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Communication over the wireless has significantly evolved to the level where it is capable of supporting the essential controlling mechanisms of the high-definition automated industrial process. The Fifth-Generation (5G) mobile networking air-based interface, named New Radio (5GNR), is presently capable of adopting scalable control and subband data transmission for small data packets, which has made it efficiently compatible for the critical controlling application of industrial automation processes. The minimum cycle time is used as a reliable parameter for an indication of the healthy techniques for industrial wireless telecommunication, but it has not undergone deep investigation within the framework of modern 5G technology. For addressing such types of challenges, this paper has taken into consideration 5G-based industrial automation process control through wireless networking by using a delay optimization approach associated with data-base channel control using the Ant Colony Optimization (ACO) approach for solving the proposed evaluation of a reliable minimum cycle time over 5G network communication. [ABSTRACT FROM AUTHOR]

In this paper, we study the relaying and cache aided digital grid data transmission, where the relaying may be equipped by caching or not, depending on specific applications. For both cases, we evaluate the impact of relaying and caching on the system performance of digital grid data transmission through theoretical derivation. To this end, an analytical expression on the outage probability is firstly derived for the data transmission. We then provide an asymptotic expression on the system outage probability. Finally, some simulation results are provided to verify the correctness of the derived analysis on the system performance, and show the impact of relaying and caching on the data transmission of digital grid system. In particular, the usage of caching at the relaying can help strengthen the data transmission performance of the considered system effectively. The results in this paper could provide some reference to the development of wireless transmission and scalable information systems. [ABSTRACT FROM AUTHOR]

Fire incidents can have severe consequences, including loss of life, property damage, and disability. Industries like nuclear power plants, refineries, and chemical factories are susceptible to major fires. To address this, a fire control robot has been developed, reducing the need for human intervention. Fire accidents are common in daily life, posing challenges for firefighters. In such cases, firefighting robots play a vital role. Simultaneously, surveillance robots have become pivotal in security, industrial monitoring, and home automation. A low-cost, efficient surveillance robot using ESP32-CAM has been created for indoor and outdoor use. These robots offer remote monitoring through the ESP32 CAM module, providing Wi-Fi and Bluetooth connectivity for remote control and data collection. They integrate seamlessly, capturing high-quality imagery and videos, which are wirelessly transmitted for analysis. The ESP32 CAM module offers several advantages, including high-quality data capture, remote control, and wireless data transmission, making it suitable for various applications such as security and monitoring. Combining fire control with surveillance capabilities ensures safety and provides valuable insights. This paper presents a combined design for a fire detection and suppression robot with surveillance capabilities. The robot uses flame and temperature sensors to detect fires and employs various methods to extinguish them. It also features an ESP-32 camera for real-time fire monitoring and can be controlled remotely via a smartphone or tablet. [ABSTRACT FROM AUTHOR]

With the continuous development of science and technology, UAV technology has been widely used in various fields. As an essential part, light and small UAV platforms have the advantages of being small, lightweight, and easy to operate and thus have been widely used in aerial photography, monitoring, rescue, and other fields. However, the traditional data transmission method can no longer meet the demand for the data transmission speed and stability of small and light UAV platforms. Wireless optical communication has the advantages of being high-speed and license-free, as well as having a large bandwidth strong anti-interference ability, and good confidentiality. Therefore, this paper aims to study high-speed data transmission technology for light and small UAV platforms to improve their transmission speed and stability. In this paper, the characteristics and advantages of UAV airborne laser communication are first elaborated to illustrate the advancements and importance of data transmission technology based on light and small UAV platforms. Then, the composition of a UAV airborne laser communication system is clarified to illustrate the feasibility of conducting airborne laser communication research. Then, the current domestic and international research status of people on light and small UAV airborne laser communication high-speed data transmission systems is reviewed, and its key technical features are analyzed. Finally, the prospects for its application and development trend are investigated. [ABSTRACT FROM AUTHOR]

The 8b/10b IBM encoding scheme is used in a plethora of communication technologies, including USB, Gigabit Ethernet, and Serial ATA. We propose two primitive-based structural designs of an 8b/10b encoder and two of an 8b/10b decoder, all targeted at modern AMD FPGA architectures. Our aim is to reduce the amount of resources used for the implementations. We compare our designs with implementations resulting from behavioral models as well as with state-of-the-art solutions from the literature. The implementation results show that our solutions provide the lowest resource utilization with comparable maximum operating frequency and power consumption. The proposed structural designs are suitable for resource-constrained data communication protocol implementations that employ the IBM 8b/10b encoding scheme. This paper is an extended version of our paper published at the 2022 International Symposium on Electronics and Telecommunications (ISETC), Timisoara, Romania, 10–11 November 2022. [ABSTRACT FROM AUTHOR]

This paper presents the design and implementation of an ISO-compliant ocean profiling observation systemfor wave-powered vertical profiler. This systemaims to provide a comprehensive, scalable, and interoperable solution for high- resolution, real-time oceanic observation. As a part of this system, we introduce a wave-powered vertical profiler, known as "Wave Master," designed to offer enhanced stability and reliability for long-term oceanic data collection. The core of the paper focuses on the Ocean Profiling Observation Complex Virtual Instrument (OPO-CVI), a comprehensive system developed in alignment with ISO 21851 standard. OPO-CVI seamlessly integrates data collection, transmission, storage, and visualization. Specifically, OPO-CVI addresses the challenges of information isolation, system rigidity, and lack of modularity in traditional ocean profiling methods by standardizing data formats and transmission protocols, allowing for seamless integration of new observation elements, and employing a modular architecture for enhanced scalability and reusability. By offering detailed technical insights into the OPO-CVI architecture and its compliance with ISO 21851 standard, this paper aims to contribute significantly to the advancement of standardized, efficient, and reliable oceanic observation systems. [ABSTRACT FROM AUTHOR]

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As mobile communications transform, 5G technology can potentially change many industries and businesses. The change will have a great influence across many fields, such as the automotive, healthcare, and manufacturing sectors. This paper aims to review the existing applications of blockchain technology in providing 5G network security and identify new possibilities for such security solutions. We consider different aspects of blockchain in 5G, particularly data transmission, access control, and applications including vertical industry-oriented applications and specific solutions supporting such sectors of economic activity. The paper briefly describes modern technologies in 5G networks and introduces blockchain's properties and different aspects of using such technology in practical applications. It also presents access control management with blockchain applied in 5G and related problems, reviews other blockchain-enforced network technologies, and shows how blockchain can help in services dedicated to vertical industries. Finally, it presents our vision of new blockchain applications in modern 5G networks and beyond. The new-generation networks use two fundamental technologies, slicing and virtualization, and attackers attempt to execute new types of attacks on them. In the paper, we discuss one of the possible scenarios exhibiting the shortcomings of the slicing technology architecture. We propose using blockchain technology to create new slices and to connect new or existing subscribers to slices in the 5G core network. Blockchain technology should solve these architectural shortcomings. [ABSTRACT FROM AUTHOR]

The fast advance and evolution of technology in Internet of Things (IoT) is a double-edged sword, striking with new performant solutions and backfiring with a lot of unanswered questions. Due to cheap manufacturing costs and large-scale production, sensors, actuators and even microcontrollers are not designed with security on the first place. Also, the IoT market is a new one and that means that it is still unregulated and there isn’t a well-defined set of standards to control and manage better these problems. The IoT ascent has impacted many industries, but probably the most changes were made to the Supply Chain Management (SCM) industry. The forementioned question of cheap devices that need to be manufactured with a minimum of costs, very fast and ready to be deployed, is digging a big security hole in this kind of ecosystems. This paper aims to discuss the challenges involved in hardening de security in embedded devices, protecting the data and the communication channels between an IoT node and an IoT gateway and finally, assuring the persistence of data and its security after is stored. All these matters are addressed with privacy and security in design. Because SCM is a multiparty ecosystem that involves many different actors each with its tasks and data handling components, it is important to assure the fact that they will not interfere, tamper, or profit in a bad manner of each other. One solution for this problem is decentralization that comes with strings attached. Finally, and on short, this paper will try to describe a security model based on decentralization in a SCM flow, addressing its threats and how they can be overcome. [ABSTRACT FROM AUTHOR]

This paper investigates the integration of relay-assisted Internet of Things (IoT) systems, focusing on the use of multiple relays to enhance the system performance. The central metric of interest in this study is system outage probability, evaluated in terms of latency. Our research provides a comprehensive analysis of system outage probability, considering different relay selection criteria to optimize the system's transmission performance. Three relay selection strategies are employed to enhance the system transmission performance. Specifically, the first strategy, optimal relay selection, aims to identify the relay that minimizes the latency and maximizes the data transmission reliability. The second approach, partial relay selection, focuses on selecting a subset of relays strategically to balance the system resources and achieve the latency reduction. The third strategy, random relay selection, explores the potential of opportunistic relay selection without prior knowledge. Through a rigorous investigation, our paper evaluates the impact of these relay selection criteria on the performance of relay-assisted edge computing systems. By assessing the system outage probability in relation to latency, we provide valuable insights into the trade-offs and advantages associated with each selection strategy. Our findings contribute to the design and optimization of reliable and efficient edge computing systems, with implications for various applications, including the IoT and intelligent data processing. [ABSTRACT FROM AUTHOR]

This review paper discusses the development trends of agricultural autonomous all-terrain vehicles (AATVs) from four cornerstones, such as (1) control strategy and algorithms, (2) sensors, (3) data communication tools and systems, and (4) controllers and actuators, based on 221 papers published in peer-reviewed journals for 1960–2023. The paper highlights a comparative analysis of commonly employed control methods and algorithms by highlighting their advantages and disadvantages. It gives comparative analyses of sensors, data communication tools, actuators, and hardware-embedded controllers. In recent years, many novel developments in AATVs have been made due to advancements in wireless and remote communication, high-speed data processors, sensors, computer vision, and broader applications of AI tools. Technical advancements in fully autonomous control of AATVs remain limited, requiring research into accurate estimation of terrain mechanics, identifying uncertainties, and making fast and accurate decisions, as well as utilizing wireless communication and edge cloud computing. Furthermore, most of the developments are at the research level and have many practical limitations due to terrain and weather conditions. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks (WSNs) have emerged as an efficient solution for numerous real-time applications, attributable to their compactness, cost-effectiveness, and ease of deployment. The rapid advancement of 5G technology and mobile edge computing (MEC) in recent years has catalyzed the transition towards large-scale deployment of WSN devices. However, the resulting data proliferation and the dynamics of communication environments introduce new challenges for WSN communication: (1) ensuring robust communication in adverse environments and (2) effectively alleviating bandwidth pressure from massive data transmission. In response to the aforementioned challenges, this paper proposes a semantic communication solution. Specifically, considering the limited computational and storage resources of WSN devices, we propose a flexible Attention-based Adaptive Coding (AAC) module. This module integrates window and channel attention mechanisms, dynamically adjusts semantic information in response to the current channel state, and facilitates adaptation of a single model across various Signal-to-Noise Ratio (SNR) environments. Furthermore, to validate the effectiveness of this approach, the paper introduces an end-to-end Joint Source Channel Coding (JSCC) scheme for image semantic communication, employing the AAC module. Experimental results demonstrate that the proposed scheme surpasses existing deep JSCC schemes across datasets of varying resolutions; furthermore, they validate the efficacy of the proposed AAC module, which is capable of dynamically adjusting critical information according to the current channel state. This enables the model to be trained over a range of SNRs and obtain better results. [ABSTRACT FROM AUTHOR]

With the advent of 6G Narrowband IoT (NB-IoT) technology, IoT security faces inevitable challenges due to the application requirements of Massive Machine-Type Communications (mMTCs). In response, a 6G base station (gNB) and User Equipment (UE) necessitate increased capacities to handle a larger number of connections while maintaining reasonable performance during operations. To address this developmental trend and overcome associated technological hurdles, this paper proposes a hardware-accelerated and software co-designed mechanism to support streaming data transmissions and secure zero-trust inter-endpoint communications. The proposed implementations aim to offload processing efforts from micro-processors and enhance global system operation performance by hardware and software co-design in endpoint communications. Experimental results demonstrate that the proposed secure mechanism based on the use of non-repeating keys and implemented in FPGA, can save 85.61%, 99.71%, and 95.68% of the micro-processor's processing time in key block generations, non-repeating checks, and data block transfers, respectively. [ABSTRACT FROM AUTHOR]

This paper begins by exploring the challenge of event-triggered state estimations in nonlinear systems, grappling with packet dropout and correlated noise. A communication mechanism is introduced that determines whether to transmit measurement values based on whether event-triggered conditions are violated, thereby minimizing redundant communication data. In designing the filter, noise decorrelation is initially conducted, followed by the integration of the event-triggered mechanism and the unreliable network transmission system for state estimator development. Subsequently, by combining the three-degree spherical–radial cubature rule, the numerical implementation steps of the proposed state estimation framework are outlined. The performance estimation analysis highlights that by adjusting the event-triggered threshold appropriately, the estimation performance and transmission rate can be effectively balanced. It is established that when there is a lower bound on the packet dropout rate, the covariance matrix of the state estimation error remains bounded, and the stochastic stability of the state estimation error is also confirmed. Ultimately, the algorithm and conclusions that are proposed in this paper are validated through a simulation example of a target tracking system. [ABSTRACT FROM AUTHOR]

Cloud computing has data leakage from all parties, security protection of private data, and existing solutions do not provide a trade-off between security and overhead. With distributed data communication due to data barriers, information interaction security and data computation security have become challenges for secure computing. Combining cloud computing with secure multiparty computation can provide a higher level of data protection while maintaining the benefits of cloud computing. In this case, data can be stored in the cloud and computed through SMPC protocols, thus protecting the privacy and security of the data. However, multiple rounds of information interaction are often required, increasing the communication overhead, and the security strength is limited by the hardness assumption. In this paper, we work to achieve an optimal setting of the number of rounds in secure multi-party computation on the cloud to achieve a sublinear communication overhead and improve the security concept. A 2-round SMPC protocol is constructed in the framework of Universally Composable (UC). A 2-round SMPC protocol is constructed that uses multilinear maps based on the Learning from Errors (LWE) assumption. The participant encodes the input and sends it via broadcast to reduce the interaction, homomorphic computational encoding information for secure access to computational data and secure the SMPC protocol through UC security. This paper extends the participants to multiple parties, reduces the communication rounds to 2, the protocol achieves sublinear communication overhead in poly polynomial time, smaller setup size to poly(k), and static security is achieved. [ABSTRACT FROM AUTHOR]

This paper mainly studies the deployment of hybrid sensors on highways. By constructing the deployment location constraint model, the overall accuracy of sensor deployment can be maximized. In addition, in order to meet the needs of intelligent transportation, the consideration of traffic data communication is added to the work. The highway under study is first divided into several units, and the combination type of sensors is used to represent the possible layout of two adjacent sensors. Then, a 0–1 optimization model reflecting the interaction between the sensor position and the server position is established. Then, a two-step search algorithm is proposed to find the optimal solution of the model and determine the deployment scheme with maximum accuracy. Finally, an example is given to verify the method. The results show that there are significant differences between uniform unit-deployment schemes and non-uniform unit-deployment schemes. Through the sensitivity analysis of each factor, the influence of budget and communication radius on the deployment plan is proven. In addition, the ramp length can also have a negative impact on the target value. [ABSTRACT FROM AUTHOR]

In today’s interconnected digital landscape, safeguarding sensitive data has become paramount. Recognizing this imperative, our study directs its focus towards enhancing data security by means of the practical implementation of the Internet Protocol Security (IPsec) protocol. Tailored for network managers and cybersecurity specialists, our research endeavors to demystify the intricacies of IPsec, offering a comprehensive exploration that spans both theoretical insights and actionable recommendations. Delving into the core features of IPsec- authentication, encryption, and secure key exchange-we aim to provide a lucid roadmap for users grappling with the multifaceted challenges of data security. Through a meticulous blend of theoretical elucidation and practical application, this brief conference paper serves as a vital bridge between theory and practice. By equipping individuals with the requisite knowledge and tools, our study empowers them to navigate the dynamic landscape of cybersecurity with confidence. With an emphasis on information confidentiality and integrity, our research endeavors to fortify defenses against the ever-evolving array of cyber threats. [ABSTRACT FROM AUTHOR]

Based on the distribution characteristics of railway video acquisition points, this paper classifies the section video collection points, analyzes the access requirements of the line patrol platform, and puts forward the construction scheme of line patrol platform, which includes four parts: line patrol center platform, station and depot patrol screens, workshop patrol terminals and data transmission channels. The line patrol center platform adopts the cloud collaboration technology to analyze, upload, and alarm on-site video stream, and is connected to the railway comprehensive video monitoring system and other external systems to share resources. Stations and depots are equipped with large patrol screens, and workshops are equipped with patrol terminals. Based on the characteristics of patrol platform construction, a supporting channel construction is proposed. This platform has three major functions including professional management enhancement, intelligent technical defense, and patrol strategy optimization. This paper provides the reference for the construction of railway line patrol platforms. [ABSTRACT FROM AUTHOR]

In this paper, a bulk arrival and two-phase bulk service with active Bernoulli feedback, vacation, and breakdown is considered. The server provides service in two phases as mandatory according to the general bulk service rule, with minimum bulk size ′ a ′ and maximum bulk size ′ b ′ . In the first essential service (FES) completion epoch, if the server fails, with probability ′ δ ′ , then the renewal of the service station is considered. On the other hand, if there is no server failure, with a probability ′ 1 − δ ′ , then the server switches to a second essential service (SES) in succession. A customer who requires further service as feedback is given priority, and they join the head of the queue with probability β . On the contrary, a customer who does not require feedback leaves the system with a probability ′ 1 − β ′ . If the queue length is less than ′ a ′ after SES, the server may leave for a single vacation with probability ′ 1 − β ′ . When the server finds an inadequate number of customers in the queue after vacation completion, the server becomes dormant. After vacation completion, the server requires some time to start service, which is attained by including setup time. The setup time is initiated only when the queue length is at least ′ a ′ . Even after setup time completion, the service process begins only with a queue length 'N' (N > b). The novelty of this paper is that it introduces an essential two-phase bulk service, immediate Bernoulli feedback for customers, and renewal service time of the first essential service for the bulk arrival and bulk service queueing model. We aim to develop a model that investigates the probability-generating function of the queue size at any time. Additionally, we analyzed various performance characteristics using numerical examples to demonstrate the model's effectiveness. An optimum cost analysis was also carried out to minimize the total average cost with appropriate practical applications in existing data transmission and data processing in LTE-A networks using the DRX mechanism. [ABSTRACT FROM AUTHOR]

The UAV-borne video SAR (ViSAR) imaging system requires miniaturization, low power consumption, high frame rates, and high-resolution real-time imaging. In order to satisfy the requirements of real-time imaging processing for the UAV-borne ViSAR under limited memory and parallel computing resources, this paper proposes a method of embedded GPU-based real-time imaging processing for the UAV-borne ViSAR. Based on a parallel programming model of the compute unified device architecture (CUDA), this paper designed a parallel computing method for range-Doppler (RD) and map drift (MD) algorithms. By utilizing the advantages of the embedded GPU characterized with parallel computing, we improved the processing speed of real-time ViSAR imaging. This paper also adopted a unified memory management method, which greatly reduces data replication and communication latency between the CPU and the GPU. The data processing of 2048 × 2048 points took only 1.215 s on the Jetson AGX Orin platform to form a nine-consecutive-frame image with a resolution of 0.15 m, with each frame taking only 0.135 s, enabling real-time imaging at a high frame rate of 5 Hz. In actual testing, continuous mapping can be achieved without losing the scenes, intuitively obtaining the dynamic observation effects of the area. The processing results of the measured data have verified the reliability and effectiveness of the proposed scheme, satisfying the processing requirements for real-time ViSAR imaging. [ABSTRACT FROM AUTHOR]

This paper examines the performance of Full-Duplex Cooperative Rate Splitting (FD-CRS) with Simultaneous Wireless Information and Power Transfer (SWIPT) support in Multiple Input Single Output (MISO) networks. In a Rate Splitting Multiple Access (RSMA) multicast system with two local users and one remote user, the common data stream contains the needs of all users, and all users can decode the common data stream. Therefore, each user can receive some information that other users need, and local users with better channel conditions can use this information to further enhance the reception reliability and data rate of users with poor channel quality. Even using Cell-Center-Users (CCUs) as a cooperative relay to assist the transmission of common data can improve the average system speed. To maximize the minimum achievable rate, we optimize the beamforming vector of Base Station (BS), the common stream splitting vector, the cooperative distributed beam vector and the strong user transmission power under the power budget constraints of BS and relay devices and the service quality requirements constraints of users. Since the whole problem is not convex, we cannot solve it directly. Therefore, we propose a low complexity algorithm based on Successive Convex Approximation (SCA) technology to find the optimal solution to the problem under consideration. The simulation results show that FD C-RSMA has better gain and more powerful than FD C-NOMA, HD C-RSMA, RSMA and NOMA. [ABSTRACT FROM AUTHOR]

The Argo buoy detects marine environmental data by making profile movements in the ocean and transmits the profile detection data to the shore base through the communication terminal. However, due to the large volume of data collected from profile detections and the continuous operation of the terminal, the remote communication of buoys is characterized by lengthy communication times and significant power consumption. A low-power Beidou transparent transmission terminal is designed to solve these problems in this paper. The terminal performs low-power operation management and power management for terminal remote communication. After the end of a communication process, the microcontroller turns the Beidou module power off and enters STOP mode. Before the next communication process begins, the serial port wakes up the microcontroller, which powers up the Beidou module. Before the remote communication, the microcontroller compacts the profile detection data collected by the buoy to reduce the quantity of remote communication data. In this paper, a variety of data compression methods are used to compare the compression rate, and the best compression method is selected according to the format characteristics of the data. The results show that the Beidou transparent transmission terminal of the Argo buoy can realize low power consumption for remote communication in ocean exploration. The terminal reduces power consumption by 77.282% per communication, and the average number of remote communications for each profile detection data are reduced by 55 times. The low-power Beidou transparent transmission terminal improves the battery life and is conducive to the long-term operation of the buoy. [ABSTRACT FROM AUTHOR]

Effective data communication is a crucial aspect of the Social Internet of Things (SIoT) and continues to be a significant research focus. This paper proposes a data forwarding algorithm based on Multidimensional Social Relations (MSRR) in SIoT to solve this problem. The proposed algorithm separates message forwarding into intra- and cross-community forwarding by analyzing interest traits and social connections among nodes. Three new metrics are defined: the intensity of node social relationships, node activity, and community connectivity. Within the community, messages are sent by determining which node is most similar to the sender by weighing the strength of social connections and node activity. When a node performs cross-community forwarding, the message is forwarded to the most reasonable relay community by measuring the node activity and the connection between communities. The proposed algorithm was compared to three existing routing algorithms in simulation experiments. Results indicate that the proposed algorithmsubstantially improves message delivery efficiency while lessening network overhead and enhancing connectivity and coordination in the SIoT context. [ABSTRACT FROM AUTHOR]

Background and Objectives: Reliable data transmission and congestion control are considered as the transport layer primary functions in Wireless Sensor Networks (WSNs). WSNs are a specific category of wireless ad-hoc networks where their performance is highly affected by their characteristics and limitations. These limitations necessitate an effective data transport control in WSNs which considers quality of service (QoS), energy efficiency, and congestion control. Methods: Congestion affects normal data transmission and ends in packet loss. Furthermore, wireless channels introduce packet loss because of high bit-error rate which wastes energy and affects reliability. The major problems regarding transport protocols in WSNs are congestion and reliability where the latter is classified and reviewed in the current paper. Results: In this paper, reliable data transport protocols are classified as the traffic direction, the parameter the reliability focuses on, and loss detection, notification, and recovery. Traffic direction-based reliable data transport protocols can be upstream, downstream or bidirectional, however, the parameter-based ones can be packet-based, event-based or destination-based, the loss detection and notification-based ones can be ACK-based, NACK-based, ACK and NACK-based or SACK-based, and the loss recovery-based reliable data transport protocols can be E-2-E or H-by-H. Thereafter, a comprehensive review of different reliable data transport protocols in wireless sensor networks is presented. Also, different performance metrics are used to compare these schemes. Conclusion: In this paper, reliable data transport protocols in WSNs are classified, reviewed and compared using different performance metrics. Finally, the current work attempts to provide specific directives to design and develop novel reliable data transport protocols in wireless sensor networks. [ABSTRACT FROM AUTHOR]

In this paper, a design model for resource allocation is formulated beyond 5G networks for effective data allocations in each network nodes. In all networks, data is transmitted only after allocating all resources, and an unrestrained approach is established because the examination of resources is not carried out in the usual manner. However, if data transmission needs to occur, some essential resources can be added to the network. Moreover, these resources can be shared using a parallel optimization approach, as outlined in the projected model. Further the designed model is tested and verified with four case studies by using resource allocator toolbox with parallax where the resources for power and end users are limited within the ranges of 1.4% and 6%. Furthermore, in the other two case studies, which involve coefficient determination and blockage factors, the outcomes of the proposed approach fall within the marginal error constraint of approximately 31% and 87%, respectively. [ABSTRACT FROM AUTHOR]

Ultra-Reliable Low Latency Communication (URLLC) is mostly used for core services in the fifth generation (5G) and beyond cellular networks. Due to the conflicting demands of low latency and extremely high reliability, the ongoing research on this subject remains in its nascent phase. The utilization of Device-to-Device (D2D) communication shows great potential in facilitating URLLC. The implementation of URLLC and its Quality of Service (QoS) requirements may encounter high power consumption in dynamic wireless channels, potentially conflicting with the system's power limitations. In this paper, a packet delivery mechanism is introduced, aiming to achieve energy efficiency by incorporating a Power-Aware QoS-centric Preemptive Dropping mechanism to minimize latency while ensuring the successful transmission of URLLC data. The method aims to optimize bandwidth and channel assignment to effectively reduce overall power consumption. The optimization problem is formulated which is non-convex, posing challenges in selecting an optimal solution. To address this problem, we have undertaken the task of transforming the original problem into two subproblems: bandwidth allocation and subchannel assignment. To achieve optimal resource allocation for the formulated problem, we propose the Optimal Bandwidth Allocation (OBA) and Optimal Sub-channel Assignment (OSA) algorithms. The simulation results validate the proposed method outperforms the benchmark schemes, demonstrating higher energy efficiency ranging from 6.96 to 31.6%, as well as a reduction in latency ranging from 5.7 to 25.67%. The proposed method exhibits broad applicability in various domains, including remote healthcare and Industrial Internet of Things (IIoT) applications. [ABSTRACT FROM AUTHOR]

Fog computing and the Internet of Things (IoT) have revolutionized healthcare monitoring systems, enabling real-time health data collection and transmission while overcoming cloud computing limitations. However, efficiently selecting fog nodes for application modules with varying deadline requirements and ensuring adherence to quality of service (QoS) criteria pose significant challenges due to resource constraints and device limitations. In this paper, we present a novel two-layered hierarchical design for fog devices, leveraging cluster aggregation to optimize the selection of fog nodes for healthcare applications. We introduce three efficient algorithms to minimize system latency and reduce energy consumption in fog computing environments. Our proposed model is rigorously evaluated using the iFogSim toolkit and compared with cloud-based and latency-aware model [Mahmud R, Ramamohanarao K, Buyya R in ACM Transactions on Internet Technology.19, 2018, 10.1145/3186592]. In four distinct network topologies, our model exhibits an average latency reduction of at least 87% and energy consumption reduction of at least 76% when compared to the Cloud-based model. Similarly, when compared to the Latency-aware model proposed in [Mahmud R, Ramamohanarao K, Buyya R in ACM Transactions on Internet Technology. 19, 2018, 10.1145/3186592], our model showcases a minimum reduction of 43% in average latency and 27% in energy consumption. Our contribution lies in addressing the complexity of selecting fog nodes for application modules with diverse deadline requirements, while ensuring QoS. This work advances the field of real-time healthcare monitoring systems, promising substantial improvements in efficiency and effectiveness. [ABSTRACT FROM AUTHOR]

Background Aims Methods Main Contribution Conclusions WHAT THIS PAPER ADDS What is already known on the subject What this paper adds to existing knowledge What are the clinical implications of this work? Communication impairments are a leading concern for parent caregivers of individuals with rare neurodevelopmental disorders (RNDDs). Clinical trials of disease modifying therapies require valid and responsive outcome measures that are relevant to individuals with RNDDs. Identifying and evaluating current psychometric properties for communication measures is a critical step towards the selection and use of appropriate instruments.This systematic review offers (1) a description of parent‐reported communication measures and (2) evidence for their psychometric properties, in RNDDs.The systematic review protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO; CRD42022334649). MEDLINE (Ovid), Embase, PsychINFO, Web of Science, CINAHL Plus, Cochrane Library, ClinicalTrials.gov, the Australian New Zealand Clinical Trials Registry were searched from inception to August 2023. Methodological assessment of quality was completed using the COnsensus‐based Standards for the selection of health status Measurement INstruments (COSMIN) checklist. Parent‐reported measures used in observational studies and clinical trials were identified. Data on utility, reliability and validity for RNDDs were extracted.Sixteen parent‐reported communication measures were used in RNDD research, the Vineland Adaptive Behavior Scales being most commonly used. Validation data in RNDDs were identified for six of these measures. Limitations related to sample size or the scope of psychometric testing.Many communication measures have been used for RNDDs but there are few data validating their use. Valid and reliable methods of measuring communication in persons with RNDDs is a priority for future high‐quality clinical trials. Communication is a critical domain for families with a child with a rare neurodevelopmental disorder (RNDD). Validated outcome measures are essential for accurate evaluation and interpretation of responses to treatments in clinical trials. We identified 16 parent‐reported communication measures that have been used with RNDDs, but only six measures had validation data for at least one RNDD. High quality evidence is accumulating, with all validation studies in this review published between 2020 to 2023. Modifications of existing measures may be required to assess communication for RNDDs. This systematic review catalogues the available psychometric data for communication measures and indicates an ongoing need for new validation studies to ensure they are fit‐for‐purpose for upcoming clinical trials in RNDDs. This review will inform the selection of communication measures for clinical trials and research studies. [ABSTRACT FROM AUTHOR]

Existing skeleton-based action recognition methods face the challenges of insufficient spatiotemporal feature mining and a low efficiency of information transmission. To solve these problems, this paper proposes a model called the Spatial–Temporal Attention Residual Network for 3D human action recognition (3D-STARNET). This model significantly improves the performance of action recognition through the following three main innovations: (1) the conversion from skeleton points to heat maps. Using Gaussian transform to convert skeleton point data into heat maps effectively reduces the model's strong dependence on the original skeleton point data and enhances the stability and robustness of the data; (2) a spatiotemporal attention mechanism (STA). A novel spatiotemporal attention mechanism is proposed, focusing on the extraction of key frames and key areas within frames, which significantly enhances the model's ability to identify behavioral patterns; (3) a multi-stage residual structure (MS-Residual). The introduction of a multi-stage residual structure improves the efficiency of data transmission in the network, solves the gradient vanishing problem in deep networks, and helps to improve the recognition efficiency of the model. Experimental results on the NTU-RGBD120 dataset show that 3D-STARNET has significantly improved the accuracy of action recognition, and the top1 accuracy of the overall network reached 96.74%. This method not only solves the robustness shortcomings of existing methods, but also improves the ability to capture spatiotemporal features, providing an efficient and widely applicable solution for action recognition based on skeletal data. [ABSTRACT FROM AUTHOR]

Due to the deficiency of radio spectrum resources caused by the progress in technology, cognitive radio networks (CRNs) have made significant progress. CRNs have two types of users, namely, primary users (PUs) and secondary users (SUs). Considering that PUs have a higher priority and diversified data transmission requirements, this study divides PUs into two levels, namely, PU1s with a higher priority and PU2s with a lower priority. On the other hand, the occurrence of failures is inevitable in CRNs, which affects the data transmission of users. In this paper, combined with an adjustable PU packets transmission rate mechanism, a communication failure and repair mechanism with classified PUs based on the single-channel CRNs is proposed, and different preemption principles are set according to different system states. A queueing model is established and analyzed with a Markov chain, the performance index expressions that need targeted research are listed, numerical experiments are conducted, and the system performance change trends are obtained. The comparison experiment shows that the proposed communication failure and repair mechanism with classified PUs can improve the throughput of PU1 packets and reduce the blocking rate of PU1 packets compared with the conventional communication failure and repair mechanisms with unclassified PUs. [ABSTRACT FROM AUTHOR]

A digitizer is considered one of the fundamental components of an earthquake monitoring system. In this paper, we design and implement a high accuracy seismic digitizer. The implemented digitizer consists of several blocks, i.e., the analog-to-digital converter (ADC), GPS receiver, and microprocessor. Three finite impulse response (FIR) filters are used to decimate the sampling rate of the input seismic data according to user needs. A graphical user interface (GUI) has been designed for enabling the user to monitor the seismic waveform in real time, and process and adjust the parameters of the acquisition unit. The system casing is designed to resist harsh conditions of the environment. The prototype can represent the three component sensors data in the standard MiniSEED format. The digitizer stream seismic data from the remote station to the main center is based on TCP/IP connection. This protocol ensures data transmission without any losses as long as the data still exist in the ring buffer. The prototype was calibrated by real field testing. The prototype digitizer is integrated with the Egyptian National Seismic Network (ENSN), where a commercial instrument is already installed. Case studies shows that, for the same event, the prototype station improves the solution of the ENSN by giving accurate timing and seismic event parameters. Field test results shows that the event arrival time and the amplitude are approximately the same between the prototype digitizer and the calibrated digitizer. Furthermore, the frequency contents are similar between the two digitizers. Therefore, the prototype digitizer captures the main seismic parameters accurately, irrespective of noise existence. [ABSTRACT FROM AUTHOR]

Survivability is a critical concern in WSNs, heavily influenced by energy efficiency. Addressing severe energy constraints in WSNs requires solutions that meet application goals while prolonging network life. This paper presents an Energy Optimization Approach (EOAMRCL) for WSNs, integrating the Grey Wolf Optimization (GWO) for enhanced performance. EOAMRCL aims to enhance energy efficiency by selecting the optimal duty-cycle schedule, transmission power, and routing paths. The proposed approach employs a centralized strategy using a hierarchical network architecture. During the cluster formation phase, an objective function, augmented with GWO, determines the ideal cluster heads (CHs). The routing protocol then selects routes with minimal energy consumption for data transmission to CHs, using transmission power as a metric. In the transmission phase, the MAC layer forms a duty-cycle schedule based on cross-layer routing information, enabling nodes to switch between active and sleep modes according to their network allocation vectors (NAVs). This process is further optimized by an enhanced CSMA/CA mechanism, which incorporates sleep/activate modes and pairing nodes to alternate between active and sleep states. This integration reduces collisions, improves channel assessment accuracy, and lowers energy consumption, thereby enhancing overall network performance. EOAMRCL was evaluated in a MATLAB environment, demonstrating superior performance compared with EEUC, DWEHC, and CGA-GWO protocols, particularly in terms of network lifetime and energy consumption. This highlights the effectiveness of integrating GWO and the updated CSMA/CA mechanism in achieving optimal energy efficiency and network performance. [ABSTRACT FROM AUTHOR]

Due to the ability of optical modulators to achieve rapid modulation of optical signals, meeting the demands of high-speed data transmission, modulators based on different novel nanomaterials have become one of the research hotspots over the past dacade. Recently, TiN/Ti3C2 heterojunction exhibits highly efficient thermo-optic performance and extremely strong stability. Therefore, we have demonstrated an all-optical modulator based on the principle of Michelson interference and the thermo-optic effect in this paper. The modulator employs a TiN/Ti3C2 heterojunction-coated microfiber (THM) and further demonstrates its ability to generate phase shifts through an ASE light source. The modulator, with a phase shift slope of 0.025π/mW, can also convert the phase shifts of signal light into amplitude modulation through Michelson interference. The fixed signal light wavelength is 1552.09 nm, and the modulation depth is stable at about 26.4 dB within a wavelength detuning range of −10 to 6 nm; The waveforms of signal light at modulation rates of 500 Hz, 1000 Hz, 2000 Hz, and 3000 Hz were tested, and a 3 dB modulation bandwidth of 2 kHz was measured. The all-optical modulator based on THM has the advantages of high efficiency and stability and has broad application prospects in the fields of all-optical signal processing and high-speed optical communication. [ABSTRACT FROM AUTHOR]

This paper introduces a novel, small-sized, highly integrated, circularly polarized wide-angle scanning antenna using substrate-integrated waveguide (SIW) technology at millimeter-wave frequencies. The antenna unit addresses requirements for high data transmission rates, wide spatial coverage, and strong interference resistance in communication systems. By integrating radiating square waveguides, circular polarizers, filters, and matching loads, the antenna enhances out-of-band suppression, eliminates cross-polarization, and reduces manufacturing complexity and costs. Utilizing this antenna unit as a component, a 4 × 4 phased array antenna with a two-dimensional ±60° scanning capability is designed and simulated. The simulation and measurement results confirm that the phased array antenna achieves the desired scan range with a gain reduction of less than 3.9 dB. [ABSTRACT FROM AUTHOR]

Silicon-based optical switches are integral to on-chip optical interconnects, and mode-division multiplexing (MDM) technology has enabled modes to function as carriers in routing, further boosting optical switches' link capacity. However, traditional multimode optical switches, which typically use Mach–Zehnder interferometer (MZI) structures and mode (de)multiplexers, are complex and occupy significant physical space. In this paper, we propose and experimentally demonstrate a novel demultiplexing-free dual-mode 3 × 3 thermal-optical switch based on micro-rings (MRs) and mode exchangers (MEs). All MRs are designed to handle TE1 mode, while the ME converts TE0 mode to TE1 mode, enabling separate routing of both modes. Bezier curves are employed to optimize not only the ME, but also the dual-mode 45° and 90° waveguide bends, which facilitate the flexible and compact layout design. Moreover, our structure can support multiple wavelength channels and spacings by adding pairs of MRs, exhibiting strong WDM compatibility. The switch has an ultra-compact footprint of 0.87 × 0.52 mm2. Under both "all-bar" and "all-cross" configurations, its insertion losses (ILs) remain below 8.7 dB at 1,551 nm, with optical signal-to-noise ratios (OSNRs) exceeding 13.0 dB. Also, 32 Gbps data transmission experiments validate the switch's high-speed transmission capability. [ABSTRACT FROM AUTHOR]

The frequency of natural disasters has increased recently, posing a huge threat to human society. Rapid, accurate, authentic, and comprehensive acquisition and transmission of disaster information are crucial in emergency response. In this paper, we propose a design scheme for an aerial remote sensing platform based on real-time satellite communication. This platform mainly includes a civilian heavy-duty unmanned aerial vehicle, ground observation system with the self-developed orthographic image stabilization device, wireless communication system with an airborne mobile communication device using Ku band, ground satellite information receiving station, and data processing and application analysis system. The image stabilization capability of the ground observation system and the communication capability of the wireless communication system were verified through ground and flight tests respectively. The results showed that the stability accuracy of the platform was better than the theoretical threshold, the system transmission rate was not less than 2 M bandwidth, the data packet loss rate was low, and the time delay was not more than 2 s. The images captured in the experiment were clear, with a resolution of less than 1cm and an overlap rate of more than 70%. These all results meet the emergency observation requirement, which indicates that the aerial remote sensing platform based on real-time satellite communication has great potential for application in natural disaster emergency response. [ABSTRACT FROM AUTHOR]

In the framework of the space-air-ground-ocean integrated network, the underwater acoustic sensor network (UASN) plays a pivotal role. The design of media access control (MAC) protocols is essential for the UASN to ensure efficient and reliable data transmission. From the perspective of differentiated services in the UASN, a service-aware and scheduling-based hybrid MAC protocol, named the SSH-MAC protocol, is proposed in this paper. In the SSH-MAC protocol, the centralized scheduling strategy is adopted by sensor nodes with environmental monitoring service, and the distributed scheduling strategy is adopted by sensor nodes with target detection service. Considering the time-varying data generation rate of sensor nodes, the sink node will switch the scheduling mode of sensor nodes based on the specific control packet and adjust the resource allocation ratio between centralized scheduling and distributed scheduling. Simulation results show that the performance of the SSH-MAC protocol, in terms of utilization, end-to-end delay, packet delivery ratio, energy consumption, and payload efficiency, is good. [ABSTRACT FROM AUTHOR]

Let = { T 1 , T 2 , ... , T k } be a set of k ≥ 2 spanning trees in a graph G. The k spanning trees are called completely independent spanning trees (CISTs for short) if the paths joining every pair of vertices x and y in any two trees have neither vertex nor edge in common except for x and y. Particularly, is called a dual-CIST provided k = 2. For data transmission applications in reliable networks, the existence of a dual-CIST can provide a configuration of fault-tolerant routing called protection routing. This paper investigates the problem of constructing a dual-CIST in the n -dimensional hierarchical folded cubic network H F Q n . The network is a two-level network using folded hypercube F Q n as clusters to reduce the diameter, hardware overhead and improve the fault tolerance ability. We propose a recursive algorithm to construct a dual-CIST of H F Q n in (2 2 n) time for n ≥ 2 , where the time required is the same scale as the number of vertices of H F Q n . Also, the diameter of each constructed CIST is 4 n + 1. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel approach to enhance spectral efficiency in communication systems by dynamically adjusting the mapping between cyclic permutation coding (CPC) and its injected form. By monitoring channel conditions such as interference levels and impulsive noise strength, the system optimises the coding scheme to maximise data transmission reliability and efficiency. The CPC method employed in this work maps information bits onto non-binary symbols in a cyclic manner, aiming to improve the Hamming distance between mapped symbols. To address challenges such as low data rates inherent in permutation coding, injection techniques are introduced by removing δ column(s) from the CPC codebook. Comparative analyses demonstrate that the proposed dynamic adaptation scheme outperforms conventional permutation coding and injection schemes. Additionally, we present a generalised mathematical expression to describe the relationship between the spectral efficiencies of both coding schemes. This dynamic approach ensures efficient and reliable communication in environments with varying levels of interference and impulsive noise, highlighting its potential applicability to systems like power line communications. [ABSTRACT FROM AUTHOR]

The paper is devoted to the study of the steady-state transmission problem between two Herschel-Bulkley fluids in thin layers with different viscosities, yield limits and power law index. [ABSTRACT FROM AUTHOR]

As a hot technology trend, the federated learning (FL) cleverly combines data utilization and privacy protection by processing data locally on the client and only sharing model parameters with the server, embodying an efficient and secure collaborative learning model between clients and aggregated Servers. During the process of uploading parameters in FL models, there is susceptibility to unauthorized access threats, which can result in training data leakage. To ensure data security during transmission, the Authentication and Key Agreement (AKA) protocols are proposed to authenticate legitimate users and safeguard training data. However, existing AKA protocols for client–server (C/S) architecture show security deficiencies, such as lack of user anonymity and susceptibility to password guessing attacks. In this paper, we propose a robust 2FAKA-C/S protocol based on ECC and Hash-chain technology. Our security analysis shows that the proposed protocol ensures the session keys are semantically secure and can effectively resist various attacks. The performance analysis indicates that the proposed protocol achieves a total running time of 62.644 ms and requires only 800 bits of communication overhead, showing superior computational efficiency and lower communication costs compared to existing protocols. In conclusion, the proposed protocol securely protects the training parameters in a federated learning environment and provides a reliable guarantee for data transmission. [ABSTRACT FROM AUTHOR]

Vehicular Ad Hoc Networks (VANETs) play a critical role in ensuring safety and welfare applications for drivers and passengers amidst the escalating vehicular population in urban environments. The efficient functioning of VANETs hinges on addressing the challenge of load balancing among Road Side Units (RSUs). This paper introduces a groundbreaking approach aimed at enhancing real-time data transmission services within VANETs. The key contribution lies in the development of a multicast routing algorithm utilizing a geo-targeting protocol, facilitating simultaneous delivery of source data packets to multiple destinations. This innovative strategy aims to alleviate RSU congestion, thereby significantly enhancing the quality of real-time data transmission services. Moreover, this study presents advancements in the Statistical Match and Queuing algorithm, refining it over time to substantially mitigate network congestion and redundancy. Additionally, a Multi-Protocol Label Switching based algorithm is implemented to elevate service quality parameters, including end-to-end latency, packet loss, and overall network efficiency within in-vehicle networks. Importantly, this approach remains adaptable across various Layer two technologies, ensuring compatibility and scalability. Simulation results validate the efficacy of the proposed methodology, showcasing its superiority over existing methods. The findings underscore the innovative algorithms' prowess in addressing load balancing challenges across diverse scenarios, affirming their potential to significantly enhance VANET service quality. [ABSTRACT FROM AUTHOR]

With the vigorous development of cloud computing, most organizations have shifted their data and applications to the cloud environment for storage, computation, and sharing purposes. During storage and data sharing across the participating entities, a malicious agent may gain access to outsourced data from the cloud environment. A malicious agent is an entity that deliberately breaches the data. This information accessed might be misused or revealed to unauthorized parties. Therefore, data protection and prediction of malicious agents have become a demanding task that needs to be addressed appropriately. To deal with this crucial and challenging issue, this paper presents a Malicious Agent Identification-based Data Security (MAIDS) Model which utilizes XGBoost machine learning classification algorithm for securing data allocation and communication among different participating entities in the cloud system. The proposed model explores and computes intended multiple security parameters associated with online data communication or transactions. Correspondingly, a security-focused knowledge database is produced for developing the XGBoost Classifier-based Malicious Agent Prediction (XC-MAP) unit. Unlike the existing approaches, which only identify malicious agents after data leaks, MAIDS proactively identifies malicious agents by examining their eligibility for respective data access. In this way, the model provides a comprehensive solution to safeguard crucial data from both intentional and non-intentional breaches, by granting data to authorized agents only by evaluating the agent's behavior and predicting the malicious agent before granting data. The performance of the proposed model is thoroughly evaluated by accomplishing extensive experiments, and the results signify that the MAIDS model predicts the malicious agents with high accuracy, precision, recall, and F1-scores up to 95.55%, 95.30%, 95.50%, and 95.20%, respectively. This enormously enhances the system's security in terms of authorized data access accuracy up to 55.49%, precision up to 43.15%, recall up to 55.49%, and F1-score up to 39.96%, respectively, as compared to state-of-the-art work. [ABSTRACT FROM AUTHOR]

This paper studies the problem of joint deployment, user association, channel, and resource allocation in unmanned aerial vehicle‐enabled access network. Since different user equipments performing different tasks and have different data rate requirements, the priority‐based traffic fairness problem is investigated. This problem, however, is a mixed integer nonlinear programming problem with NP‐hard complexity, making it challenging to be solved. To address this issue, a self‐organized and distributed framework "sense‐as‐you‐fly" based on the decomposition process, which divides the original problem into several subproblems, is proposed. Assuming without central controller, we derive the closed‐form resource allocation scheme and propose distributed many‐to‐one matching to optimize user association subproblem. Considering the coupled characteristics, the multi‐unmanned aerial vehicle deployment and channel allocation subproblems are modelled as a local altruistic game. The existence of Nash equilibrium is proved with the aid of exact potential game and efficient best response learning‐based algorithm is proposed. The original problem is finally addressed by solving the sub‐problems alternately and iteratively. Simulation results verify its effectiveness. By jointly optimizing multidimensional variables, the proposed algorithm unlocks network performance gains, especially in resource‐limited regimes. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to optical communication systems by introducing a hybrid MGDM–FSO (Mode Group Diversity Multiplexing—Free Space Optical) system. The primary objective of this innovative system is to address the limitations of traditional communication systems, particularly in challenging environmental conditions. By combining the advantages of MGDM, which enhances transmission capacity in optical fibers, with the flexibility and high data rates offered by FSO technology, the hybrid MGDM–FSO system aims to overcome obstacles encountered during data transmission. In this study, we provide a detailed analysis of the proposed system's architecture and performance characteristics under various operating conditions. Specifically, we investigate both single-input single-output (SISO) and multiple-input multiple-output (MIMO) configurations of the MGDM–FSO system. Performance metrics such as received power levels, bit error rate (BER), and quality factor (Q-factor) are evaluated to assess the system's efficiency across different weather conditions. Numerical simulations are conducted to analyze the system's performance under a range of scenarios. Our findings indicate that under clear weather conditions, both SISO and MIMO configurations exhibit optimal performance, characterized by high Q-factor and low BER. However, as weather conditions deteriorate to heavy rain and heavy fog, the Q-factor of the received signal decreases, highlighting the impact of environmental factors on system performance. This study contributes valuable insights into the behavior of hybrid MGDM–FSO systems and emphasizes the importance of robust communication techniques to mitigate environmental challenges. The findings presented here have implications for the design and implementation of optical communication systems in real-world scenarios. [ABSTRACT FROM AUTHOR]

One of the networking technologies is called a wireless sensor network, and what it does is link sensor nodes by using wireless communication as the channel of connection. A haphazard and random distribution of nodes is carried out throughout the deployment process within the network area. As a result, the distances between the nodes do not remain constant. The nodes have a high sensing capacity, but their range of perception and battery life are also severely limited. The wireless data may be sensed by all of the nodes inside their respective sensing regions. Consequently, there are a variety of new applications that make use of WSN applications, particularly in surveillance monitoring applications such as those used in hospitals, buildings, forests, and airspace monitoring. The transmission of the data to the appropriate server or data centre that is linked with the cloud or the internet is experiencing greater difficulties as a result of the growing amount of monitoring data. This indicates that a significant quantity of data is lost as a result of the fact that wireless transmission is affected by environmental factors such as precipitation, humidity, and wind storms. It is vital to create and execute an innovative routing protocol to deliver greater throughput and raise the overall Quality of Service of the WSN applications in order to solve the difficulties that have been outlined above. This study paper presents a metaheuristic algorithm based optimal routing protocol for WSN application, which boosts the overall quality of service of any surveillance monitoring applications. To achieve this goal, the protocol was designed for wireless sensor networks. It does so in an effective manner, resulting in decreased delay and energy consumption as well as enhanced throughput and PDR. Based on the findings of the experiments, it has been hypothesised that the proposed metaheuristic algorithm-based routing protocol is capable of performing better routing for any type of surveillance monitoring and remote monitoring, as well as successfully transmitting any type of data, including numerical, video, and image data. [ABSTRACT FROM AUTHOR]

The seamless integration of intelligent Internet of Things devices with conventional wireless sensor networks has revolutionized data communication for different applications, such as remote health monitoring, industrial monitoring, transportation, and smart agriculture. Efficient and reliable data routing is one of the major challenges in the Internet of Things network due to the heterogeneity of nodes. This paper presents a traffic-aware, cluster-based, and energy-efficient routing protocol that employs traffic-aware and cluster-based techniques to improve the data delivery in such networks. The proposed protocol divides the network into clusters where optimal cluster heads are selected among super and normal nodes based on their residual energies. The protocol considers multi-criteria attributes, i.e. energy, traffic load, and distance parameters to select the next hop for data delivery towards the base station. The performance of the proposed protocol is evaluated through the network simulator NS3.40. For different traffic rates, number of nodes, and different packet sizes, the proposed protocol outperformed LoRaWAN in terms of end-to-end packet delivery ratio, energy consumption, end-to-end delay, and network lifetime. For 100 nodes, the proposed protocol achieved a 13% improvement in packet delivery ratio, 10 ms improvement in delay, and 10 mJ improvement in average energy consumption over LoRaWAN. [ABSTRACT FROM AUTHOR]

Edge computing enables prompt responses in IoT environments, such as the operation of autonomous vehicles and unmanned aerial vehicles. However, with the increase in sensor nodes, the computational burden on the computing node also increases. Specifically, data filtering and reduction at application nodes add to the energy burden for battery-operated devices. In this paper, we propose a preprocessing system at the application node that requires low power consumption for data transmission reduction. Based on our simulations, we identify the minimum data size needed to preserve the signal. We first design the preprocessing system using a hardware description language to evaluate its performance. Then, we implement the open-library-based MCU system, including the proposed preprocessing IP, to assess its operation and overhead. Our implementation of the preprocessing system reduces data transmission by 50% with acceptable information loss. Additionally, the area and power consumption after the logic synthesis of the preprocessing IP within the entire MCU system are evaluated at only 3.6% and 13.1%, respectively. By performing preprocessing using the MCU and proposed IP, nearly 74.4% power reduction is achieved compared to using the existing MCU core. [ABSTRACT FROM AUTHOR]

The agriculture Internet of Things (IoT) has been widely applied in assisting pear farmers with pest and disease prediction, as well as precise crop management, by providing real-time monitoring and alerting capabilities. To enhance the effectiveness of agriculture IoT monitoring applications, clustering protocols are utilized in the data transmission of agricultural wireless sensor networks (AWSNs). However, the selection of cluster heads is a NP-hard problem, which cannot be solved effectively by conventional algorithms. Based on this, This paper proposes a novel AWSNs clustering model that comprehensively considers multiple factors, including node energy, node degree, average distance and delay. Furthermore, a novel high-performance cluster protocol based on Gaussian mutation and sine cosine firefly algorithm (GSHFA-HCP) is proposed to meet the practical requirements of different scenarios. The innovative Gaussian mutation strategy and sine–cosine hybrid strategy are introduced to optimize the clustering scheme effectively. Additionally, an efficient inter-cluster data transmission mechanism is designed based on distance between nodes, residual energy, and load. The experimental results show that compared with other four popular schemes, the proposed GSHFA-HCP protocol has significant performance improvement in reducing network energy consumption, extending network life and reducing transmission delay. In comparison with other protocols, GSHFA-HCP achieves optimization rates of 63.69%, 17.2%, 19.56%, and 35.78% for network lifespan, throughput, transmission delay, and packet loss rate, respectively. [ABSTRACT FROM AUTHOR]

This paper proposes a novel cache replacement technique based on the notion of combining periodic popularity prediction with size caching. The popularity, size, and time updates characteristics are used to calculate the value of each cache item. When it comes to content replacement, the information with the least value is first eliminated. Simulation results show that the proposed method outperforms the current algorithms in terms of cache hit rate and delay. The hit rate of the proposed scheme is 15.3% higher than GDS, 17.3% higher than MPC, 20.1% higher than LRU, 22.3% higher than FIFO, and 24.8% higher than LFU when 350 different categories of information are present. In real-world industrial applications such as including supply chain management, smart manufacturing, automation energy optimization, intelligent logistics transportation, and e-healthcare applications, it offers a foundation for the selection of caching algorithms. [ABSTRACT FROM AUTHOR]