networks. If a layered architecture is incorporated this higher inter-cell interference would cause a reduction of approximately 19% of the Enhanced Layer (Lower Layer) coverage. [ABSTRACT FROM AUTHOR]

With emergence of self-driving vehicles and multimedia rich Internet of Things (IoTs), Inter-Vehicular Communication (IVC) is at rise. IVC has the potential to radically improve the efficiency, safety, and comfort of everyday road travel without needing expensive roadside infrastructure. Nevertheless, a proficient way to quantify and price the multimedia services provided through IVC are yet to be fully investigated. The primary objective of this paper is to develop a Quality of Experience (QoE)-centric pricing model for the multimedia services provided through IVC by seamlessly integrating the multimedia QoE pricing concept. The developed model aims to motivate multimedia-driven vehicle-to-vehicle (V2V) communication by allowing the end-user vehicles to achieve higher QoE and vehicle-to-infrastructure (V2I) by incentivizing neighboring vehicles participating in relaying the multimedia content. Utility maximization between the base station seller, relaying vehicle and the mobile user consumer is modeled using the proposed economic pricing orchestration. Realistically, we translate the three-party interaction into a four-stage Stackelberg game. In addition, we derive the Nash Equilibrium using backward induction and provide an algorithm for future implementation reference. Simulation studies demonstrate the efficacy of developed model and reveal that all three parties achieve reasonable utilities where the Stackelberg equilibrium exists stably. [ABSTRACT FROM AUTHOR]

This work is focused on the system-level performance of a broadcast network. Since all transmitters in a broadcast network transmit identical signals, received signals from multiple transmitters can be combined to improve system performance. We develop a stochastic geometry-based analytical framework to derive the coverage of a typical receiver. We show that there may exist an optimal connectivity radius that maximizes the rate coverage. Our analysis includes the fact that users may have their individual content/advertisement preferences. We assume that there are multiple classes of users with each user class preferring a particular type of content/advertisements and the users will pay the network only when they can see content aligned with their interest. The operator may choose to transmit multiple contents simultaneously to cater to more users’ interests to increase its revenue. We present revenue models to study the impact of the number of contents on the operator revenue. We consider two scenarios for users’ distribution- one where users’ interest depends on their geographical location and the other where it doesn’t. With the help of numerical results and analysis, we show the impact of various parameters including content granularity, connectivity radius, and rate threshold and present important design insights. [ABSTRACT FROM AUTHOR]

Communication pattern is drifting from conventional audio to multimedia applications, streaming live and on-demand digital video contents over telecommunications and broadcasting networks. Currently, some businesses deploy video in promoting products in a far more enriching, entertainment and informative approach than typical traditional audio would allow. However, users of multimedia applications are interested in paying for a good acceptable video quality. Thus, this paper reviews methods used in Peak Signal-to- Noise Ratio (PSNR), Structural Similarity Index Metric (SSIM) and Video Quality Metric (VQM) with the objective of providing useful information to wireless video services providers in assessing and monitoring of quality of multimedia services delivered to users. Experimental comparison of PSNR, SSIM and VQM assessment methods to examine their performances in evaluation of multimedia applications has been performed. Comparing the quality performance of PSNR, SSIM and VQM metrics for Akiyo and Crew standard test sequences, it has been observed that the quality performance of the metrics improves when the bitrates allocation increase. For the test of consistency and quality performance of the metrics, observation shows that for a given bitrates of 3.84Mb/s, under CABA test configuration, Akiyo test sequence, experienced better quality performance of 46.63dB (PSNR), 99.10% (SSIM) and 11.00% (VQM) compared to lower quality performance of 36.18dB (PSNR), 90.40% (SSIM) and 22.00% (VQM) experienced by Crew test sequence. Experimental results of the media quality metrics for Akiyo and Crew standard test sequences with different temporal activity levels show that the quality performance of media content also depends on the temporal activity of the media content. The experimental results further show consistency in quality performance of PSNR, SSIM and VQM metrics for CABA and UBA test configurations. Thus, the objective metrics can be harnessed for evaluation of quality performance of multimedia applications at different channel conditions. [ABSTRACT FROM AUTHOR]

Background: Dementia has become a major public health issue due to its high prevalence and serious consequences. In this context, the use of Information and Communication Technologies (ICT) could provide support for communication between people living with dementia and their formal and informal caregivers, both locally and remotely. More specifically, multimedia communication in the form of digital story narratives might improve communication in such care networks through richer forms of expression of life experiences and care activities. Objective: To explore caregiver perspectives on the communication issues and requirements involved in caring for people with dementia at home, and their reactions to digital storytelling technology as a possible intervention. Method: Semi-structured interviews were carried out with ten community caregivers in a countryside town of Sao Paulo state, Brazil. Each involved discussion of communication issues, and feedback on a mobile digital storytelling app and associated stories. Results: Formal and informal caregivers were both concerned about how to understand and to be understood by the people they were caring for, and saw value in digital storytelling as a new kind of assistive communication tool for more visual communication. Caregivers also wanted better ways of capturing or stimulating memories and conversation in people with dementia and saw digital stories as an extension of current social media systems for sharing life experiences. Conclusion: One of the greatest challenges in caring for people with dementia is communication, especially to understand their feelings, frustrations, and language. Another major challenge is finding time to go beyond caring for their basic activities of daily living (ADL) to enhance their quality of life through more meaningful conversations and experiences. Requirements for new digital storytelling technology were suggested for each of these challenges. [ABSTRACT FROM AUTHOR]

The end users’ satisfactory Quality of Experience (QoE) is a fundamental criterion for networked video service providers such as video-on-demand providers (Netflix, YouTube, etc.), cloud gaming providers (Google Stadia, PlayStation Now, etc.) and videoconferencing providers (Zoom, Microsoft Teams, etc.). To know the QoE, providers today typically predict it from the Quality of Service (QoS) parameters or the client-side's actual QoE metrics measured at the current time-step. But the former does not precisely reflect the users' experience, and the latter has a delay between QoE measurements at the client-side and the user's current experience. Mitigating this delay can provide a noticeable improvement in the delivery system's performance. For example, accurate forecasting of QoE for the near future allows the service management system to take a proactive approach and fix delivery issues before they become a noticeable problem at the end user, or at least reduce overall QoE degradation. QoE forecasting can also be used in rate adaptation in DASH or resource allocation in wireless networks. In this paper, we propose a method to prognosticate QoE metrics. Using data collected from an industry video streaming testbed for three different classes, we define a multivariate time series forecasting problem. We then model a hybrid state-of-the-art deep learning method, BiLSTM-CNN, to forecast the QoE metrics in advance. Evaluation of our proposed method compared to four other well-known ML models of Support Vector Regression (SVR), Multi-Layer Perceptron (MLP), Long short-term memory (LSTM), and Bidirectional LSTM (BiLSTM) demonstrates the superior performance of our proposed method.

Video streaming currently dominates global Internet traffic. Live streaming broadcasts events in real-time, with very different characteristics compared to video-on-demand (VoD), being more sensitive to variations in delay, jitter, and packet loss. The use of adaptive streaming techniques over HTTP is massively deployed on the Internet, adapting the video quality to instantaneous condition of the network. Dynamic Adaptive Streaming over HTTP (DASH) is the most popular adaptive streaming technology. In DASH, the client probes the network quality and adjusts the quality of requested video segment according to the bandwidth fluctuations. Therefore, DASH is an over-the-top application using unmanaged networks to distribute content in the best possible quality. In order to maintain a seamless playback, VoD applications commonly use a large reception buffer. However, in live streaming, the use of large buffers is not allowed because of the induced delay. Active Queue Management (AQM) arises as an alternative to control the congestion in router's queue, pressing the traffic sources to reduce their transmission rate when it detects incipient congestion. In this article, we evaluate the performance of recent AQM strategies for real-time adaptive video streaming. Furthermore, we propose a new AQM algorithm to improve the user-perceived video quality. The results show that the proposed method achieves better performance than competing AQM algorithms and improves the video quality in terms of average peak signal-to-noise ratio while keeping the fairness among concurrent flows. [ABSTRACT FROM AUTHOR]

This study presents the design analysis and correlation properties of a new spreading code for the incoherent synchronous pulse position modulation‐optical code division multiple access (PPM‐OCDMA) networks. The proposed code called optimised modified prime code (OMPC), which refers to the modified prime codes (MPCs) family. Additionally, this new code designed at a higher code length, optimised code weight and good correlation characteristics to enhance communication security and improve the bit error rate (BER) performance. In this study, the proposed code is used as source code for different kinds of multimedia services such as data, voice, and video. Furthermore, the characteristics and correlation properties of the OMPC in comparison with the other MPCs families that utilised in the PPM‐OCDMA networks are presented. Moreover, for the PPM‐OCDMA networks, the effect of OMPC auto‐ and cross‐correlation properties on the multiple access interference (MAI) was investigated. Consequently, the MAI is considered in the BER analysis and calculations. Finally, the results show that the proposed OMPC is better than the other existing codes with respect to the channel capacity and system performance. [ABSTRACT FROM AUTHOR]

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The immense increase in multimedia-on-demand traffic that refers to audio, video, and images, has drastically shifted the vision of the Internet of Things (IoT) from scalar to Multimedia Internet of Things (M-IoT). IoT devices are constrained in terms of energy, computing, size, and storage memory. Delay-sensitive and bandwidth-hungry multimedia applications over constrained IoT networks require revision of IoT architecture for M-IoT. This paper provides a comprehensive survey of M-IoT with an emphasis on architecture, protocols, and applications. This article starts by providing a horizontal overview of the IoT. Then, we discuss the issues considering the characteristics of multimedia and provide a summary of related M-IoT architectures. Various multimedia applications supported by IoT are surveyed, and numerous use cases related to road traffic management, security, industry, and health are illustrated to show how different M-IoT applications are revolutionizing human life. We explore the importance of Quality-of-Experience (QoE) and Quality-of-Service (QoS) for multimedia transmission over IoT. Moreover, we explore the limitations of IoT for multimedia computing and present the relationship between the M-IoT and emerging technologies including event processing, feature extraction, cloud computing, Fog/Edge computing and Software-Defined-Networks (SDNs). We also present the need for better routing and Physical-Medium Access Control (PHY-MAC) protocols for M-IoT. Finally, we present a detailed discussion on the open research issues and several potential research areas related to emerging multimedia communication in IoT.

Wireless traffic produced by modern mobile devices displays high temporal and spatial dynamics as users spontaneously engage in collective applications where a significant portion of generated data remains localized. As a result, conventional service provisioning approaches may no longer be sufficient in beyond fifth generation (B5G) systems. The challenge of increased dynamics on the access networks can be mitigated with moving cells. However, the deployment time of these temporary serving entities may lag behind the service demand lifetime. Another viable solution to offload excessive cellular traffic is to rely upon locally available radio resources offered by user devices via direct mmWave-based mesh interworking. An important challenge in such systems is related to the incentivization of users to partake in collaborative resource sharing. To leverage multi-hop mesh capabilities, we propose the use of emerging blockchain technology that offers cryptographically-strong accounting while maintaining the anonymity of the participants. With system-level evaluations, we demonstrate that the utilization of mobile blockchain methods allows for a non-incremental improvement in the offloading gains. This demonstrates the potential of the outlined proposal for becoming a successful mechanism in the emerging B5G systems.

The aim of this article is to present an architecture to support reconfigurable multimedia services for a practical emergency environment use case of rescue operations. Specifically, radio communication and video surveillance services are provided by means of a small device carried by a mobile vehicle. This solution is validated by implementing a digital mobile radio (DMR) standard radio hotspot and a video streaming server in an unmanned aerial vehicle (UAV) that conveys a device with scarce resources in order to minimize power consumption. To achieve a fast and flexible deployment of the envisioned services, a virtualization-based approach is proposed. Namely, a Kubernetes orchestrator is used to manage the life-cycle of services deployed on a small resource device, endowing the architecture with scalability and management flexibility. This article describes the executed performance tests that measured key parameters such as deployment time and recovery time after disconnection. Highly promising results were obtained, showing that the proposed architecture can be deployed in less than 4 minutes and can recover from network disconnections in less than 10 seconds. Thus, the performance, reliability and flexibility of the overall solution are demonstrated.

We consider an uplink multicarrier system with multiple video users who want to send compressed video data to the base station. In the time domain, we model the time-varying channel using Jakes' model, and in the frequency domain, each subcarrier is assumed to be independently fading. The video is scalably coded in units of a group of pictures (GOP), and users have different video rate distortion (RD) functions. At the beginning of the GOP, the base station collects both the RD information and the instantaneous channel state information (CSI) for subcarrier allocation purposes. We design a cross-layer resource allocation algorithm to assign subcarriers to users based on both the demand of the video and the quality of the channel. Once the resource allocation decision is made, the users then periodically adapt the modulation format of the subcarriers allocated according to the evolution of the CSI for the duration of the GOP. We show that our cross-layer resource allocation robustly outperforms two baseline algorithms, each of which uses only one layer of information for resource allocation.

Quality of experience (QoE) that serves as a direct evaluation of viewing experience from the end users is of vital importance for network optimization, and should be constantly monitored. Unlike existing video-on-demand streaming services, real-time interactivity is critical to the mobile live broadcasting experience for both broadcasters and their audiences. While existing QoE metrics that are validated on limited video contents and synthetic stall patterns have shown effectiveness in their trained QoE benchmarks, a common caveat is that they often encounter challenges in practical live broadcasting scenarios, where one needs to accurately understand the activity in the video with fluctuating QoE and figure out what is going to happen to support the real-time feedback to the broadcaster. In this paper, we propose a temporal relational reasoning guided QoE evaluation approach for mobile live video broadcasting, namely TRR-QoE, which explicitly attends to the temporal relationships between consecutive frames to achieve a more comprehensive understanding of the distortion-aware variation. In our design, video frames are first processed by deep neural network (DNN) to extract quality-indicative features. Afterwards, besides explicitly integrating features of individual frames to account for the spatial distortion information, multi-scale temporal relational information corresponding to diverse temporal resolutions are made full use of to capture temporal-distortion-aware variation. As a result, the overall QoE prediction could be derived by combining both aspects. The results of experiments conducted on a number of benchmark databases demonstrate the superiority of TRR-QoE over the representative state-of-the-art metrics. [ABSTRACT FROM AUTHOR]

This paper is part of the study of writing design (i.e. the graphic sign of writing) and of the concept of movement. It is placed within the context of historical references on the design of writing (as an archaic sign, pictogram, ideogram) and representation technologies (from calligraphy to typography). The relationship between graphic design (writing) and movement (animation) has been addressed in the digital environment through the design of video-graphic products analyzed on the basis of: visual theories of typographic composition; the figurative-generative languages of graphic signs, relational contexts (chromatic, dimensional, formal) along with the integration between image and photo-cinematography (where present); the duration of the audiovisual spot; of the sound component as a key to emotional reading functional to the visual narrative; of communication strategies. Kinetic typography, which integrates movement and writing, is therefore the object of study of this paper. In the field of graphic design and specifically of drawing discipline, two aspects will be evaluated: technological innovation, which made possible the video-graphic representation of the movement while physical time passes; audiovisual languages and compositional criteria for the figurative management of writing and multimedia communication. The realized projects are configured as short-term video-graphic ads and are developed in the context of audiovisual narrative in relation to the creative relationship between writing and: acting; sound; title design; heritage.

This paper presents the results of a study on the evaluation of adaptive transmission of video streams using the DASH technique on Software Defined Networks. There are also presented in this document, the description of the tools required for the implementation of the evaluation, as well as a description of the methodology used for the development of the experiments. In addition, the results of an adaptive transmission of a video by using DASH are presented. This transmission was carried out over a software defined network emulated on MININET. The results show that DASH technique easily allows to implement video streaming services that can adapt the quality of the transmission according to the resources available in the network.

For current steganalysis of the image content-adaptive steganography, there are multiple problems to be improved, such as high difficulty and low accuracy, when detecting images with various contents and textures. For this problem, an improved steganalytic method is proposed in this paper based on the pre-classification and feature selection. First, using the features extracted based on the dependency analysis of image adjacent data, the images with various content and texture complexities are pre-classified as multiple clusters by the K-means algorithms. Then, the performance of existing various steganalytic features are analyzed for different clusters of images, and the optimal features for each cluster are selected for final classification. The experimental results show that the detection accuracy could be improved by the proposed method, and the rationality and availability are also verified. At the same time, the analysis and experimental results in this paper also show that the images with rich content and complex texture should be paid more attention both in steganography and in steganalysis.

With the improvement of mobile device performance, the requirement of equivalent dose description in intensity-modulated radiation therapy is increasing in mobile multimedia for healthcare. The emergence of mobile cloud computing will provide cloud servers and storage for intensity-modulated radiotherapy (IMRT) mobile applications, thus realizing visualized radiotherapy in a real sense. Equivalent uniform dose (EUD) is a biomedical indicator based on the dose measure. In this paper, the dose volume histogram is used to describe the dose distribution of different tissues in target and nontarget regions. The traditional definition of EUD, such as the exponential form and the linear form, has only a few parameters in the model for fast calculation. However, there is no close relationship between this traditional definition and the dose volume histogram. In order to establish the consistency between the EUD and the dose volume histogram, this paper proposes a novel definition of EUD based on the volume dose curve, called VD-EUD. By using a unique organic volume weight curve, it is easy to calculate VD-EUD for different dose distributions. In definition, different weight curves are used to represent the biological effects of different organs. For the target area, we should be more careful about those voxels with a low dose (cold point); thus, the weight curve is monotonically decreasing. While for the nontarget area, the curve is monotonically increasing. Furthermore, we present the curves for parallel, serial, and mixed organs of nontarget areas separately, and we define the weight curve form with only two parameters. Medical doctors can adjust the curve interactively according to different patients and organs. We also propose a fluence map optimization model with the VD-EUD constraint, which means that the proposed EUD constraint will lead to a large feasible solution space. We compare the generalized EUD (gEUD) and the proposed VD-EUD by experiments, which show that the VD-EUD has a closer relationship with the dose volume histogram. If the biological survival probability is equivalent to the VD-EUD, the feasible solution space would be large, and the target areas can be covered. By establishing a personalized organic weight curve, medical doctors can have a unique VD-EUD for each patient. By using the flexible and adjustable EUD definition, we can establish the VD-EUD-based fluence map optimization model, which will lead to a larger solution space than the traditional dose volume constraint-based model. The VD-EUD is a new definition; thus, we need more clinical testing and verification.

With the advancement of multimedia technologies and driven by the ever-increasing user interests in the variety of multimedia applications, the content-rich multimedia streaming services tend to be the most attractive service in future Internet. The multipath TCP (MPTCP), which uses multiple paths for parallel transmission and bandwidth aggregation, is considered to be the most potential transfer mechanism to satisfy the specific requirements of multimedia transmission in a multi-homed wireless network environment. However, the fully-reliable transmission nature of MPTCP can cause an unnecessary retransmission of expired multimedia data, block message from handing over to upper layer, and thus degrade the user-perceived multimedia service quality. In this paper, we propose a receiver-centric partial-reliable multipath transport solution (referred to as $rec$ PR-MPTCP) to support real-time Internet multimedia applications. In the $rec$ PR-MPTCP, a partial reliability extension is presented which runs at receiver side in order to offer a partial reliability multipathing service for multimedia applications. In addition, a new one-way delay-based bandwidth aggregation method is included into the $rec$ PR-MPTCP in order to reduce the receive buffer blocking problem in MPTCP and increase multimedia services performance. Simulation results show that $rec$ PR-MPTCP outperforms the current MPTCP solutions in terms of throughput performance and user-perceived quality of service.

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 multidomain Cloud to Edge networks. The STREK architecture consists of a holistic SDNFV dataplane, NFV servicechaining 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 hardwarebased 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. [ABSTRACT FROM AUTHOR]

Network slicing is a widely discussed technology for 5G broadcasting services, as it allows the operators to create end-to-end virtual slices across the 5G core (5GC) and the 5G radio access network (RAN). The joint network slicing is necessary for 5GC and 5G RAN in a bid to enhance the overall resource utilization and quality of service. Nevertheless, as the dimension of network resource and user demand increase, the computational complexity of slice status update goes up as well. To overcome this scalability problem, we propose a data driven approach to realize joint slice reconfiguration from 5GC to 5G RAN in real-time. Our design shortens significantly the time of slice status update by mapping the resource status to a two-dimensional vector graph. In addition, we also introduce a corresponding slice reconfiguration algorithm to balance the load of each slice in 5GC and 5G RAN. Simulation results justify that our proposed approach can greatly reduce the cost of slice status update and achieve desirable slice reconfiguration performance. [ABSTRACT FROM AUTHOR]

Modern technologies allow for quick processing of digital images. In the era of the Internet, there are many mobile applications supporting the digital processing of photos used on social media. The algorithms of many popular social networks focus on many factors, however, the photography that is placed on a given portal is of great importance. Social media allows you to reach many sources and people. With the help of a good photo, we can get high post reach that contain additional information. The use of mobile applications helps to achieve very good results. This paper presents the results obtained in the process of comparing posts using digital photo processing with those in which the photos were used without processing in a graphics program.