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For each vehicle in a trusted clustering model, its movement is analyzed by vehicle network mobility routing protocol with identified speed and position. The fifth paper entitled "Ant colony optimization-induced route optimization for enhancing driving range of electric vehicles" by Gunasekaran Manogaran et al. proposed a fitness-ant colony optimization (FACO)-based route optimization for improving the driving range of electric vehicles (EVs). The second paper entitled "A SDN-based fine-grained measurement and modeling approach to vehicular communication network traffic" by Liuwei Huo et al. proposed a novel accurate and software defined networking (SDN) based fine-grained traffic measurement approach to obtain comprehensive traffic in VCN. [Extracted from the article]

Summary Delivering health care services in isolated rural regions through vehicular communications has recently attracted more attention. Real‐time video streaming is one of the most commonly used applications in such services. Escorting this increasing interest, there is a high demand for high‐quality streaming video in vehicular environments. However, these services face challenging network characteristics such as high dynamic topology and mobility, leading to high packet loss and degraded visual quality. This paper presents a smart approach to multi‐access terrestrial and non‐terrestrial networks (NTNs) for high‐quality and real‐time video streaming in vehicular environments to enhance healthcare services in remote areas. The proposed approach integrates a mobile telemedicine unit connected to an expert site through different channels, including satellite communication, 5 Generation (5G), and long‐term evolution (LTE) networks. A modified multipath QUIC extension (MPQUIC) was introduced to stream data hybridly through the network. Furthermore, multiple description coding (MDC) was applied to split data into two different descriptions and prioritize one over the other. Important data would be transmitted through cellular networks, and non‐priority data would be transmitted through satellite links, enhancing the reliability of video transmission. We demonstrate the effectiveness of our approach through the use of a connected ambulance as a case study. The Mininet‐Wifi was used to emulate network conditions. The peak signal‐to‐noise ratio (PSNR), structural SIMilarity (SSIM), and video multimethod assessment fusion (VMAF) were measured to evaluate the received video quality; the received data rate and packet loss were also calculated. The obtained results show our proposed method's efficiency by reducing latency by up to 60% and improving the receiving data rate by up to 143% compared with the classical MPQUIC. The proposed system enhances video quality by up to 70%. It minimizes packet loss by up to 50% compared with the unreliable QUIC, showcasing the potential to improve m‐health services' efficiency and mobility in isolated rural regions. [ABSTRACT FROM AUTHOR]

In this paper, we propose a binary feedback scheme for congestion control in computer networks using a gradient-based mechanism which employs neural network modelling of the system dynamics. The optimal direction for rate adjustment at the source is based on a single bit feedback signal which depends upon the sign of the sensitivity of the system performance index with respect to queue input rate. The paper presents the scheme and the analysis that went into the choice of the various decision mechanisms. Simulation results are presented to show the performance of the gradient based technique as compared to the conventional queue-based approach. Copyright © 2000 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The steady improvements in the networking infrastructure and ever increasing broadband penetration has fueled the resurgence of voice-over-IP (VoIP). One of the important contributors to this growth has also been the development and wide acceptance of the session initiation protocol (SIP). However, the current usage of SIP requires a per-application deployment (each application using its own SIP stack). In addition to shared port number problems, this leads to a narrow development of SIP based services, even though SIP, as a protocol, offers incredible opportunities for enabling various applications simultaneously. In this paper, we propose SPLAT—a unified SIP platform, consisting of a client-side SIP service and supporting network infrastructure blocks, that provide unified mechanisms to execute generic SIP functions through an exported higher level API. Applications can leverage the API and ready-made building blocks for creating richer interfaces without significant and often repeated development effort, e.g. a conferencing server coupled with a gaming server can provide context-aware audio conferencing between occupants of a particular game room. Importantly, the SPLAT framework is available to all applications including the ones not inherently based on SIP and thus presents a great opportunity for enhancing such applications. The SIP service API is designed to be extensible and provides novel higher level functional primitives like ad hoc conferencing and seamless transition of sessions. In addition, it also exports a low level interface for specialized applications that need direct access to SIP call flows. Another feature of the service is that it allows a user to plug-in an end device (softphone, IP phone, PSTN phone) of his/her choice on a per-session basis. We demonstrate the richness of the API by describing prototypes for enhancing various applications as well as new converged applications. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The transmission control protocol (TCP) is one of the most important Internet protocols. It provides reliable transport services between two end-hosts. Since TCP performance affects overall network performance, many studies have been done to model TCP performance in the steady state. However, recent researches have shown that most TCP flows are short-lived. Therefore, it is more meaningful to model TCP performance in relation to the initial stage of short-lived flows. In addition, the next-generation Internet will be an unified all-IP network that includes both wireless and wired networks integrated together. In short, modelling short-lived TCP flows in wireless networks constitutes an important axis of research. In this paper, we propose simple wireless TCP models for short-lived flows that extend the existing analytical model proposed in [IEEE Commun. Lett. 2002; 6(2):85–88]. In terms of wireless TCP, we categorized wireless TCP schemes into three types: end-to-end scheme, split connection scheme, and local retransmission scheme, which is similar to the classification proposed in [IEEE/ACM Trans. Networking 1997; 756–769]. To validate the proposed models, we performed ns-2 simulations. The average differences between the session completion time calculated using the proposed model and the simulation result for three schemes are less than 9, 16, and 7 ms, respectively. Consequently, the proposed model provides a satisfactory means of modelling the TCP performance of short-lived wireless TCP flows. Copyright © 2005 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper proposes a multi-dimensional Markov model to analyse the performance of the IEEE 802.11e EDCF MAC protocol. Based on this model, we present extensive performance evaluation in terms of throughput, throughput ratios, and access delay of flows of distinct priorities under RTS/CTS mode. We also provide quantitative analysis of the impact of prioritized parameters, i.e. Arbitration InterFrame Space (AIFS), Contention Window (CW) on Quality of Service (QoS) differentiation. The accuracy of the proposed model is verified by means of comparing the numerical results obtained from both analytical model and simulations. Our research can be used as a guideline for the prediction of how flows belonging to a certain Traffic Category (TC) perform with their TC-specific parameters, as well as designing EDCF-based WLANs and tuning the parameters to achieve the desirable di .erentiated QoS objectives. [ABSTRACT FROM AUTHOR]

Video streaming is expected to account for a large portion of the traffic in future networks, including wireless networks. It is widely accepted that the user datagram protocol (UDP) is the preferred transport protocol for video streaming and that the transmission control protocol (TCP) is unsuitable for streaming. The widespread use of UDP, however, has a number of drawbacks, such as unfairness and possible congestion collapse, which are avoided by TCP. In this paper we investigate the use of TCP as the transport layer protocol for streaming video in a multi-code CDMA cellular wireless system. Our approach is to stabilize the TCP throughput over the wireless links by employing a recently developed simultaneous MAC packet transmission (SMPT) approach at the link layer. We study the capacity, i.e. the number of customers per cell, and the quality of service for streaming video in the uplink direction. Our extensive simulations indicate that streaming over TCP in conjunction with SMPT gives good performance for video encoded in a closed loop, i.e. with rate control. We have also found that TCP is unsuitable (even in conjunction with SMPT) for streaming the more variable open-loop encoded video. Copyright © 2004 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Wireless IP networks will provide voice and data services using IP protocols over the wireless channel. But current IP is unsuitable to provide delay or loss bounds and insufficient to support diverse quality of service, both required by real-time applications. In order to support real-time applications in wireless IP networks, in this paper a measurement-based admission control (MBAC) with priority criteria and service classes is considered. First we have shown the suitability of MBAC in wireless IP networks by comparing its performance with a parameter-based scheme. Next, we have investigated the performance of strictly policy-based MBAC and policy plus traffic characteristic-based MBAC schemes in terms of (1) increasing the user mobility, (2) changing traffic parameters and (3) the presence of greedy users. The efficiency and fairness of each scheme are measured in terms of lower class new and handoff traffic performance. Copyright © 2003 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper studies the performance of radio assignment algorithms for portable access in cellular systems. Several channel access procedures are proposed and simulated using block oriented network simulator (BONeS) simulation of a model 36-port system. Simulation results exhibit that load-sharing system with LIBTA algorithm is better than directed retry system with the same algorithm by around 0.9 erlangs while better than quasi-fixed channel assignment (QFCA) system by around 2 erlangs if the grade of service (GOS) is constrained to less than 10 per cent. Plus, a hybrid time-slot selection procedure is proposed to enhance the system performance. It is observed that systems with hybrid time-slot selection perform better than those with LIBTA algorithm in GOS under heavy load. It is also observed that load sharing system with hybrid time-slot selection algorithm is better than directed retry system with the same algorithm by around 0.7 erlangs and better than QFCA system by around 2 erlangs. Copyright © 2001 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Power assignment schemes are man-made methods to enhance the capture effect of radio communications. In a previous study, Wen and Yang investigated the combined capture effect of the fixed power assignment scheme, Rayleigh fading, and near–far effect on the performance of packet radios. The performance analysis was limited to an infinite population environment. This assumption is reasonable for a conventional packet radio system with a vast service area. However, for a cellular mobile system, a finite population model should be used. In this paper, we analyse the combined natural and man-made capture effect on the performance of a cellular system with finite population in each cell. A random power assignment scheme is adopted to produce the man-made capture. The system throughput and delay are carried out by a Markov model. Some numerical calculations are used to demonstrate the degree of performance improvement. Copyright © 2001 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, a combined trellis coded quantization/modulation (TCQ/TCM) scheme is introduced for the wireless local-loop environment modelled with realizable and practical medium parameters. The performance analysis of the combined system is carried out through the evaluation of signal-to-quantization noise ratio (SQNR) versus signal-to-noise ratio (SNR) curves and bit error probability upper bounds. Simulation studies confirm the analytical results. Copyright © 2000 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The concept of a person-based number is attractive due to several pressing demands in implementation of current wireless communication systems. Some of these are: sudden proliferation in number of area codes; the need for freedom from number changes due to changes in service provider, location, or area code; and demand for improved and integrated communication service for users. Some important factors that determine the efficiency of a mobility management scheme include fewer number of times that locations need to be updated, reduced amount of overhead data that represents mobility related information, and efficient storage mechanisms that allow for fast storage and retrieval of this information. In this paper, we shall outline a mobility management scheme that provides a globally unique personal number and offers important benefits in regard to the issues cited above. For an efficient implementation of such a scheme however, an investigation of its performance is required in order to estimate signaling traffic and signaling delays. This paper will focus on some recent studies conducted on an analysis of this scheme by using query and update operations as the metrics for determining average call delay and control data storage and transmission requirements. A comparative analysis is also performed with equivalent cases of query and update in the IS-41 system. This analysis provides a valuable tool to determine network management requirements in the implementation of a person-based number scheme. Copyright © 1999 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

A method and a technique for the probability of error estimation in digital channels with memory are developed and demonstrated. The expressions for the mean and variance of a random variable, representing a block of bits transmission in a bursty channel (channel with memory), are derived. The influence of the memory is expressed by a parameter called the memory factor. It is shown that the traditional Monte Carlo method can be applied for the probability of error estimation. In order to control the accuracy and increase the time efficiency of estimation this method is modified and a new method, called the modified Monte Carlo method, is proposed. Based on this modified method a technique of estimation with controlled accuracy is developed and demonstrated using data obtained by simulation. According to this technique the sample size is adjusted in the course of estimating procedure to give an accurate estimate of the probability of error for a minimum required time of estimation. Copyright © 2003 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In order to extend fair queueing algorithms to wireless networks, we propose a channel error and handoff compensation scheme. A compensation is performed by a compensation server and a priority swapping mechanism. The proposed compensation scheme provides a short-term fairness guarantee for an error-free session, long-term fairness guarantee for an erroneous session, fast handoff and traffic-specific quality of service control. Copyright 2002 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The traditional cable TV network has recently emerged as a promising infrastructure for high-speed data communications such as the Internet and multimedia. A cable TV network may cover a wide range of geographical area that thousands of subscribers live in or work at. However, this broad service range also brings some problems such as bandwidth congestion due to too many users, and the overhead in the design of access protocol. This article presents a bridged architecture that can increase the bandwidth re-usability and data transmission reliability over the cable TV network. It first describes the method of bridging the cable TV networks and then gives the design of a cable bridge which partitions the cable segment into several subnetworks. For load-balancing and fairness among subnetworks, a prioritized queuing scheme with a numerical analysis will be also described. Copyright © 2000 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary: Fire is a serious threat to human life and property, and effective prediction of fire can reduce the harm of fire to human. In the research of fire alarm automation, the fire alarm system based on wireless sensor network is a common method. When using wireless sensor to monitor the fire alarm information, it is necessary to ensure the safety coverage of the network in the monitoring area. Therefore, it is very necessary to study the network coverage in the fire alarm monitoring, which can ensure the effective work of the monitoring network, and good coverage control can reduce the energy consumption of the network and extend the service life of the network. Based on this, this paper designs a network coverage control algorithm based on multiobjective genetic algorithm optimization considering the coverage and energy consumption of wireless network. In this algorithm, the probability perception model is used to design the network coverage control model for the monitoring area with different coverage requirements, taking the maximum area coverage and the minimum network energy consumption rate as the optimization goal. Then the genetic algorithm is used to solve the model. In addition, because the multiobjective genetic algorithm is easy to fall into the local optimal solution when solving the optimization problem, this paper introduces the cross and variation coefficients of self‐adaptive adjustment to improve the genetic algorithm. Through the simulation analysis, it is shown that when solving the multiobjective optimization problem, the introduction of self‐adaptive adjustment of cross and variation coefficients can well overcome the problem that genetic algorithm falls into the local optimal solution, whereas the network coverage control algorithm designed in this paper based on the multiobjective genetic algorithm optimization can achieve greater coverage and lower energy consumption. Compared with the network coverage control algorithm before optimization, the optimized algorithm improves greatly in coverage, network residual energy, and number of nodes, which can well extend the service life of wireless sensor network, and is conducive to the good application of wireless sensor in fire prediction. [ABSTRACT FROM AUTHOR]

Summary: The Internet of Things (IoT) is a system of physical objects embedded with various sensors to receive information, software, chips, and other technologies that allow connecting and transferring data to other devices through the Internet without human intervention. As the number of smart devices increase, IoT has started to be applied in many more fields. Therefore, there is a lot of information that should be processed. To manage this amount of data, some researchers proposed the usage of big data techniques. Big data are a collection of structured and unstructured data incoming with a high speed and large amounts. This paper investigates big data applications in IoT to comprehend the different published approaches using the systematic literature review (SLR) technique. This paper systematically studies the latest research methods on big data in IoT approaches published between 2016 and August 2021. A methodical taxonomy is shown for big data in IoT‐related fields consistent with the content of existing articles chosen with the SLR process in this research like healthcare, smart city, algorithms, industry, and general aspects in those environments. The advantages and drawbacks of each paper are presented, with specific proposals for stating their pros and cons open issues and advising possible research challenges in big data implementation in the IoT. The evaluation factors of big data applications in IoT are distributed as follows: security (18%), throughput (17%), cost (17%), energy consumption (15%), reliability (15%), response time (9%), and availability (9%). [ABSTRACT FROM AUTHOR]

Summary: In recent years, wireless sensor networks (WSNs) have been widely used in various applications. The localization problem has been identified as one of the biggest problems faced by WSNs. The traditional localization techniques may not be able to handle the issues during the scenario to estimate the location of sensor nodes due to anchor mobility, mobile WSNs, latency, energy harvesting, unfavorable environmental states, and many more issues. However, these issues open the door for the amalgamation of machine learning (ML) and optimization techniques with localization techniques. Motivated by the earlier discussion, we explored various ML and optimization techniques to estimate the location coordinates in a sensor network in this paper. Finally, a comparison of existing ML algorithms concerning optimization techniques has been presented, highlighting their improved outcomes. This research offers a detailed survey by exploring the various parameters for location estimation through tabular forms by incorporating ML and optimized localization techniques. A survey of surveys is also presented to identify the key limitations of existing surveys and to introduce the novelty in the comprehensive study done in this paper. A year‐wise evaluation of ML Techniques with localization (2011–2022) is also discussed and presented over various performance parameters, including energy‐efficiency, accuracy, error, and complexity. This discussion concluded that Hybrid Techniques are least explored for using optimized localization machine learning. Further, a summarized discussion of the various comparison tables paves the path for future research in the area of localization in WSN. [ABSTRACT FROM AUTHOR]

Summary: Art painting is a very important major in China's education system. Under the background of the new era, the country vigorously promotes the modernization of education and the development of intelligence. Many subjects of teaching have been more mature and carried out intelligent teaching based on virtual reality technology. But throughout the art painting profession, the research on this aspect is almost blank. The main reason is that there are deep academic barriers between art painting and computer science. Therefore, this paper puts forward the application research of multi‐source information art painting fusion interactive 3D dynamic scene virtual reality technology. This paper deeply analyzes the needs of art painting and its teaching reform and believes that the existing virtual reality technology cannot adapt to the teaching environment of art painting. In view of the possible inaccurate calculation and other problems, this paper puts forward the optimization scheme. The core of the scheme is to use the information integration advantages of multi‐source information fusion to provide more comprehensive and complete object information for 3D modeling of virtual reality technology, so as to improve the imaging quality of virtual reality technology. In order to meet the requirement of high precision, the calculation method is optimized, the calculation steps are simplified, and the sensor selection is optimized again. This paper introduces the design principle and operation steps of the optimization method in detail. In order to further verify the actual effect of this method, comparative analysis method is used to test the comprehensive performance. In order to ensure the test quality, the median filtering algorithm and fuzzy algorithm are compared. Through the analysis and comparison of the data, the optimization method in this paper greatly improves the accuracy of calculation and the comprehensive performance is improved. [ABSTRACT FROM AUTHOR]

Summary: Intelligent fire safety systems place higher demands on the speed and reliability of data communication between sensors, controllers, and other devices. The two‐wire bus has become a significant trend in developing fire safety communication systems because of its low cost and simple maintenance. This paper proposes a two‐wire bus communication system for fire safety based on orthogonal frequency division multiplexing (OFDM) technology. First, we introduce the low‐voltage power line channel model and conduct relevant simulations, providing the conditions for subsequent simulation work. Then, we design the system's transmission and reception schemes, provide the parameters, and introduce each technology used. Finally, we conducted system simulations based on three different channel models, and the system performance is compared among different encoding, modulation, and channel estimation methods. The simulation results show that the system designed in this paper has superior performance compared with other systems and can meet the requirements of intelligent fire safety systems for communication speed and reliability. [ABSTRACT FROM AUTHOR]

Summary Location‐based underwater communication applications such as strategic surveillance, disaster prevention, marine research, and mine detection have given the field of underwater wireless sensor networks (UWSN) a head start. Node localization is a prerequisite for accurate data collection, target monitoring, and network management in UWSNs. However, the unique characteristics of the underwater environment, such as signal attenuation, multipath propagation, and variable acoustic properties, pose a major challenge to effective node localization. Accurate sensor node location data is essential for successful underwater data collection, but difficult to achieve as the GPS system cannot be used in an underwater environment. In this paper, existing node localization techniques such as ALS, SLUM, MASL, SLMP, UDB, USP, etc., and recent advances such as the fusion of range‐based and range‐free techniques, the fusion of RSSI and AoA to improve localization accuracy by using directional information in addition to signal strength, and the use of optimization techniques such as PSO, COA, and WOA algorithms to improve the accuracy of the applied node localization algorithm, e.g., TP‐TSFLA, and challenges related to UWSN are discussed. Also, different localization algorithms that affect the accuracy of UWSN localization techniques have been evaluated and compared with NS2 in terms of localization error, localization coverage, energy consumption, and average communication cost metrics. In addition, this paper also provides an up‐to‐date investigation of localization techniques. Finally, the tools available for simulation are presented, followed by open research questions that need to be addressed in the localization of nodes. [ABSTRACT FROM AUTHOR]

Summary The increasing prevalence of MIMO technology in wireless communication networks is attributed to its ability to augment system capacity and dependability. Consequently, there is a notable enthusiasm for the advancement and implementation of S‐band applications. Nevertheless, the mutual coupling between numerous antennas presents a crucial obstacle to MIMO system performance. This paper presents a novel technique that utilizes a defective ground structure with parasitic components to increase antenna isolation and gain. Additionally, an L‐shaped slot is incorporated into the patch element to enhance the antennas impedance bandwidth. Antennas are intentionally placed in a perpendicular arrangement to minimize the impact of the coupling effects. The antenna exhibits an impedance bandwidth in the frequency range of 2.62–2.79 GHz. Furthermore, the utilization of a four‐element MIMO antenna setup with a defective ground structure yields outstanding isolation properties, with values notably lower than −25 dB. To achieve an optimal MIMO performance, we assessed various diversity parameters, including diversity gain, channel capacity loss, total active reflection coefficient, and envelope correlation coefficient. The parameter values were within acceptable limits (ECC < 0.04, DG = 10 dB, TARC < 0 dB, and CCL < 0.1 bits/s/Hz). This research paper therefore offers essential insights into the design and optimization of MIMO antennas specifically for 2.7 GHz applications. [ABSTRACT FROM AUTHOR]

Summary: 5G and beyond (5GB) systems show a flexible characteristic to meet different user communications requirements in parallel. Multi‐numerology waveform design is an important part of this human centric characteristic, however, it is necessary to make multi‐numerology planning. In this paper, the integrated sensing and communications (ISAC) concept is used with machine learning (ML) techniques to develop an intelligent numerology control mechanism for 5GB. Thanks to the ISAC capabilities, an environment‐aware system is designed, and several useful sensing information (USI) that affect the wireless channel characteristic is utilized. It is assumed that the USI is obtained through 5GB smart city networks. At that point, synthetic data generation is performed to form a new dataset with USI‐based features. Additionally, a novel feature control algorithm is proposed in the paper. Lastly, simulation results are presented for different type of ML models including several ensemble methods. [ABSTRACT FROM AUTHOR]

Summary: Autonomy is becoming a prime requirement for satellite mission control operations. Data‐driven methods like Machine Learning models are playing a key role in bringing in autonomy. Health keeping data from satellite telemetry is a key ingredient in these data‐driven methods. In real‐world satellite operations, the health‐keeping telemetry data gradually drifts due to adverse space weather effects and wear and tear of electronic and mechanical components. The key question that arises is how to detect and quantify the data drift which is generally a gradual phenomenon. This paper discusses a novel statistical method for detecting data drift occurring in satellite telemetry. For the purpose of experimental work in this paper, an actual telemetry data set of the BUS CURRENT sensor which is part of the Electrical Power System of a Low Earth Orbit Satellite was considered. Data drift detection test was carried out using this sensor data using the developed novel statistical method and with Kolmogorov Smirnov test which is a probabilistic method. Both results are analysed and compared. Thereafter novel statical method was used to check its efficacy using a synthetic data set with induced drift. [ABSTRACT FROM AUTHOR]

Summary: In this paper, we study a UAV‐based fog or edge computing network in which UAVs and fog/edge nodes work together intelligently to provide numerous benefits in reduced latency, data offloading, storage, coverage, high throughput, fast computation, and rapid responses. In an existing UAV‐based computing network, the users send continuous requests to offload their data from the ground users to UAV–fog nodes and vice versa, which causes high congestion in the whole network. However, the UAV‐based networks for real‐time applications require low‐latency networks during the offloading of large volumes of data. Thus, the QoS is compromised in such networks when communicating in real‐time emergencies. To handle this problem, we aim to minimize the latency during offloading large amounts of data, take less computing time, and provide better throughput. First, this paper proposed the four‐tier architecture of the UAVs–fog collaborative network in which local UAVs and UAV–fog nodes do smart task offloading with low latency. In this network, the UAVs act as a fog server to compute data with the collaboration of local UAVs and offload their data efficiently to the ground devices. Next, we considered the Q‐learning Markov decision process (QLMDP) based on the optimal path to handle the massive data requests from ground devices and optimize the overall delay in the UAV‐based fog computing network. The simulation results show that this proposed collaborative network achieves high throughput, reduces average latency up to 0.2, and takes less computing time compared with UAV‐based networks and UAV‐based MEC networks; thus, it can achieve high QoS. [ABSTRACT FROM AUTHOR]

The article calls on individuals to submit research papers addressing issues about implementing mobile multimedia communications over heterogeneous infrastructure for realizing next-generation networking and computing. The cited topics include new emerging multimedia applications and architectures like wireless sensor system for video surveillance, video communication over next-generation networks, and emerging technologies for multimedia communications. Instructions on how to submit a research paper are also given.

The article calls for papers related to the theme "Interdisciplinary and Cross-layer Design of Mobile Social Networks and Wireless Networks."

The article presents an introduction to papers related to ubiquitous computing for communications and broadcasting published within the issue.

A call for papers on Next Generation Networks (NGN) is presented.

The article encourages authors to submit papers on ubiquitous wireless mesh networks and Internet access.

Summary: Artificial intelligence, which simulates the behavior of the human brain with a computer, including learning, reasoning, decision‐making and prediction, association, and other aspects, with the help of artificial intelligence technology to help visual communication designers complete high‐quality, efficient, and high‐volume design output, has become a trend. However, there are many defects in the existing visual design and creation system under the intelligent human–computer cooperation. Therefore, based on 5G virtual reality, this paper proposes the framework of visual design and creation system under intelligent human–computer cooperation research that has been carried out. This paper uses the method of literature analysis and other methods to study. In the research process, based on 5G virtual reality, this paper builds the framework of visual design and creation system under the intelligent human–computer cooperation of virtual reality and tests the visual design creation system based on 5G virtual reality from the aspects of response time, visual design completion time, and visual presentation effect; the system is compared with other intelligent human–computer cooperation visual design creation systems. The results show that the clarity score of this system is 96.5, the visual presentation quality score is 95.8, the clarity score of other systems is 87.6, and the visual presentation quality score is 86.3. Therefore, this system has very high superiority compared with other intelligent human–computer cooperation visual design and creation systems. [ABSTRACT FROM AUTHOR]

Summary: 5G virtual reality technology is a technology that has attracted widespread attention in the computer field in recent years. Establishing a harmonious human–computer interaction environment in the multidimensional information space is one of the development goals of information technology. Face information is important information for identifying the identity of others. Three‐dimensional information has important applications in many fields and directions of machine vision. Therefore, the three‐dimensional common face image has a significant meaning. In this paper, binocular stereo vision system is used to collect multiple pairs of facial information images. The image correction method was used to correct the collected image pairs. According to the basic criteria of stereo matching, the advantages and disadvantages of various traditional image matching methods are analyzed. On the basis of completing the image correction, the graph cut matching method is selected as the matching method, and multiple pairs of collected image pairs are matched by this method to obtain a multi‐angle face disparity map. In this paper, after studying the basic dense matching algorithm and its improved algorithm, the SAD, SD, and NC methods of fixed window are used to compare the matching cost and the performance of the adaptive weight method in face matching. This paper studies the virtual roaming technology and the basis of the related Internet of Things (IoT) 3D face graphics theory and develops a building virtual roaming system based on MFC and OpenGL. The system draws on the basic I/0 device of the computer and provides users with a friendly MFC interface and multiple viewing angles and multiple roaming mode options for virtual faces. Experimental research shows that the reconstruction accuracy of the spatial points of the reconstructed face and the actual situation are both about 1%, which shows that the IoT 3D face modeling algorithm designed in this paper has high accuracy. [ABSTRACT FROM AUTHOR]

Summary: The Internet of Things (IoT) is a rapidly growing trend within many domains, such as automotive, avionics, automation, energy, and health. IoT architecture is the system of numerous elements, including sensors, protocols, actuators, cloud services, and layers. IoT architecture plays an important role to provide desired services. Nowadays, tens of IoT architectures are provided by the research community. Many challenges have been identified by the research community, including interoperability, security and privacy, reliability, energy constraints, scalability, and lack of common standards. However, to provide suitable IoT architecture, the importance and priority of requirements in different scenarios may vary, and requirement analysis should be regarded. To this end, this paper presents a systematic mapping survey to give a review of IoT architecture and provide a structured overview of research trends. Moreover, a technical taxonomy is presented for these challenges according to reviewed studies. This classification model can be used as a guideline for future works. [ABSTRACT FROM AUTHOR]

Summary: The Internet of Vehicles (IoV) is an emerging network of connected vehicles as a branch of dynamic objects in the Internet of Things (IoT) ecosystem. With the rapid development of IoV, real‐time data‐centric applications would be a significant concern in academia and industry to promote efficiency and realize modern services in such high dynamic networks. In this paper, we aim to present a systematic literature review (SLR) for the IoV networks to investigate the different attitudes in the field of data‐centric approaches. This paper systematically categorizes the 48 recent articles on data‐driven techniques in the IoV field published from 2017 to March 2022. A complete technical taxonomy is presented for the data‐centric approaches in IoV according to the content of current studies. Collected methods are chosen with the SLR process, and they are investigated considering some technical classifications including IoV security, data traffic, vehicular social network, data propagation, energy, and multimedia categories. The achievements, drawbacks, and new findings of studies are carefully investigated for addressing the deficiencies, as well as emphasizing future research direction and open issues of data‐driven approaches in IoV. [ABSTRACT FROM AUTHOR]

Summary: By incorporating on‐demand resources, software and data for collaborative services through the Internet, the conventional Information Technology enterprise has been transformed by cloud computing. Based on the pay‐per‐use approach, Infrastructure, platform or Software resources and servers located across data centres are among the several types of resources offered to consumers in cloud computing. Data centres handle these resources. These resources are constantly provisioned to users based on their availability, demand, and quality requirements. Cloud computing systems are known as one of the largest utilisers of energy resources all over the world. Also, power consumption has become a crucial aspect as most cloud computing systems work on traditional nonrenewable resources of energy. In order to make data centres environment‐friendly, there is a need for optimal approaches to reduce energy consumption and their hazardous effects on the environment. To analyse different available strategies for building and maintaining an energy‐efficient cloud is the main objective of this paper. The paper will comprehensively review several energy‐efficient resource provisioning methods and provide a graphical comparative study of Quality of Service (QoS) Metrics in cloud computing. Moreover, the present study identifies the areas of study that need to be further improved to increase the energy efficiency of cloud computing systems. [ABSTRACT FROM AUTHOR]

Summary: The growth of small communication devices has pushed designers to design compact‐size antennas. These antennas must be low cost, lightweight, needed for mechanically robust construction, and ease of installation. In this paper, we use a novel genetic algorithm (GA) to produce an ensemble of compact self‐avoiding (SA) antennas such that the voltage standing wave ratio (VSWR) is less than 2 at the desired frequencies (as a measure of efficiency); an optimization criterion to get a desirable multiband antenna in the ultra high frequency (UHF) band. First, the electromagnetic properties of these antennas are simulated using the method of moments in MATLAB. SA antennas form a particular set of dipoles introduced here by applying a novel backtracking algorithm. We also use a Lindenmayer system that generates the geometries by a Turtle graphics render to reach our goal. Next, we simulate the VSWR for 150,000 SA antennas with lengths L from 0.1 to 0.4 m; 10 different frequencies are chosen randomly within the UHF band to obtain our results. All the VSWR ≤ 2 are clustered using density‐based spatial clustering of applications with noise algorithm (DBSCAN), so our method provides the frequency ranges where this condition is fulfilled. From this, we obtain the VSWR minimums used for the antenna design. Finally, as an instance, we use our results to select the appropriate size of a multiband antenna and, through genetic algorithms, modify the geometry to satisfy the design requirements. [ABSTRACT FROM AUTHOR]

Summary: Many sorts of services in the cloud environments must be composited based on the user's requests to meet the requirements. Thus, the distributed services are joined to the cloud services through service composition. Also, it is known as NP‐hard problems and many researchers significantly are focused on this problem in recent years. Therefore, many different nature‐inspired meta‐heuristic techniques are proposed for solving this problem. The nature‐inspired meta‐heuristic techniques have an important role in solving the service composition problem in the cloud environments, but there is not a wide‐ranging and detailed paper about reviewing and studying the important mechanisms in this field. Therefore, this study presents a comprehensive analysis of the nature‐inspired meta‐heuristic techniques for the service composition issue in the cloud computing. The review also contains a classification of the important techniques. These classifications include Ant Colony Optimization, Bee Colony Optimization, Genetic Algorithm, Particle Swarm Optimization, Cuckoo Optimization Algorithm, Bat Algorithm, greedy algorithm, and hybrid algorithm. An important aim of this paper is to highlight the emphasis on the optimization algorithms, and the benefits to tackle the challenges are encountered in the cloud service composition. Also, this paper presents the advantages and disadvantages of the nature‐inspired meta‐heuristic algorithms for solving the service composition problem in the cloud environments. Moreover, this paper aims to provide more efficient service composition algorithms in the future. Finally, the obtained results have shown that the discussed algorithms have an important effect in solving the cloud service composition problem, and this effect has been increased in recent years. [ABSTRACT FROM AUTHOR]

Summary: In recent years, applying Internet of Things (IoT) applications has significantly increased to facilitate and improve quality of human life activities in various fields such as healthcare, education, industry, economics, etc. The energy aware cloud‐edge computing paradigm has developed as a hybrid computing solution to provide IoT applications using available cloud service providers and fog nodes for the smart devices and mobile applications. Since the IoT applications are developed in the form of several IoT services with various quality of service (QoS) metrics which can deploy on the cloud‐edge providers with different resource capabilities, finding an efficient placement solution as one of challenging topics to be measured for IoT applications. The service placement issue arranges IoT applications on the cloud‐edge providers with various capabilities of atomic services though sufficient different QoS factors to support service level agreement (SLA) contracts. This paper presents a technical analysis on the cloud‐edge service placement approaches in IoT systems. The key point of this technical analysis is to identify substantial studies in the service placement approaches which need additional consideration to progress more efficient and effective placement strategies in IoT environments. In addition, a side‐by‐side taxonomy is proposed to categorize the relevant studies on cloud‐edge service placement approaches and algorithms. A statistical and technical analysis of reviewed existing approaches is provided, and evaluation factors and attributes are discussed. Finally, open issues and forthcoming challenges of service placement approaches are presented. [ABSTRACT FROM AUTHOR]

Summary: A sensor network is a situation‐based critical network defined under certain restrictions and constraints. The clustered architecture is defined over these networks to utilize the criticality vectors and to improve network communication. In this paper, a degree load‐balanced and fuzzy‐ACO (DLB‐fACO) protocol is proposed for optimizing the clustered architecture. In this architecture, the load analysis is performed while forming the clusters. The cluster head selection is performed based on energy, cluster density, and probability vector. The node degree‐ and energy‐balanced analysis is performed for identifying the cluster members. Once the clusters are formed, the ACO approach is applied to perform the cluster‐based hierarchical routing. Communication is performed at two levels. In the first level, node‐to‐cluster head communication is performed by considering energy and degree consideration. In the second level, the fuzzy‐integrated ACO method is applied for inter‐cluster route formation. The route optimization is here performed under fuzzy‐based energy, degree, and distance parameters. These fuzzy parameters are evaluated within the ACO algorithm for generating the optimized route. The proposed load‐balanced protocol is analyzed against the LEACH, LEACH‐C, LEACH‐CC, M‐LEACH, Fuzzy‐PSO, Fuzzy‐ACO, Fuzzy‐Cuckoo, and FMCB‐ER protocols. The experimentation results confirm the significant gain in network lifetime and packet communication. The cluster count, clustering switching, and communication failure are also reduced in comparison with existing conventional and optimized protocols. [ABSTRACT FROM AUTHOR]

Summary: In the presence of noise in communication systems, constellation diagram points are scattered to the extent that may make the modulation classification a difficult task. With the plethora of applications of machine and deep learning, several communication systems have adopted machine and deep learning to solve some classical detection and classification problems. Casting the modulation order detection as a pattern classification of the constellation images opens the door for application of mature machine learning and image processing tools to solve the classification problem, efficiently. This paper presents a system based on a wavelet‐aided convolutional neural network (CNN) classifier to efficiently detect the modulation type and order in the presence of noise. The proposed system depends on a pretrained CNN setup, which is trained with a set of constellation diagrams for each modulation scheme and used after that for testing. In addition, discrete wavelet transform (DWT) is investigated to generate representative patterns from constellation diagrams to be used for the training and testing tasks as well. The wavelet approximation images and their corresponding wavelet sub‐bands across all predefined scales are used in the dataset. Several pretrained networks including AlexNet, VGG‐16, and VGG‐19 are used as classifiers for the modulation type from the DWTs for different constellation diagrams. Several simulation experiments are presented in this paper to compare different scenarios for modulation classification at different signal‐to‐noise ratios (SNRs). [ABSTRACT FROM AUTHOR]

Summary: With the continuous proliferation of sensing technology, it has become possible to utilize energy harvesting (EH)‐enabled sensor nodes for a variety of applications. However, conventional wireless sensor networks (WSNs), that is, those without EH‐enabled nodes, still have limited applicability due to their limited battery resources. Further, the utilization of EH‐enabled nodes in the network not only imposes a financial burden on the user but also limits its performance due to its dependence on environmental conditions. To address this concern, in this paper, we propose the EH‐enabled energy‐efficient routing (EHEER) technique for green communication in WSN. The predominant concern being addressed in this paper is the selection of cluster head (CH), which helps in gathering, aggregating and forwarding the data from the cluster‐based routing paradigm. We use the spotted hyena optimizer (SHO) algorithm for optimizing the fitness parameters for CH selection, namely, energy ratio, distance considerations, node density, load balancing and the network's average energy. We use EH‐enabled nodes in the network strategically so as to keep control over the costs incurred in the network. The simulation outcomes empirically prove the efficacy of the proposed work, as it effectively increases the network stability and operational period by a huge margin as compared to the existing techniques. [ABSTRACT FROM AUTHOR]

Summary: This paper investigates optimizing the collaborative energy power consumption between nodes with energy harvesting (EH) capability at the fusion center (FC) and multi‐antenna sensors using game theory. Using multi‐antennas at FC on sensor networks (SNs), we can benefit from the spatial diversity in receiving the data and using multi‐antenna sensors and energy to transfer the data and optimize the SN, respectively. Also, in this paper, the data transmission in the network is formulated by considering the limitations of storage resources of each sensor, minimum data receiving, minimum EH, and maximum collaboration among sensors. In this paper, some modes are suggested to minimize the collaborative energy among sensors for transmitting the data and energy among sensors in the collaboration of sensors to optimize the power control and allocation power policy. Suggestions have been studied based on the number of antennae to transmit, using the cooperative games in sharing the data and the energy and auction game in transmitting to FC. The simulation results of the proposed problem using MATLAB software show optimization in participation function, EH, allocation in cooperation time, and transferring to FC to improve the detection of the transmitted data based on the increasing number of antennas in FC. [ABSTRACT FROM AUTHOR]

Summary: This paper evaluates the performance of a spectral‐amplitude‐coding optical code division multiple access (SAC‐OCDMA) system over a free space optical (FSO) communication link under various weather conditions such as fog, snow, and rain. The system uses different code families, including modified quadrature congruence (MQC), random diagonal (RD), and diagonal eigenvalue unity (DEU), to address user codes and reduce the effects of multiple access interference (MAI). The system's bit error rate (BER) performance has been analyzed taking into account receiver noises and MAI, and calculates the required optical power for a BER value of 10−9 under different weather conditions. The results show that fog has the most significant impact on the system's performance, while rainy conditions require the lowest optical power. The performance of the system also declines with increasing transmission length and concurrent user count. Finally, the paper compares the performance of different code families under unfavorable weather conditions and concludes that DEU performs better than MQC and RD in bad weather. [ABSTRACT FROM AUTHOR]

Summary: In the era of big data, massive amounts of data hold great value. However, much data exists as isolated islands, and the maximum value of the data cannot be fully utilized. Federated learning allows each client to train local data and then share the training model parameters securely, which can address the isolated data island problem and exploit data value while ensuring data privacy and security. Accordingly, in order to securely complete the electric power load forecasting using existing data, this paper constructs a federated learning‐based privacy‐preserving scheme to support electricity load forecasting in edge computing scenarios. To address the problems of the data‐isolated islands and data privacy in electric power systems, this paper proposes a decentralized distributed solution based on the federated learning technique. Our scheme achieves electricity load forecasting for power systems through the federated learning‐based framework and uses edge computing architecture to improve real‐time data capability and reduce network latency. For the hierarchical scheduling structure in power systems, we divide the system into a cloud‐side‐device three‐layer architecture, which achieves structural coordination and balance, and each layer collects information according to the scheduling control tasks, promoting scheduling effectiveness. Finally, different privacy protection methods are used on the cloud‐edge and edge‐device sides to significantly enhance data security. Moreover, We have conducted extensive experimental simulations for our proposed scheme. The experimental results show that the relative error of electricity load forecasting is around 1.580%. Meanwhile, our scheme achieves high accuracy and low memory usage. The security analysis proves the feasibility and security of our scheme. [ABSTRACT FROM AUTHOR]

The article calls for submissions of articles on the topic "Secure Communications and Data Management in Ubiquitous Services."