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The emergence of the Internet has brought revolutionary changes to modern information technology. The development of electronic communication information storage technology facilitates people to access information anytime and anywhere, effectively achieving resource sharing. However, traditional methods scatter communication information to all nodes, but neglect the extraction of electronic communication information association features, resulting in low information storage efficiency. This article analyzes the efficiency management of electronic communication information storage in multi-threaded networks and sets up a control experiment. Comparing the method proposed in this article with traditional methods, this study focuses on five aspects: information redundancy storage, information space utilization, productivity, data accuracy, and data transmission efficiency. It is concluded that the average information redundancy storage capacity of traditional electronic information storage methods is 8.35 x 107 T which is 6 x 107 T higher than using multi wire network electronic communication information storage methods. It indicates that traditional redundant information occupies a large amount of storage space, and its storage value exceeds the upper limit of electronic communication information storage. This means that the stored information may be overwritten by redundant information, resulting in the loss of stored information. The experimental results show that using the method proposed in this paper for electronic communication information storage results in a high distribution density of storage space and a significant improvement in information storage efficiency. [ABSTRACT FROM AUTHOR]

This paper examines a nonlinear Networked Control System (NCS) incorporating Takagi–Sugeno (T–S) fuzzy models to address the output tracking control problem in the presence of input state delay. The paper introduces a strategy based on an event-triggered scheme to reduce bandwidth utilization in the NCS by leveraging inherent constraints, including communication time delays and data transmission limitations. The presence of communication time delay leads to an asynchronous interaction between the designed control algorithm for T–S fuzzy systems, which utilizes novel LMI–based conditions, and the proposed T–S fuzzy controller. Additionally, this paper proposes a model of operation based on synchronous behaviour, enabling the design of a linear controller that is more easily implementable. In comparison to recent literature results, these results are obtained by using an associate Lyapunov Krasovskii Function (LKF) with fuzzy properties, in addition to different forms of integral inequalities as alternatives. A fuzzy model for NCSs is illustrated through an example of tracking control for output response. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) networks always operate within the context of diverse and constrained characteristics of the devices. Low-Power and Lossy Networks (LLNs) constitute a network architecture commonly utilized in IoT application deployments, facilitating networking and the establishment of paths for data transmission. The Routing Protocol for Low-Power and Lossy Networks (RPL) demonstrates promising capabilities for LLN network operations, supporting IPv4 and IPv6-enabled services. The RPL protocol constructs a Destination Oriented Directed Acyclic Graph (DODAG) logical routing topology based on defined Objective Function (OF) metrics. Routing operations within the DODAG utilize these metrics and constraints to select parent nodes and calculate optimal routes between two nodes. Standardized OFs have traditionally focused on either parent node selection or routing objectives within the DODAG, often treating load balancing and bottleneck optimization separately. However, their combined impact on RPL's effectiveness has been overlooked. This paper introduces an Adaptively Composite Objective Function (AC-OF) approach that considers the combined objectives of DODAG load balancing and optimized routing operations. Through simulation evidence, the paper presents improved network parameters. The AC-OF implementation brings out significant results in the form of a balanced DODAG topology and it has good impacts on data transmission, control overhead messages, parent switching, delay, energy consumption, and node lifetime. [ABSTRACT FROM AUTHOR]

The unlicensed industrial, scientific, and medical (ISM) band at 2.4 GHz has gained increased attention recently due to the high data rate communication systems developed to operate in this band. The paper presents measurement results of fading characteristics, multipath parameters and background interference for these frequencies. Some statistical analysis of the measured data is presented. The paper provides information that may be useful in design and deployment of communication systems operating in the 2.4 GHz ISM band, like those compliant with IEEE 802.11 standard and Bluetooth open wireless standard. [ABSTRACT FROM AUTHOR]

The transition from conventional standalone metrology to integrated metrology has been accelerating in advanced manufacturing over the past decade. This keynote paper defines the concept of integrated metrology, which extends beyond parts inspection and encompasses processes and manufacturing equipment to enhance efficiency and productivity. The paper presents the characteristics, benefits, constraints, and future possibilities of integrated metrology for parts, processes, and equipment. It also includes a classification of the physical quantities of measurands, the corresponding measuring instruments, data and communication methods, uncertainty, and traceability. The paper also discusses future challenges and emerging trends. [ABSTRACT FROM AUTHOR]

Maritime activities are on the rise, there is a growing demand for high-quality communication services that can cover larger areas. However, the transmission of high data rates to maritime users is challenging due to path loss from land base stations, which limits the transmission power. To overcome this challenge, researchers have been exploring the use of buoys in a marine environment as relays for communication technology. This paper proposes a simulation-based approach to investigate the impact of various beamwidths on communication performance when using a buoy as a relay. The objective is to determine the optimal beamwidth that yields the highest data rate for the target location. The approach is based on an offshore wave model where the direction of the buoy changes according to the height of the wave. The study investigates the performance of the relay in the downlink situation using receive beamforming, and the capacity at the user in the three-hop situation is verified using an amplify-and-forward (AF) relay that uses transmit beamforming to the user. The simulation results suggest that the beamwidth of the relay should be adjusted according to the wave conditions to optimize the data rate and relay position that satisfies a data rate superior to the direct path to the target position. Using a buoy as a relay can be a promising solution for enhancing maritime communications, and the simulation-based approach proposed in this paper can provide insights into how to optimize beamwidth for effective communication system design and implementation. In conclusion, the study results suggest that the use of buoys as relays for maritime communication is a feasible solution for expanding coverage and enhancing communication quality. The proposed simulation-based approach provides a useful tool for identifying relay beamwidths for achieving higher data rates in different wave conditions. These findings have significant implications for the design and deployment of communication systems in maritime environments. [ABSTRACT FROM AUTHOR]

The security of patient data is a critical problem for health networks due to the rising popularity of telehealth services and the requirements for clinical data sharing between surgeons, consultants, and medical groups. In contrast to protecting medical data, which includes the cover (i.e., clinical picture), the requirements for protecting other pertinent data are more general. The paper advocates for data encryption before concealment as a robust strategy to uphold patient privacy during medical information exchange. The primary focus of this analysis revolves around a comprehensive exploration of different steganography methods. Through a meticulous examination of various steganographic techniques, including LSB, PVD, and transform domain approaches, this paper provides a detailed analysis of their strengths and limitations. Objective metrics like PSNR and SSIM are employed to dissect the trade-offs between data security and visual fidelity. The research leads to the conclusion that the diagonal queue-based steganog-raphy methodology, supported by chaotic methods, the Linear Feedback Shift Register (LFSR), and the durable Rabin encryption system, is the best course of action. This method enables autonomous data transmission among numerous contacts while ensuring the highest level of confidentiality and integrity of patient data inside e-health networks. In summary, this study provides a comprehensive solution that protects patient data and speeds data transmission inside the expanding framework of e-health networks in order to meet urgent data security concerns in telemedicine and healthcare data exchange. [ABSTRACT FROM AUTHOR]

As China's electricity market continues to evolve, the increasing number and diversity of market participants have led to a rapid increase in data volume. An immediate challenge is designing a robust blockchain system that ensures not only the transparency, credibility, tamper-resistance, traceability, privacy, and security of substantial market data in a complex environment, but also provides trusted data support for intelligent dispatching within the power market. This paper proposes a solution to this pressing issue through Blockchain as a Service (BaaS). BaaS leverages the capabilities of cloud computing platforms to enhance the ease and efficiency of deploying and operating blockchain systems. Specifically, the paper introduces a BaaS system built upon an integrated intelligent scheduling and operation cloud-edge platform (CEP). It incorporates technological solutions such as data on-chain, trusted comparison, edge cluster data transmission, optimized transaction authentication, and lightweight storage nodes. Rigorous testing has conclusively demonstrated that the proposed BaaS system meets the requirements of the digital transformation of the China Southern Power Grid, and provides robust technical support for its future practical applications. [ABSTRACT FROM AUTHOR]

In this paper, an innovative event-triggered optimal tracking control algorithm is proposed for input saturated strict-feedback nonlinear systems with unknown dynamics. In order to reduce the requirement of configuring a complete suit of sensors and enhance the reliability of the controlled system, a neural networks (NNs) based adaptive state observer is developed firstly to reconstruct the system states. Subsequently, based on the state estimation information, a hybrid-triggered feedforward controller is designed to transform the original tracking control problem into an equivalent regulation issue, which is then solved by developing an event-triggered optimal controller. Therefore, the final controller consists of a hybrid-triggered feedforward controller and an event-triggered optimal controller. In order to make the actual input signals of the two controllers be updated simultaneously, a synchronization-oriented triggering rule is established by using multiple triggering errors. By virtue of this unique framework, the proposed control scheme can not only minimize the predefined cost function, but also greatly reduce the data transmission. What is more, the convergence properties of the proposed control strategy are achieved by using Lyapunov theory. It is important to note that unlike the widely adopted observer-controller framework, where the separation principle holds for the design of the state observer, there is a considerable coupling relationship between the error dynamics of the state observer and the event-triggered optimal controller in this paper. The distinguishing feature of the proposed method is its ability to ensure a satisfactory level of precision in both state estimation and tracking control, even in the presence of control saturation issues. At last, the proposed control strategy is applied to the tracking control problem of a high-order robot system and marine surface vehicle to demonstrate its effectiveness. • A novel event-triggered optimal tracking control framework is proposed. • A phenomenon we defined as the "jump of error surfaces" is noticed and tackled via filter technique. • A multi-error based adaptive triggering rule is established to improve the control performance. • The proposed method not only achieves the optimality but also lowers data transmission. [ABSTRACT FROM AUTHOR]

This paper proposes an improved dual-phased framework for energy-efficient, cluster-based routing in Wireless Sensor Networks (WSNs). It addresses the critical challenge of balancing energy consumption with reliable network performance. Cluster-based routing is a crucial parameter for WSN operational efficiency, especially in applications demanding minimal energy use and dependable data transmission. The proposed framework integrates two advanced meta-heuristic algorithms: Sailfish Optimization (SFO) and Spotted Hyena Optimization (SHO). This combined approach leverages SFO's rapid exploration for efficient clustering and optimal Cluster Head (CH) selection. Additionally, SHO's refined exploitation capabilities optimize efficient routing paths. This innovative methodology significantly improves network performance metrics like energy efficiency, network lifetime, and Packet Delivery Ratio (PDR). The originality of this work lies in the dual-phased optimization strategy. It distinctively outperforms traditional single-algorithm based approaches by employing a unique hybrid optimization approach, offering greater originality and value. Experimental simulations demonstrate that the proposed framework outperforms several popular algorithms in terms of key performance metrics. This makes it a valuable contribution to the field and an efficient solution for diverse applications. [ABSTRACT FROM AUTHOR]

This paper is concerned with the secure output consensus problem for the heterogeneous multi-agent systems under the event-triggered scheme in the presence of the denial-of-service attack. Without detecting the attack, the hold-input controller update strategy is adopted when some transmission data may be lost due to the effect of the attack. Based on the tolerable duration of the attack, a novel edge-based event-triggered scheme is developed. The scheme can avoid continuous communication and exclude Zeno behavior. With the aid of the switched system theory, output consensus is preserved. An example shows the effectiveness. • Secure problem for the heterogeneous multi-agent systems is solved in the presence of the denial-of-service attack. • A novel edge-based event-triggered scheme is developed based on the tolerable duration of the attack. • Without detecting the attack, the hold-input controller update strategy is adopted. • Output consensus is preserved with the aid of the switched system theory. [ABSTRACT FROM AUTHOR]

Due to the rapid development of confidential digital communication over international networks, security is the most significant factor. Steganography is the science of concealed communication and is used to conceal the presence of secret information among the various methods of hiding data in communications. Steganography techniques are usually implemented either in spatial or frequency domains. Some spatial domain methods fundamentally utilize the absolute difference value between neighbor pixels to encode the secret message, categorized as Pixel-Value Differencing Steganography methods (PVDS). In PVDS, the hiding capacity of the adjacent pixels depends on their difference value. Consequently, the secret data will be embedded with a high visual quality of the stego-image. Indicator-based PVDS (IPVDS) technique is derived from the PVDS method. It depends on an Indicator pixel (IP) to extract the secret data correctly. The Genetic Algorithm (GA) approach to optimization depends on the concept of survival of the fittest. This paper introduces two proposals, GA-based steganography schemes (GA-IPVD) and (GA-IPVDM). These new techniques encoded secret data using the IPVDS method. Before embedding data in the cover image, the order of the pixels corresponding to the secret data is modified and rearranged. GA controls the operation of rearranging and modifying the order of pixels and all parameters. The current paper addresses steganography as an optimization problem and seeks to determine the optimal order of the pixels that enhance the matching between the cover image and stego-image to reduce distortion despite high embedded capacity. In the first proposed technique GA-IPVD, GA concentrates on the imperceptibility of embedded data and maximizes the quality of the stego-image according to the given secret data. In contrast, the GA maximizes the capacity of embedded data while maintaining an acceptable amount of stego-image quality in the second proposed technique GA-IPVDM. The proposed systems have embedding key that increase the security of proposed schemes. The experimental results demonstrate that the proposed methods can embed a large quantity of secret data while maintaining an acceptable visual quality of the stego-images. The proposed technique has also demonstrated excellent resistance to a variety of stego-attacks, including the pixel difference histogram (PDH) as well as regular and singular (RS) analyses. Additionally, the out-of-boundary pixel issue (BI), which endures in the majority of modern data hiding algorithms, has been successfully resolved. [ABSTRACT FROM AUTHOR]

Network security technology is capable of mitigating attack signals launched by malicious attackers, thereby safeguarding and bolstering system security. Secure state estimation is a type of network defense technology that involves reconstructing the system state by measuring potential attacks. The relevant research has also been expanded to distributed systems to enable collaborative secure state estimation among different agents facing homogeneous attacks; however, such research significantly enhance the communication load of the system. On the other hand, if the homogeneous attack is non-existent or consistent, excessive network communication is definitely inefficient. An event-triggered approach is a potent technique that can alleviate communication overhead while having minimal impact on system performance. This paper proposes a mechanism for event-triggered transmission in the context of distributed secure state estimation. While communication latency and data transmission disorder may be present within the communication network, the estimation error of the proposed observer is constrained and bounded. The simulation results indicate that for stable malicious attack signals, system communication can be divided into high-frequency and low-frequency communication periods. The simulation results also shows that the maximum estimation error is proportional to the trigger threshold, allowing the observer's performance to be finely tuned to the required precision. • In this paper, the observer presented implements an event-triggered communication strategy, which effectively decreases the frequency of data transmission and reduces the communication load on the network. • Network latency and data disorder are also taken into consideration. • The maximum estimation error is proportional to the trigger threshold, allowing the observer's performance to be finely tuned to the required precision. [ABSTRACT FROM AUTHOR]

This paper systematically reviews the current applications of various spatial information technologies in CO2 sequestration monitoring, analyzes the challenges faced by spatial information technologies in CO2 sequestration monitoring, and prospects the development of spatial information technologies in CO2 sequestration monitoring. Currently, the spatial information technologies applied in CO2 sequestration monitoring mainly include five categories: eddy covariance method, remote sensing technology, geographic information system, Internet of Things technology, and global navigation satellite system. These technologies are involved in three aspects: monitoring data acquisition, positioning and data transmission, and data management and decision support. Challenges faced by the spatial information technologies in CO2 sequestration monitoring include: selecting spatial information technologies that match different monitoring purposes, different platforms, and different monitoring sites; establishing effective data storage and computing capabilities to cope with the broad sources and large volumes of monitoring data; and promoting collaborative operations by interacting and validating spatial information technologies with mature monitoring technologies. In the future, it is necessary to establish methods and standards for designing spatial information technology monitoring schemes, develop collaborative application methods for cross-scale monitoring technologies, integrate spatial information technologies with artificial intelligence and high-performance computing technologies, and accelerate the application of spatial information technologies in carbon sequestration projects in China. [ABSTRACT FROM AUTHOR]

Infrastructure construction companies encounter numerous challenges in managing large and dispersed teams, along with fragmented or non-existent operational data. These challenges often result in delays, inefficiencies, and over-budget projects. Road pavement works are an example of this, as they heavily rely on expensive heavy construction equipment that requires detailed planning and real-time adjustments. Also, pavement quality is closely linked to the quality of the asphalt mixture in terms of viscosity and compactability, which is significantly influenced by temperature. This paper describes the features, challenges and results of a road paving real-time management system that was conceived in a co-creation environment with a construction company. Such a partnership has allowed to specify the requirements of such an application aligned with the identified needs of a real-world development. According with the state-of-the-art, this innovative system is unique in the way it is manufacturer-agnostic and designed to be compatible with most situations. It is also data production-oriented to allow future developments that may provide business analytics or scientific research in the road paving area. This work also presents the development of sensors such as a high precision geolocalized infrared matricial temperature sensor for the application of the bituminous mixture, the data and communication structure, and a web-based interface that manages the construction projects for different stakeholders. [ABSTRACT FROM AUTHOR]

Ad hoc networks are the ultimate technology in wireless communication that allow network nodes to communicate without the need for a fixed infrastructure. The paper addresses issues associated with control of data transmission in wireless sensor networks (WSN) -- a popular type of ad hoc networks with stationary nodes. Since the WSN nodes are typically battery equipped, the primary design goal is to optimize the amount of energy used for transmission. The energy conservation techniques and algorithms for computing the optimal transmitting ranges in order to generate a network with desired properties while reducing sensors energy consumption are discussed and compared through simulations. We describe a new clustering based approach that utilizes the periodical coordination to reduce the overall energy usage by the network. [ABSTRACT FROM AUTHOR]

Rapid development of 5G networks encourages researchers to improve the radio-over-fiber (RoF) technique in order to reach 10 Gbps data transmission rates, to increase bandwidth and range, while reducing latency and implementation cost. This paper evaluates an analog radio-over-fiber (ARoF) technique that is compatible with long-distance communication systems. We demonstrate a long distance transmission of a 28 GHz 64 QAM signal via a single mode fiber (SMF) after modulating it with the use of two parallel Mach-Zehnder modulators, without any optical amplifiers. The results show that our prototype solution is capable of transferring data over distances of up to 140 km, via SMF, with a 10 Gbps data rate. The error vector magnitude (EVM) was found to be 7.709%. The proposed system offers exceptional capabilities in terms of supporting high bitrates, while ensuring that EVM remains within the 3GPP limits. Compared to other works, the proposed solution proves to be superior in terms of performance, making it an ideal choice for next generation long-haul communication systems. [ABSTRACT FROM AUTHOR]

This paper introduces a method that combines the Kmeans clustering genetic algorithm (GA) and Lempel-Ziv-Welch (LZW) compression techniques to enhance the efficiency of data aggregation in wireless sensor networks (WSNs). The main goal of this research is to reduce energy consumption, improve network scalability, and enhance data aggregation accuracy. Additionally, the GA technique is employed to optimize the cluster formation process by selecting the cluster heads, while LZW compresses aggregated data to reduce transmission overhead. To further optimize network traffic, scheduling mechanisms are introduced that contribute to packets being transmitted from sensors to cluster heads. The findings of this study will contribute to advancing packet scheduling mechanisms for data aggregation in WSNs in order to reduce the number of packets from sensors to cluster heads. Simulation results confirm the system’s effectiveness compared to other compression methods and non-compression scenarios relied upon in LEACH, M-LEACH, multi-hop LEACH, and sLEACH approaches. [ABSTRACT FROM AUTHOR]

Counterfactuals – expressing what might have been true under different circumstances – have been widely applied in statistics and machine learning to help understand causal relationships. More recently, counterfactuals have begun to emerge as a technique being applied within visualization research. However, it remains unclear to what extent counterfactuals can aid with visual data communication. In this paper, we primarily focus on assessing the quality of users' understanding of data when provided with counterfactual visualizations. We propose a preliminary model of causality comprehension by connecting theories from causal inference and visual data communication. Leveraging this model, we conducted an empirical study to explore how counterfactuals can improve users' understanding of data in static visualizations. Our results indicate that visualizing counterfactuals had a positive impact on participants' interpretations of causal relations within datasets. These results motivate a discussion of how to more effectively incorporate counterfactuals into data visualizations. [ABSTRACT FROM AUTHOR]

The rise of the national fitness trend has led more and more people to join the ranks of physical fitness, and the current physical education resources and human resources have not been able to keep pace with the development of sports. Due to the lack of guidance, many beginners of sports are not standardized, and their movements are not effective and even cause injuries. Sports action recognition technology can make up for this lack and realize the action recognition and guidance for sports players. In this paper, we build a sports movement and posture recognition model based on acceleration sensors, introduce Selectable Mode Vocoder (SMV) algorithm to optimize the performance, and ensure the effectiveness of sensor data transmission through a low energy multi-layer clustered wireless sensor network. The experiment mainly compares the generation results of the first energy depleted node in the entire network with the number of rounds with energy depleted nodes reaching 10 %. The experimental results show that the low-energy multi-layer clustered wireless sensor network effectively shortens the data transmission path, reduces the energy consumption of nodes, extends the network life time, ensures the data transmission effectiveness, and provides network guarantees for sports action recognition. In addition, in the comparison experiments, the action recognition model in this paper shows better recognition effect and efficiency with obvious performance advantages. [ABSTRACT FROM AUTHOR]

Information technology acts an important role in gathering, transmitting with executing data from areas of disaster-prone such as the battlefield and international borders. In addition to the country's security, the soldier needs protection by defending himself with advanced weapons such as a bomb detector. This paper provides the capability to track the whereabouts and health of soldiers who have been lost or injured on the battlefield. It assists in reducing the time, searching and rescuing operation efforts of the military control room. This paper implements a system for health-condition monitoring that sends soldiers' health parameters, such as the electrocardiogram (ECG), blood oxygen level, pulse rate, and temperature, to the control room via a Mobile Ad hoc Network (MANET). Body parameters are sensed utilizing various body sensors fixed to the bodies of soldiers. The body parameters are broadcasted to the control room via MANET devices at the path. To preserve the health parameters data of soldiers from enemies while data transmission, this paper also proposes a cryptographic ensemble approach. This approach combines Symmetric Key Encryption, and Identity Based Encryption (IBE) with Identity Based Signature (IBS). The experimental result shows proposed cryptographic ensemble provides high security compared with existing MANET security algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we consider stability and latency analysis of a two-user cognitive radio network while considering Age of Information requirements imposed on the data transmissions of the users. We provide two different formulations. In the first formulation, our objective is to maximize the stable throughput of the secondary user subject to Age of Information constraints imposed on the data transmission of the users. While, in the second formulation, we introduce a multi-objective programming approach that investigates the trade-off between the secondary user stable throughput and its Age of Information. Our numerical results characterize the effect of imposing different Age of Information restrictions on the stable throughput region of the network; we show that the stability region, in certain cases, is reduced by only 11 % with strict Age of Information restrictions. Our results also investigate the trade-off between the secondary user throughput and the Age of information. Finally, our results show the potential accuracy of the algorithm adopted in this paper to solve the formulated non-linear optimization problems. [ABSTRACT FROM AUTHOR]

This paper examined uplink and downlink di-state (primary and secondary) situations to build the theoretical and practical realization of a bidirectional cooperative wireless cellular network. In the primary scenario, full-duplex (FD) base stations support two sets of half-duplex (HD) users, where the transmitter (uplink) and receiver (downlink) respectively. Each uplink transmitted signal is rotated in a variant phase through a set of scalars known to the base stations before transmission. The signal from the transmitter ensures the reconfigurable receiver antennas at the base stations can configure the received signal as decoded signals. The proposed work exposed strong self and inter-user interference from the transmitter during demonstrating FD wireless communication mode that destroyed network functionality at the base stations. The occurred self-interference signals from the transmitter are neutralized using precoding and beam-forming technique. During the secondary scenario, decoded base station signals are independently encoded and transmitted to the downlink users. Base stations aid the inter-user interference management by precoding the uplink transmission data and forwarding it to the downlink users. Consequently, the inter-user interference signals are aligned using the span interference alignment technique. A proposed cooperative additional receiver (listener U1) can decode the desired signals and helps in recovering and reconstructing the interference signals. This proposed work completely characterized and evaluated the degree of freedom (DoF) for unknown channel state information at the transmitter (CSIT); whereas achievable lower and upper bound DoF are demonstrated for the partial CSIT. At last, the analytical and simulation results reveal the sum of DoF improvement for unknown and partial CSIT. [ABSTRACT FROM AUTHOR]

Performance evaluation plays a vital role in the field of cryptography. It is essential to assess the security, efficiency, and suitability of different algorithms in various applications. By evaluating the performance of cryptography algorithms, we can identify vulnerabilities, weaknesses, and strengths, which are crucial for ensuring the integrity and confidentiality of sensitive data. Moreover, performance evaluation allows for benchmarking, algorithm selection, and continuous improvement in the field, driving advancements in cryptography techniques and enhancing the overall security of systems that rely on cryptography. This paper implements a test algorithm that can evaluate the performance of different parameters for a range of cryptography algorithms. The performance of input is evaluated using parameters such as the Avalanche effect, Correlation coefficient, Bit independence test, Frequency test, Encryption and decryption execution time, Throughput, Brute Force attack, and Information entropy. By comparing results obtained from the performance tests, we can gain valuable insights into the relative strengths and weaknesses of the algorithms. This aids in making informed decisions regarding algorithm selection and improvement, ultimately contributing to the advancement of secure communication and data protection. [ABSTRACT FROM AUTHOR]

The demand for high data throughput and security in Unmanned Aerial Vehicle (UAV) communication is rising. Efficient data transmission remains challenging due to limited wireless resources. This paper introduces a Scale Perception Compression Method that leverages compression and blockchain technology to optimize UAV communication. The method involves normalizing data into matrices, generating compression and decompression matrix codebook pairs, and selecting suitable pairs for small or large-scale matrices. Simulation results show that the error rate is associated with the distributions of the data and compression matrix. It remains relatively low when the data and compression matrix subjected to Uniform distribution compared to Gaussian distribution, regardless of the values of the number of rows m and columns r in compression matrix. Bubble method is more suitable to find out the proper matrix pair to compress and decompress transmitted data for small-scale codebook because it is stable, fast and results in lower difference between original and recovered data matrices. The same applies to Merge method for the large-scale codebook. The ER is always lower based on a small-scale codebook searching by Bubble method than that of on a large-scale codebook searching by Merge method, which indicates the former is sufficient for compression. [ABSTRACT FROM AUTHOR]

VANETs (Vehicular Ad-hoc Networks) are a kind of Mobile Ad-hoc Networks (MANETs) with increased mobility as well as occasional geographic changes. Clustering is used in VANETs to divide networks into groups of adaptable vehicles to optimize routing, information gathering, as well as routing. As large data block transmission contains several stages and inside those, one of the important stages such as optimal model selection was these selections of quintessential features helps in a further stage called data transmission much more effective. This stage will also bring energy optimization and also improves the effectiveness of the optimal path for data transmission. This paper brings a comparative analysis of this optimal relay node selection. Here, we use Linear Scaling based Red Colobuses Monkey technique and are contrasted with other state-of-the-art models over various measures. Analysis proves that the proposed optimal relay node selection technique boosts the data transmission model. [ABSTRACT FROM AUTHOR]

Owing to the deep integration of intelligent control, big data and communication, networked Takagi–Sugeno fuzzy control systems is widely studied and applied to the real-world scenarios. This paper studies the issue of resilient event-triggered dynamic output feedback controller design of networked Takagi–Sugeno fuzzy systems under denial-of-service (DoS) attacks launched by adversaries. Considering the types of the attack limited by frequency and duration, a resilient event-triggered mechanism is established to resist the impact of DoS attacks and improve resource utilization efficiency, and two new switched fuzzy system models are constructed by integrating the underlying system and the event-based static and dynamic output feedback intelligent controllers. Then sufficient conditions are obtained to guarantee that the switched systems are exponential stable and then the control gains are designed by using a novel iterative algorithm. Finally, two examples are employed to verify the effectiveness of the developed method. [ABSTRACT FROM AUTHOR]

In the big data era, image compression is of significant importance in today's world. Importantly, compression of large sized images is required for everyday tasks; including electronic data communications and internet transactions. However, two important measures should be considered for any compression algorithm: the compression factor and the quality of the decompressed image. In this paper, we use Frei-Chen bases technique and the Modified Run Length Encoding (RLE) to compress images. The Frei-Chen bases technique is applied at the first stage in which the average subspace is applied to each 3 × 3 block. Those blocks with the highest energy are replaced by a single value that represents the average value of the pixels in the corresponding block. Even though Frei-Chen bases technique provides lossy compression, it maintains the main characteristics of the image. Additionally, the Frei-Chen bases technique enhances the compression factor, making it advantageous to use. In the second stage, RLE is applied to further increase the compression factor. The goal of using RLE is to enhance the compression factor without adding any distortion to the resultant decompressed image. Integrating RLE with Frei-Chen bases technique, as described in the proposed algorithm, ensures high quality decompressed images and high compression rate. The results of the proposed algorithms are shown to be comparable in quality and performance with other existing methods. [ABSTRACT FROM AUTHOR]

The paper presents the analysis and diagnosis of cables for data transmission in telecommunications. Among these data transmission cables, the paper presents the optical cable and the UTP cable. For these cables, following the analysis and diagnosis, the defects that appeared were fixed. At the same time, the services provided through the repaired cables were also checked. [ABSTRACT FROM AUTHOR]

The paper addresses the challenge of transmitting a big number of files stored in a data center (DC), encrypting them by compilers, and sending them through a network at an acceptable time. Face to the big number of files, only one compiler may not be sufficient to encrypt data in an acceptable time. In this paper, we consider the problem of several compilers and the objective is to find an algorithm that can give an efficient schedule for the given files to be compiled by the compilers. The main objective of the work is to minimize the gap in the total size of assigned files between compilers. This minimization ensures the fair distribution of files to different compilers. This problem is considered to be a very hard problem. This paper presents two research axes. The first axis is related to architecture. We propose a novel pre-compiler architecture in this context. The second axis is algorithmic development. We develop six algorithms to solve the problem, in this context. These algorithms are based on the dispatching rules method, decomposition method, and an iterative approach. These algorithms give approximate solutions for the studied problem. An experimental result is implemented to show the performance of algorithms. Several indicators are used to measure the performance of the proposed algorithms. In addition, five classes are proposed to test the algorithms with a total of 2350 instances. A comparison between the proposed algorithms is presented in different tables discussed to show the performance of each algorithm. The result showed that the best algorithm is the Iterative-mixed Smallest-Longest-Heuristic (ISL) with a percentage equal to 97.7% and an average running time equal to 0.148 s. All other algorithms did not exceed 22% as a percentage. The best algorithm excluding ISL is Iterative-mixed Longest-Smallest Heuristic (ILS) with a percentage equal to 21,4% and an average running time equal to 0.150 s. [ABSTRACT FROM AUTHOR]

Due to laws, regulations, privacy, etc., between 70-90 percent of providers do not share medical data, forming a "data island". It is essential to collaborate across multiple institutions without sharing patient data. Most existing methods adopt distributed learning and centralized federal architecture to solve this problem, but there are problems of resource heterogeneity and data heterogeneity in the practical application process. This paper proposes a collaborative deep learning modelling method based on the blockchain network. The training process uses encryption parameters to replace the original remote source data transmission to protect privacy. Hyperledger Fabric blockchain is adopted to realize that the parties are not restricted by the third-party authoritative verification end. To a certain extent, the distrust and single point of failure caused by the centralized system are avoided. The aggregation algorithm uses the FedProx algorithm to solve the problem of device heterogeneity and data heterogeneity. The experiments show that the maximum improvement of segmentation accuracy in the collaborative training mode proposed in this paper is 11.179% compared to local training. In the sequential training mode, the average accuracy improvement is greater than 7%. In the parallel training mode, the average accuracy improvement is greater than 8%. The experimental results show that the model proposed in this paper can solve the current problem of centralized modelling of multicenter data. In particular, it provides ideas to solve privacy protection and break "data silos", and protects all data. [ABSTRACT FROM AUTHOR]

Cryptography field, which enables secure communication between civilians, governmental organizations, military forces, and many more, addresses security, confidentiality, and integrity of information being conveyed regardless of the medium used. Protection of priceless information resources on intranets, the Internet, and the cloud has become a vital demand of contemporary electronic security systems. In this paper, we deploy homomorphic data encryption (HDE) technique on Bipolar-valued Fuzzy Sub-Bigroups (BVFSB). Intuitionistic Fuzzy Sets were presented by Atanassov in 1986, as a modification of Fuzzy Sets, by taking into consideration the grade of membership value and non-membership value for each element in the universe. A fuzzy algebraic structure known as Bipolar-valued Fuzzy sub-bigroup of a bigroup has been established by applying the concept of bipolar-valued Fuzzy sets to bigroups. Some of the theorems related to homomorphism and anti-homomorphism, are stated and proved. [ABSTRACT FROM AUTHOR]

In many IIoT architectures, various devices connect to the edge cloud via gateway systems. For data processing, numerous data are delivered to the edge cloud. Delivering data to an appropriate edge cloud is critical to improve IIoT service efficiency. There are two types of costs for this kind of IoT network: a communication cost and a computing cost. For service efficiency, the communication cost of data transmission should be minimized, and the computing cost in the edge cloud should be alsominimized. Therefore, in this paper, the communication cost for data transmission is defined as the delay factor, and the computing cost in the edge cloud is defined as the waiting time of the computing intensity. The proposed method selects an edge cloud that minimizes the total cost of the communication and computing costs. That is, a device chooses a routing path to the selected edge cloud based on the costs. The proposed method controls the data flows in a mesh-structured network and appropriately distributes the data processing load. The performance of the proposed method is validated through extensive computer simulation. When the transition probability from good to bad is 0.3 and the transition probability from bad to good is 0.7 in wireless and edge cloud states, the proposed method reduced both the average delay and the service pause counts to about 25% of the existing method. [ABSTRACT FROM AUTHOR]

Scan chain-based attacks are side-channel attacks focusing on one of the most significant features of hardware test circuitry. A technique called Design for Testability (DfT) involves integrating certain testability components into a hardware design. However, this creates a side channel for cryptanalysis, providing crypto devices vulnerable to scan-based attacks. Advanced Encryption Standard (AES) has been proven as the most powerful and secure symmetric encryption algorithm announced by USA Government and it outperforms all other existing cryptographic algorithms. Furthermore, the on-chip implementation of private key algorithms like AES has faced scan-based side-channel attacks. With the aim of protecting the data for secure communication, a new hybrid pipelined AES algorithm with enhanced security features is implemented. This paper proposes testing an AES core with unpredictable response compaction and bit level-masking throughout the scan chain process. A bit-level scan flipflop focused on masking as a scan protection solution for secure testing. The experimental results show that the best security is provided by the randomized addition of masked scan flipflop through the scan chain and also provides minimal design difficulty and power expansion overhead with some negligible delay measures. Thus, the proposed technique outperforms the state-of-the-art LUT-based S-box and the composite sub-byte transformation model regarding throughput rate 2 times and 15 times respectively. And security measured in the avalanche effect for the sub-pipelined model has been increased up to 95 per cent with reduced computational complexity. Also, the proposed sub-pipelined S-box utilizing a composite field arithmetic scheme achieves 7 per cent area effectiveness and 2.5 times the hardware complexity compared to the LUT-based model. [ABSTRACT FROM AUTHOR]

The Smart Vehicle (SV) with multiple onboard sensors is one of the indispensable tools to collect dynamic traffic information in the Intelligent Transport System (ITS). In this paper, we aims at jointly relieving the cellular network load and the transmission energy consumption during the SVs' information uploading. A Green Cluster-based Traffic Information Acquisition Method named GCTIAM is proposed, where an edge clustering management architecture is designed to control the traffic information upload cycles of each SV. On this basis. We build an optimal clustering mechanism to further improve the energy utilization while relieve the cellular network load. The mechanism optimizes the cluster iteration radius and divides SVs into different competitive areas according to their movement characteristic. An adaptive multi-parameter iteration among the same competitive area will be executed to decide the data transmission mode and build optimal cluster structures by considering dynamic parameters such as link duration time, uploading data volume etc.. The simulation results show that the proposed scheme can reduce the transmission energy consumption by 81% while cut down the cellular access rate up to 70%. [ABSTRACT FROM AUTHOR]

Among the different challenges related to the improvement of wireless sensor network (WSN) performance, the optimization of energy consumption takes an important place. Basically, sensor nodes in WSN are powered by limited battery. These batteries can allow sensor nodes to be functional for a limited period of time then sensor nodes turn out to be dead. Enhancing energy consumption and finding new manners to save sensor nodes' energy is becoming essential and more challenging. Improving energy consumption for each sensor nodes leads to enhance the lifetime of WSN. Clustering is among the outstanding strategies to reach this goal. In this paper, a new scheme of routing protocol in WSN will be presented in order to minimize the energy consumption and improve WSN lifetime. The new scheme is proposed in order to find the best selection of cluster head (CH) by taking in consideration the energy at each sensor node. It has been proposed based on Firefly Algorithm. We have compared the proposed scheme with LEACH, EAMMH, SEP, E-SEP, BRE, NEAHC and WEB protocol. Experimental results show that the proposed scheme yields better performance than the compared routing protocols in terms of better energy consumption and packet delivery between sensor nodes and base station. Results obviously prove that the proposed scheme could improve the WSN lifetime. • A new scheme of routing protocol has been proposed in order to optimize the energy consumption by sensor nodes in WSN. • The proposed scheme has been proposed based on Fireflies optimization algorithm. • Results of simulation showed the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, we investigate how data transmissions may be affected by various types of optical interference introduced into the fiber on purpose, via a clip-on coupler. The research proved that transmissions may be jammed completely using inexpensive equipment readily available on the market, provided that the attacker has physical access to the fiber optic cable. The most dangerous attacks rely on a typical, slowly modulated communication laser with a rectangular waveform. This study urges further research aimed at counteracting such attacks. [ABSTRACT FROM AUTHOR]

Wireless acoustic sensor networks (WASN) usually demand uninterrupted and reliable data transmissions and an efficient path from the source nodes to the destination nodes, thus ensuring reliable delivery of sensitive or critical data with the use of multipath routing protocols. This paper presents a novel agent-drivenWASN relying on a set of static and mobile agents. In the proposed technique, the location address is functioned into the operating node and the destination node. Calculations of the midpoint between the operating and the destination nodes are followed by identifying the shortest path based on a reference axis, using a mobile agent and a location address. Such an approach aims to ensure maximum utilization of the communicating paths. Based on the information concerning partial topology of the network, the destination node computes the weight factor and multiple paths using node distances, energy ratios and efficiencies of specific links. Then, the destination node selects the appropriate path from the multiple paths available, to transmit the data. This article also analyzes the performance of the proposed system with various parameters taken into consideration and shows its efficiency in comparison to other existing techniques. [ABSTRACT FROM AUTHOR]

In edge computing scenarios, IoT end devices play a crucial role in relaying and forwarding data to significantly improve IoT network performance. However, traditional routing mechanisms are not applicable to this scenario due to differences in network size and environment. Therefore, it becomes crucial to establish an effective and reliable data transmission path to ensure secure communication between devices. In this paper, we propose a trusted path selection strategy that comprehensively considers multiple attributes, such as link stability and edge cooperation, and selects a stable and secure data transmission path based on the link life cycle, energy level, trust level, and authentication status. In addition, we propose the Stability-based On-demand Multipath Distance Vector (STAOMDV) protocol based on the Ad hoc AOMDV protocol. The STAOMDV protocol implements the collection and updating of link stability attributes during the route discovery and maintenance process. By integrating the STAOMDV protocol with the proposed path selection strategy, a dependable and efficient routing mechanism is established for IoT networks in edge computing scenarios. Simulation results validate that the proposed STAOMDV model achieves a balance in network energy consumption and extends the overall network lifespan. [ABSTRACT FROM AUTHOR]

Automation systems are soaring due to the innovation of artificial intelligence (AI) technologies. In this paper, we mainly concentrate on the security and efficiency of data transmission in AI-based automation systems, especially, for data sharing in a group manner in distributed networks. To this end, an authenticated group key agreement protocol is proposed for secure data transmission in AI-based automation systems. In order to release the computational overhead of distributed nodes, a semi-trusted authority (STA) is introduced to enable precomputation operations. Moreover, to overcome the predominantly distributed denial of service (DDoS) attack, a dynamic batch verification mechanism is devised. The presented dynamic batch verification mechanism guarantees that the proposed protocol can be run properly among legitimate nodes regardless of the existence of nodes who suffered from the DDoS attack. Finally, the session key security of the proposed protocol is proved and the performance is evaluated. [ABSTRACT FROM AUTHOR]

Internet has changed and evolved since its origin and in recent time the communication channel for the internet has developed a flexible system design to accommodate newer devices and customized services. Internet of Medical Things (IoMT) is one such blooming service for larger data processing and customization. In this paper, we propose a novel interdependency attribute protocol for authentication and enhancing security aspects of IoMT communication. The protocol is developed on remote monitoring and Message Queuing Telemetric Transport (MQTT) protocol foundation values to secure data transmission and communication via active public domain internet and cloud storage. The approach is developed on machine learning models for attribute customization and classification. The model has been validated with AWS open pipeline cloud platforms for IoMT devices customization. The IoMT device cloud server evaluation and authentication via interdependency attribute protocol has outperformed the existing security models and analysis with Machine learning tools. [ABSTRACT FROM AUTHOR]

Recently, various security threats such as data leakage and data forgery have been possible in the communication and storage of data shared in the cloud environment. This paper conducted a study on the CP-ABSC scheme to solve these security threats. In the existing CP-ABSC scheme, if the data is obtained by the unsigncryption of the data user incorrectly, the identity of the data owner who uploaded the ciphertext cannot be known. Also, when verifying the leaked secret key, the identity information of the data user who leaked the secret key cannot be known. In terms of efficiency, the number of attributes can affect the ciphertext. In addition, a large amount of computation is required for the user to unsigncrypt the ciphertext. In this paper, we propose ECP-ABSC that provides data user traceability, and use it in a cloud environment to provide an efficient and secure data sharing scheme. The proposed ECP-ABSC scheme can trace and verify the identity of the data owner who uploaded the ciphertext incorrectly and the data user who leaked the secret key for the first time. In addition, the ciphertext of a constant size is output and the efficiency of the user's unsigncryption computation were improved. [ABSTRACT FROM AUTHOR]

In modern computing environments, speed of execution of any operations are gaining more attentions. The faster processing of the unit operations, opens the room for the applications such as cryptography, data communication etc. Hence, in this work a new software-oriented approach is proposed to use in the environments that requires faster executions. This proposed method speeds up the computations of the logical operations – bitwise XOR. This paper first elaborates on the procedure of how to construct the bitwise XOR vector space efficiently using recursive approach based on Pauli's matrix. The corresponding time complexity for the construction of the bitwise XOR vector space is computed by master theorem and is O (log 2 (n / 2 n)). Later, the paper presents on the implementation of this bitwise XOR vector space constructed to facilitate the XOR – Free operations. For the evidential proof, the proposed bitwise XOR-free operations are implemented on standard key stream generation scheme, SNOW 3G. The average speed up gained by the bitwise XOR-Free operations on the SNOW 3G is 1.36 x and the corresponding throughput attained is 21.85 Mbps. [ABSTRACT FROM AUTHOR]

In modern computing environments, speed of execution of any operations are gaining more attentions. The faster processing of the unit operations, opens the room for the applications such as cryptography, data communication etc. Hence, in this work a new software-oriented approach is proposed to use in the environments that requires faster executions. This proposed method speeds up the computations of the logical operations – bitwise XOR. This paper first elaborates on the procedure of how to construct the bitwise XOR vector space efficiently using recursive approach based on Pauli's matrix. The corresponding time complexity for the construction of the bitwise XOR vector space is computed by master theorem and is O (log 2 (n / 2 n)). Later, the paper presents on the implementation of this bitwise XOR vector space constructed to facilitate the XOR – Free operations. For the evidential proof, the proposed bitwise XOR-free operations are implemented on standard key stream generation scheme, SNOW 3G. The average speed up gained by the bitwise XOR-Free operations on the SNOW 3G is 1.36 x and the corresponding throughput attained is 21.85 Mbps. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surface (IRS) is a key technology for sixth-generation (6G) wireless communication to obtain high energy and spectral efficiency with a minimum cost. On the other hand, non orthogonal multiple access (NOMA) enhances the spectrum efficiency of the network. The combining schemes are implemented to obtain error-free data at the receiver. This paper proposes an IRS-aided NOMA-based packet combining (PC) and aggressive packet combining (APC) schemes-assisted communication architecture to enhance service quality and achieve sustainable and resilient connectivity among users for 6G wireless networks. In this paper, the mathematical model has been derived for the instantaneous achievable data rate, bit error rate, outage probability, and packet correction capability. The derived analytical expressions are validated through detailed Monte Carlo simulations. The obtained results show that the proposed schemes outperform the conventional NOMA with PC and NOMA with APC schemes and facilitate enhanced error control and reliable data transmission capabilities. Moreover, the proposed schemes have been compared with the IRS-aided orthogonal multiple access (OMA) schemes, where IRS-aided OMA schemes are considered benchmarks of the proposed schemes. It is presented that the proposed schemes are superior to the conventional OMA with PC and APC schemes and IRS-aided OMA with PC and APC schemes. [ABSTRACT FROM AUTHOR]

This paper presents a brief review of ciphering methods for secure image communications in the contexts of Internet of Things (IoT) and artificial intelligence. With the rapid advancements in mobile computing and the diversity of public data storing devices, ensuring robust security mechanisms has become a critical area of focus. We acknowledge the importance of historical context and the evolution of encryption/decryption approaches, and we aim to establish a systematic understanding of lightweight image encryption in IoT applications. To this end, a use case for AES image encryption will be highlighted to provide practical insights. Moreover, an abstract ciphering approach is suggested towards limiting the image-related de-anonymization attacks which can occur over publicly shared trained image sets. [ABSTRACT FROM AUTHOR]

Health monitoring systems are now required, particularly for essential patients, following the COVID-19 pandemic, which was followed by its variants and other epidemics of a similar nature. Effective procedures and strategies are required, though, to react promptly to the enormous volume of real-time data offered by monitoring equipment. Although fog-based designs for IoT health systems typically result in enhanced services, they also give rise to issues that need to be resolved. In this paper, we propose a two-way strategy to reduce network latency and usewhile increasing real-time data transmission of device gateways used for sensors by making educated judgments for connection setup with BS and task assignment. For this, a simulation using iFogSim in the Eclipse IDE showed how effective the suggested strategy for massive IoT healthmonitoring systems is. The algorithm is analyzed for network usage and latency, and the results reveal 20%-25% improvements compared to the existing methods regarding network usage and latency. [ABSTRACT FROM AUTHOR]

Content poisoning attacks compromise the integrity of web platforms by injecting malicious data. This paper presents a comprehensive study of these attacks, examining their methodologies and potential impacts. Through rigorous analysis, we highlight key vulnerabilities and propose effective countermeasures to ensure robust digital content security. Under the security hardness of the HCDLP, the suggested approach is technically secured. We are changing medical data depending on priority. The fuzzy-based priority aware scheme is proposed in order to have priority-based data transmission for the essential and high priority data from the essential patients. [ABSTRACT FROM AUTHOR]