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With the advent of cloud computing, secured data deduplication has gained a lot of popularity. Many techniques have been pro-posed in the literature of this ongoing research area. Among these techniques, the Message Locked Encryption (MLE) scheme is often mentioned. Researchers have introduced MLE based protocols which provide secured deduplication of data, where the data is generally in text form. As a result, multimedia data such as images and video, which are larger in size compared to text files, have not been given much attention. Applying secured data deduplication to such data files could significantly reduce the cost and space required for their storage. In this paper we present a secure deduplication scheme for near identical (NI) images using the Dual Integrity Convergent Encryption (DICE) protocol, which is a variant of the MLE based scheme. In the proposed scheme, an image is decomposed into blocks and the DICE protocol is applied on each block separately rather than on the entire image. As a result, the blocks that are common between two or more NI images are stored only once at the cloud. We provide detailed analyses on the theoretical, experimental and security aspects of the proposed scheme. [ABSTRACT FROM AUTHOR]

Generating a secret key from the physical layer is one of the most challenging topics in cryptography. Secret key generation rate (SKGR) and secrecy rate (SR) are two important concepts for any secure communication scheme. In this paper, we first propose a new power allocation strategy to minimize the power consumption under a given SKGR constraint for orthogonal frequency division (OFDM) based communication systems. Due to the non-convex nature of the SKGR expression, we convert the optimization problem into a convex problem. In the continuation of this paper, we investigate the effects of the proposed power allocation strategy on the SR performance. Simulation results demonstrate that using the obtained optimum power vector, which was calculated in the key generation phase, we achieve a better level of SR in the data communication phase. The simulation results also verify that the average SR performance obtained by the proposed method is superior to the geometric programing (GP)-based method. [ABSTRACT FROM AUTHOR]

Internet of Things search has great potential applications with the rapid development of Internet of Things technology. Combining Internet of Things technology and academic search to build academic search framework based on Internet of Things is an effective solution to realize massive academic resource search. Recently, the academic big data has been characterized by a large number of types and spanning many fields. The traditional web search technology is no longer suitable for the search environment of academic big data. Thus, this paper designs academic search framework based on Internet of Things Technology. In order to alleviate the pressure of the cloud server processing massive academic big data, the edge server is introduced to clean and remove the redundancy of the data to form a clean data for further analysis and processing by the cloud server. Edge computing network effectively makes up for the deficiency of cloud computing in the conditions of distributed and high concurrent access, reduces long-distance data transmission, and improves the quality of network user experience. For Academic Search, this paper proposes a novel weakly supervised academic search model based on knowledge-enhanced feature representation. The proposed model can relieve high cost of acquisition of manually labeled data by obtaining a lot of pseudolabeled data and consider word-level interactive matching and sentence-level semantic matching for more accurate matching in the process of academic search. The experimental result on academic datasets demonstrate that the performance of the proposed model is much better than that of the existing methods. [ABSTRACT FROM AUTHOR]

This paper investigates a new class of carrier-sense multiple access (CSMA) protocols that employ deep reinforcement learning (DRL) techniques, referred to as carrier-sense deep-reinforcement learning multiple access (CS-DLMA). The goal of CS-DLMA is to enable efficient and equitable spectrum sharing among a group of co-located heterogeneous wireless networks. Existing CSMA protocols, such as the medium access control (MAC) protocol of WiFi, are designed for a homogeneous network in which all nodes adopt the same protocol. Such protocols suffer from severe performance degradation in a heterogeneous environment where there are nodes adopting other MAC protocols. CS-DLMA aims to circumvent this problem by making use of DRL. In particular, this paper adopts α-fairness as the general objective of CS-DLMA. With α-fairness, CS-DLMA can achieve a range of different objectives (e.g., maximizing sum throughput, achieving proportional fairness, or achieving max-min fairness) when coexisting with other MACs by changing the value of α. A salient feature of CS-DLMA is that it can achieve these objectives without knowing the coexisting MACs through a learning process based on DRL. The underpinning DRL technique in CS-DLMA is deep Q-network (DQN). However, the conventional DQN algorithms are not suitable for CS-DLMA due to their uniform time-step assumption. In CSMA protocols, time steps are non-uniform in that the time duration required for carrier sensing is smaller than the duration of data transmission. This paper introduces a non-uniform time-step formulation of DQN to address this issue. Our simulation results show that CS-DLMA can achieve the general α-fairness objective when coexisting with TDMA, ALOHA, and WiFi protocols by adjusting its own transmission strategy. Interestingly, we also find that CS-DLMA is more Pareto efficient than other CSMA protocols, e.g., p-persistent CSMA, when coexisting with WiFi. Although this paper focuses on the use of our non-uniform time-step DQN formulation in wireless networking, we believe this new DQN formulation can also find use in other domains. [ABSTRACT FROM AUTHOR]

The Smart Grid represents an unprecedented opportunity to move the electric grid into a new era of reliability, availability, and efficiency. It uses two-way communications, digital technologies, advanced sensing and computing infrastructure, and software abilities to provide improved monitoring, protection and optimization of all the grids’ components including generation, transmission, distribution and consumers. [ABSTRACT FROM AUTHOR]

Recently, in the present day's data center systems an explosive growth has been observed in data traffic, which restricts the speed of exiting data communication network. To solve such problem, fiber optical-based optical communication system is preferred choice. In this paper, an arrayed waveguide grating (AWG)-based optical packet switch is presented in which priority among packets is implemented effectively. This switch is a recirculating loop buffer-based switch in which a hybrid buffering (optical + electrical) technique is used for storing packets into the buffer. The power budget analysis of switch is presented in various conditions, when packet passes through the optical or electronic buffers. Comparison of optical and electronic buffering is done in terms of power required for the correct operation of the switch. In this paper, a comparison is performed between our proposed switch with recently published switch designs. The result presented in this paper clearly reveals that the performance of our proposed switch is far better than other previously published switch architecture. The major beauty of our proposed switch is that in this design priority among packets implemented effectively. [ABSTRACT FROM AUTHOR]

One of the key issues in wearable electronics is data transmission over wireless networks. Among the most commonly used solutions are Bluetooth Low Energy (BLE), as well as the ZigBee protocol, which are characterized by low power consumption and low implementation cost. The functionality of such solutions also depends on the energy consumption of the proposed solutions, as well as their size and weight. The purpose of this paper is to analyze selected communication techniques, which were compared in terms of their range and energy efficiency. The paper presents results on wireless communication tests. A comparison is presented of Bluetooth communication range carried out under different conditions, such as in a building where there were no obstacles and in a public facility. In order to compare Bluetooth communication parameters, different phone models were used. [ABSTRACT FROM AUTHOR]

In a medical emergency situation, real-time patient data sharing may improve the survivability of a patient. In this paper, we explore how Digital Twin (DT) technology can be used for real-time data storage and processing in emergency healthcare. We investigated various enabling technologies, including cloud platforms, data transmission formats, and storage file formats, to develop a feasible DT storage solution for emergency healthcare. Through our analysis, we found Amazon AWS to be the most suitable cloud platform due to its sophisticated real-time data processing and analytical tools. Additionally, we determine that the MQTT protocol is suitable for real-time medical data transmission, and FHIR is the most appropriate medical file storage format for emergency healthcare situations. We propose a cloud-based DT storage solution, in which real-time medical data are transmitted to AWS IoT Core, processed by Kinesis Data Analytics, and stored securely in AWS HealthLake. Despite the feasibility of the proposed solution, challenges such as insufficient access control, lack of encryption, and vendor conformity must be addressed for successful practical implementation. Future work may involve Hyperledger Fabric technology and HTTPS protocol to enhance security, while the maturation of DT technology is expected to resolve vendor conformity issues. By addressing these challenges, our proposed DT storage solution has the potential to improve data accessibility and decision-making in emergency healthcare settings. [ABSTRACT FROM AUTHOR]

The increasing usage of several nodes to transfer the massive volume of data to the remotes in wireless sensor networks is a challenging task to reduce the loss. The high volumes of data transmission in wireless sensor networks (WSN) can surpass their capacity, resulting in congestion, latency issues, and packet loss. However, computational intelligence (CI) models can aid in managing and creating intelligent networks in WSN. The WSN congestion issues result in information loss and increased energy usage. CI-based models have been used to resolve this issue, reducing the latency. This paper proposes SoftMax Routing with Deep Neural Network (SRDNN) for efficient routing in WSN. This will route the data packets by choosing the high energy and lower load. It consists of two parts, such as the construction of the routing path, which determines the residual energy of the node. It is analyzed using SoftMax routing to decide whether the node is efficient in energy. The route request and reply established various paths between the source and destination. The path with minimum buffer space and maximum bandwidth is chosen in the optimal routing. The simulation results under the metrics such as energy consumption, data loss rate, throughput, and delay show the proposed model performance. [ABSTRACT FROM AUTHOR]

This paper presents an eye-opening monitor technique leveraging four-level pulse amplitude modulation (PAM-4) symbol transition characteristics. This approach facilitates the evaluation of data transmission quality concerning the adaptive coefficient settings of PAM-4 equalizers. The two-dimensional (2D) symbol transition mapping visually depicts the degree of intersymbol interference (ISI). This work expands upon the 2D mapping model introduced in [14], adding more theoretical analysis and new simulation results. Both simulation and empirical results indicate that 2D symbol mapping can assess the quality of PAM-4 data transmission impaired by ISI and can visually represent the equalization effect. [ABSTRACT FROM AUTHOR]

The most flexible and reliable technological system is Wi-Fi, which is made possible by a wireless connection that transmits data using radio frequencies. Wi-Fi networks, however, encounter numerous issues related to power supply, availability, efficiency, and security as a result of the various access points. While relational waves describe the medical device, Wi-Fi radios produce radio waves that are very dangerous for patients. This document offers line-of-sight communication between the transmitter and receiver using LED technology. Li-Fi technology is a method that transmits audio data using LED light, which is faster and more efficient than Wi-Fi. Since it is practically ubiquitous, light can be used for communication as well. A cutting-edge technology called optical communication includes a subset called light fidelity. By sending out visible light, the Li-Fi device enables wireless intranet communication. This paper is an in-depth study and analysis of Light Fidelity (Li-Fi), a novel technology that transmits data at high speeds over a wide spectrum by using light as a medium of transmission. The research fields that are pertinent to Li-Fi networks are thoroughly analyzed and categorized in this paper: high speed data transmission, receiving, sharing, broadcasting through light in free space optical communication system by Li-Fi technology. In this paper, we followed some methods and developed a unique method to develop this study: VLC, OOK, a Lambertian discharge mechanism, LOS, NLOS, or a CMOS optical receiver. The proposed model tested transmits and receives audio, video, and other data, which is very high-rated and near the 2 GB/s range. [ABSTRACT FROM AUTHOR]

The process of sending confidential data through the communication media and in complete secrecy is now necessary, whether the data is related to patients, a particular military operation, or a specified office. On the other hand, with the development of various ciphering algorithms, and information hiding algorithms, there is a need to obtain ciphered and hidden data securely without the need to exchange secret keys between the two ends of the communication. In this paper, a hiding algorithm based on fused images and Caesar cipher with intelligent methods to strengthen the security of confidential information is proposed. Firstly, fused image scattering is obtained using 1’s complement and circularly shifting the bits of fused pixels by specified positions before the hiding process. Secondly, the keys for the Caesar cipher are derived from the length of secret information according to the mathematical equation. Thirdly, strengthen the security of Caesar’s cipher by taking a 1’s complement of each letter in the cipher data. The results guarantee the security of the presented algorithm. [ABSTRACT FROM AUTHOR]

Energy efficiency, real-time response, and data transmission reliability are important objectives during networked systems design. This paper aims to develop an efficient task mapping scheme to balance these important but conflicting objectives. To achieve this goal, tasks are triplicated to enhance reliability and mapped on the wireless nodes of the networked systems with Dynamic Voltage and Frequency Scaling (DVFS) capabilities to reduce energy consumption while still meeting real-time constraints. Our contributions include the mathematical formulation of this task mapping problem as mixed-integer programming that balances node energy consumption, enhancing data reliability, under real-time and energy constraints. Compared with the State-of-the-Art (SoA), a joint-design problem is considered in this paper, where DVFS, task triplication, task allocation, and task scheduling are optimized concurrently. To find the optimal solution, the original problem is linearized, and a decomposition-based method is proposed. The optimality of the proposed method is proved rigorously. Furthermore, a heuristic based on the greedy algorithm is designed to reduce the computation time. The proposed methods are evaluated and compared through a series of simulations. The results show that the proposed triplication-based task mapping method on average achieves 24.84% runtime reduction and 28.62% energy saving compared to the SoA methods. [ABSTRACT FROM AUTHOR]

High-data-throughput and multimodal-acquisition experiments will prevail in next-generation synchrotron beamlines. Orchestrating dataflow pipelines connecting the data acquisition, processing, visualization and storage ends are becoming increasingly complex and essential for enhancing beamline performance. Mamba Data Worker (MDW) has been developed to address the data challenges for the forthcoming High Energy Photon Source (HEPS). It is an important component of the Mamba experimental control and data acquisition software ecosystem, which enables fast data acquisition and transmission, dynamic configuration of data processing pipelines, data multiplex in streaming, and customized data and metadata assembly. This paper presents the architecture and development plan of MDW, outlines the essential technologies involved, and illustrates its current application at the Beijing Synchrotron Radiation Facility (BSRF). [ABSTRACT FROM AUTHOR]

Recent advancements in deep learning have led to various challenges, one of which is the issue of data privacy in training data. To address this issue, federated learning, a technique that merges models trained by clients on servers, has emerged as an attractive solution. However, federated learning faces challenges related to data heterogeneity and system heterogeneity. Recent observations suggest that incorporating pre-trained models into federated learning can mitigate some of these challenges. Nonetheless, the main drawback of pre-trained models lies in their typically large model size, leading to excessive data transmission when clients send these models to the server. Additionally, federated learning involves multiple global steps, which means transmitting a large language model to multiple clients results in too much data exchange. In this paper, we propose a novel approach to address this challenge using adapters. Adapters demonstrate training efficiency by training a small capacity adapter layer alongside a large language model. This unique characteristic reduces the volume of data transmission, offering a practical solution to the problem. The evaluation results demonstrate that the proposed method achieves a reduction in training time of approximately 20–40% and a transmission speed improvement of over 98% compared to previous approaches. [ABSTRACT FROM AUTHOR]

With the rise of satellite-as-a-service subscriptions as technology improves, our paper examines how satellite operators (SOs) can choose between traditional channels for selling satellites, satellite-as-a-service (SataaS), and dual-channel strategies. In the space supply chain, commercial satellites display several distinct characteristics that differentiate them from other physical commodities in traditional supply chains, most notably their exposure to significant launch risks. In addition, SataaS suffers from the risk of secure data transmission. However, the emergence of novel technologies such as blockchain technology (BCT) could help to mitigate such risks. Therefore, our study analyzes the optimal strategy among the sell, SataaS, and dual-channel approaches for SOs by considering the above distinctive characteristics in the case without blockchain and the case with blockchain. Our paper reveals the existence of a dual-channel strategy that generates the highest profit for the SO and yields the highest consumer utility when launch success is high and when SataaS fixed costs are low. When the launch success rate is very high, the dual-channel strategy transforms into a pure sell strategy. After the adoption of BCT, when the cost of BCT is low, the SO's profit is enhanced in all three sales channels compared to the case without blockchain. Notably, in SataaS as well as in the dual-channel approach, the adoption of BCT always improves consumer utility compared to the case without blockchain. However, in the sell channel, the consumer benefits depend on the relatively low cost of blockchain customization. [ABSTRACT FROM AUTHOR]

Communication between a nanosatellite located in Low Earth Orbit (LEO) and a ground station is limited in regions far from the poles, occurring for only a few minutes on different days and at different times. By utilizing satellite-to-satellite communication, it is possible to transmit and receive information more efficiently, circumventing the restrictions inherent in satellite-ground station links. The objective of this study is to present a comparative report on the results of data transmission through inter-satellite and satellite-to-ground station communication, focusing on a 1U CubeSat nanosatellite (AztechSat-1). This paper discusses the use of the GlobalStar network and a nanosatellite for inter-satellite communication. This paper also discusses the use of proprietary and open-source ground stations for satellite-ground communication. We provide an overview of the GlobalStar network and the associated ground stations involved in this research, along with the results and their subsequent analysis. [ABSTRACT FROM AUTHOR]

This paper proposes the development of a wheelchair control system by combining a Mindwave electroencephalogram (EEG) sensor, an MPU6050 inertial sensor, an ultrasonic sensor, and internet of things (IoT) technology. Stroke survivors often face challenges in controlling their wheelchairs due to cognitive and physical impairments, requiring specific solutions to ensure their safety and comfort. The integration of the Mindwave EEG sensor captures the user's cognitive state, such as level of attention and focus, while the MPU6050's inertial sensor monitors physical movement and changes in head orientation. Additionally, the ultrasonic sensor is incorporated to detect obstacles and provide proximity information for safe navigation. This wheelchair control system is also linked with IoT technology to enable monitoring of the user's cognitive, physical and environmental condition, and remote assistance. In this paper, to implement this wheelchair control system, a T-BEAM with an ESP32 controller is used, which is equipped with GPS to provide wheelchair location data and LORA radio communication for remote data transmission, and a TTGO LORA32 to forward the data to Arduino IoT cloud service over Wi-Fi. The results of the development show that the wheelchair control system is safer and more monitored, and users are easier and more flexible in operating wheelchairs. [ABSTRACT FROM AUTHOR]

Design methods are presented for chip pulses and a constant envelope multiplexing (CEM) scheme for a new navigation satellite system in the S band. If we assume three equal-power signals are needed to transmit, the chip pulses of at least two signals can have two or more sample magnitudes for a high CEM power efficiency. Considering a case with two dual-magnitude signals, we can find the magnitude values for a target efficiency and then design the magnitude and sign patterns. We analyze the interference for all possible chip pulse sets and sorted them according to selected priorities. We also consider spectral separation between two different signal groups for a flexible operation. The design methods and the results provided in this paper can be a good reference for the signal design of a new navigation satellite system. [ABSTRACT FROM AUTHOR]

Mission-critical applications refer to the real-time applications, which require fast and secure service provisioning, such as defense sector and disaster management. This paper proposes a delay-aware and secure service provisioning model for such types of applications. As a use-case, we have considered the defense sector, which is a vital sector for a country's all-round well-being including security, safety, society, and economy. In the conventional sensor-cloud model, the sensor data is stored and processed in the cloud. However, the sensor nodes have small coverage and the use of the long distant cloud servers increases the delay. Therefore, the conventional sensor-cloud model may not be efficient for defense application. Moreover, data hiding for security purposes is another important aspect of this field. To address these challenges, this paper proposes a mobility-aware sensor-fog paradigm for mission-critical applications based on network coding and steganography, referred to as Mobi-Sense. In Mobi-Sense, steganography is used for hiding the data during transmission. The theoretical results demonstrate that Mobi-Sense outperforms the existing frameworks with respect to delay and power consumption by ∼ (40 - 80) %. The simulation results present that Mobi-Sense reduces the delay by ∼ (18 - 40) % than the conventional sensor-cloud framework for mission-critical applications. An optimal path finding algorithm based on deep learning has been deployed in the context of disaster scenario. The experimental analysis shows that the proposed optimal path finding method achieves precision and accuracy above 90%. This is observed that our proposed modules have outperformed existing baselines in terms of accuracy, delay, and power consumption. [ABSTRACT FROM AUTHOR]

To store, analyse and process the large volume of data generated by IoT traditional cloud computing, is used everywhere. However, the traditional cloud data centres have their limitations to handle high latency issues in time-critical applications of IoT and cloud. Their applications are computer gaming, e-healthcare, telemedicine and robot surgery. The high latency in IoTs and cloud includes high computational, communication latency (service) and network latencies. The vital requirement of IoT is to have minimum network, service and computation latencies for real-time applications. Network latency causes a delay in transmitting a message or communication from one location to another. Services that require data in real-time are almost impossible to access the data via the cloud. Traditional cloud computing approaches are unable to fulfil the quality-of-service (QoS) requirements in IoT devices. Researches related to latency reduction techniques are still in infancy. Some new approaches to minimize the latency for transmitting time-sensitive data in real-time are discussed in this paper for cloud and IoT devices. This research will help the researchers and industries to identify the techniques and technologies to minimize the latencies in IoT and cloud. The paper also discusses the research trends and the technical differences between the various technologies and techniques. With the increasing interest in the literature on latency minimization and its requirements for time-sensitive applications; it is important to systematically review and synthesize the approaches, tools, challenges and techniques to minimize latencies in IoT and cloud. This paper aims at systematically reviewing the state of the art of latency minimization to classify approaches, and techniques. The paper uses a PRISMA technique for a systematic review. The paper further identifies challenges and gaps in this regard for future research. We have identified 23 approaches and 32 technologies associated with latencies in the cloud and IoT. A total of 112 papers on latency reduction have been examined under this study. The existing research gaps and works for latency reduction in IoTs are discussed in detail. There are several challenges and gaps, which requires future research work for improving the latency minimization techniques and technologies. Finally, we present some open issues which will determine the future research direction. [ABSTRACT FROM AUTHOR]

Particularly, for real time monitoring-IOT has just evolved to support massive capacity Cellular LTE networks. The fundamental issue is the constrained bandwidth that NB-IOT channels allow. Therefore, goal of paper is to enhance the capacity of the NB-IOT physical layer shared channels for uplink and down links. The primary objective of this article is to improve the efficiency of an LTE-OFDM framework for NB-IOT-WAN via BER and BLER assessment. The proposed approach improves performance by selecting suitable cyclic prefix sampling with FFT size. It is planned to adopt M-QAM for increased data transmission capacity and reducing OFDM BER. In order to enhance the capacity approach of diversity reception is considered along with the modified modulation parameters. Increased FFT size is offered for OFDM capacity enhancement for narrowband physical downlink shared channel (NPDSCH) and narrowband physical uplink shared channel (NPUSCH) transceivers. The block error rate (BLER) is used as the performance evaluation parameters for the LTE-OFDM based NB-IOT system. The impact of the higher block transmission length is assessed for the improvement in the BLER rates. It is proposed to use M-QAM for NPUSCH which may offer better capacity of data transmission. The performance is compared with the standard QPSK modulation. For the uplink design under AWGN and frequency selective channels are considered for evaluation. The numbers of receiver antenna are increased for offering the better diversity reception to further enhance the channel capacity. The optimal design parameter selection might improve the performance of the NB-IOT cellular networks. The BLER is evaluated for different case of uplink and downlink designs against the wide range of the SNR. The entire document takes into account all factors in order to get the greatest system efficiency, and it offers capacity enhancement. [ABSTRACT FROM AUTHOR]

Summary: In order to solve the problem that IP address jump cannot be synchronized in real time due to the unstable speed of network data transmission in the Internet of Things system, in this paper, sliding window mechanism is introduced into network communication, and an Internet of Things system with network IP address jump function is constructed. The system adopts time synchronization scheme based on PTP protocol and IP address hopping strategy based on sliding window. The system includes three modules: time synchronization module based on PTP protocol to enhance security performance, address hopping module based on OpenFlow as core technology, and SDN routing module. The system can realize the security defense function of mobile devices on the Internet of Things. Finally, through the experimental test, it is found that, when the system time error is less than 18 s, the system's packet loss rate is stable and low. The anti‐attack ability is very strong. [ABSTRACT FROM AUTHOR]

Aiming at the problems of large data volume, long calculation time, and information feedback speed in traditional virtual augmented reality-based scenes, this paper constructed a virtual augmented reality scene based on 5G technology. First, based on the research of camera models and related calibration techniques, this article discusses the coordinate conversion and registration between virtual scenes and real scenes in augmented reality systems based on natural feature points. Secondly, the control mechanism of data synchronization and transmission are realized by using 5G communication technology. Then, through the approximate nearest neighbour search of the descriptor, the feature points are quickly matched. Finally, by tracking the QR-code logo black frame, the global holography matrix virtual real registration method relative to the initial image is used to calculate the camera's posture and the fast tracking registration of the scene is realized. The experimental results prove that the scene constructed in this paper has the characteristics of real-time, wide field of view, high immersion and flexible expansion, which not only meets the requirements of matching accuracy, but also has the advantages of small calculation amount and fast calculation speed, and has good robustness and real-time. [ABSTRACT FROM AUTHOR]

The existing routing protocols for wireless sensor networks were not reasonable in design, which limited their application. Most of the existing studies did not take into account the energy consumption of the network and the balanced use of the energy of sensor nodes, which led to the unsatisfactory application effect of wireless sensor networks in some fields. Therefore, from the perspective of energy balance in wireless sensor networks, this paper proposed a construction method of an energy balance routing protocol in wireless sensor networks based on a fuzzy control strategy. Firstly, based on the analysis of the basic composition of wireless sensor networks and the structure of sensor nodes, this paper expounded the basic process of wireless data transmission and summarized the classification and characteristics of routing protocols in wireless sensor networks from different angles. Secondly, according to the node data transmission characteristics of wireless sensor networks, the energy balance use model of sensor nodes was established, and the design method of the energy balance routing protocol based on fuzzy control strategy was proposed, and the data transmission link was optimized. Finally, through experimental comparative analysis, the results showed that the energy balanced routing protocol proposed in this paper can effectively realize the energy balanced use of the network data transmission process. Compared with other common routing protocols, the wireless sensor network routing protocol proposed in this paper can not only improve the data transmission efficiency and reduce the data redundancy but also save energy consumption and prolong the network running time. The design method of routing protocol proposed in this paper will be conducive to the optimization and application of routing protocol in wireless sensor networks and provide a theoretical basis for the related research of wireless sensor networks. [ABSTRACT FROM AUTHOR]

Orthogonal Frequency Division Multiplexing (OFDM) is a wireless communication technology that is used for highly reliable and high data rate communication. In a multi-user OFDM system, the interference has occurred in the receiver side between the consecutive OFDM symbols. This interference reduces the performance of the OFDM system. To achieve good quality in received symbols the interference level should be minimized. The conventional cancellation system requires higher interference reduction time and power. These limitations of the conventional interference cancellation architectures for OFDM systems are overcome by proposing efficient and low power interference cancellation architecture. Hence, this paper proposes a novel and efficient architecture based on logic gates for interference cancellation in multi-user OFDM systems. The proposed design consist of multiplexers, inverters and OR gate. The heuristic parameters for the proposed cancellation architecture are computed by performing an XOR operation. Compared to existing architecture, the proposed interference cancellation architecture consumes 7 mW of power consumption in the Virtex processor, 33.59 mW of power consumption in Spartan 3E processor and 0.029 mW of power consumption in the CPLD processor. This proposed interference cancellation architecture consumes fewer hardware resources and consumes low power. The proposed system is designed using Verilog High Definition Language (HDL) and synthesized in Xilinx Project Navigator 12.1i. Further, this paper also proposes gate diffusion input (GDI) based implementation of proposed interference cancellation architecture to analyse a delay and power consumption compared to other logic style implementation. [ABSTRACT FROM AUTHOR]

Objective: The objective was to investigate the performance of two search strategies in the retrieval of primary research papers containing descriptive information on the sleep of healthy people from MEDLINIE. Methodology: Two search strategies-one based on the use of only Medical Subject Headings (MeSH), the second based on text-word searching-were evaluated as to their specificity and sensitivity in retrieving a set of relevant research papers published in the journal Sleep from 1996 to 2001 that were preselected by a hand search. Results: The subject search provided higher specificity than the text- word search (66% and 47%, respectively) but lower sensitivity (78% for the subject search versus 88% for the text-word search). Each search strategy gave some unique relevant hits. Conclusions: The two search strategies complemented each other and should be used together for maximal retrieval. No combination of MeSH terms could provide comprehensive yet reasonably precise retrieval of relevant articles. The text-word searching had sensitivity and specificity comparable to the subject search. In addition, use of text words "normal," "healthy," and "control" in the title or abstract fields to limit the final sets provided an efficient way to increase the specificity of both search strategies. [ABSTRACT FROM AUTHOR]

This paper develops a statistics-based approach for analysis of transmission outage data. The method is applied to the Western Electricity Coordinating Council (WECC) transmission inventory and outage data collected and submitted by member utilities to the North American Electric Reliability Corporation's (NERC) Transmission Availability Data System (TADS). The developed model considers the random nature of Alternating Current (AC) circuit outages and introduces fourteen inventory attributes of the AC circuits as explanatory variables for the outage frequency. The main goal of the paper is to investigate statistical relationships between the number of automatic outages on AC circuits and AC circuit inventory attributes based on the TADS data from 2013–2018, which has proven to be sufficient in obtaining statistically valid results. Concepts associated with the statistical validation of performance indices are discussed with emphasis placed on analysis of distinct types of explanatory variables such as voltage class, mileage, number of terminals, circuits per structure, terrain, elevation, etc. [ABSTRACT FROM AUTHOR]

In this paper, we give a list of ATM related papers. This is not a complete list. Rather, it represents the bulk of the references in this ever-growing area. For easier use of this reference list, we have classified the papers into the following six categories: general, source characterization, switching, congestion control, routing, and transport. [ABSTRACT FROM AUTHOR]

This paper investigates the issue of asynchronous H∞ tracking control for nonlinear semi-Markovian jump systems (SMJSs) based on the T-S fuzzy model. Firstly, in order to improve the performance of network control systems (NCSs) and the efficiency of data transmission, this paper adopts a double quantization strategy which quantifies the input and output of the controllers. Secondly, for the purpose of reducing the burden of network communication, an adaptive event-triggered mechanism (AETM) is adopted. Thirdly, due to the influence of network-induce delay, the system mode information can not be transmitted to the controller synchronously, thus, a continuous-time hidden Markov model (HMM) is established to describe the asynchronous phenomenon between the system and the controller. Additionally, with the help of some improved Lyapunov-Krasovski (L-K) functions with fuzzy basis, some sufficient criteria are derived to co-guarantee the state stability and the H∞ performance for the closed-loop tracking control system. Finally, a numerical example and a practical example are given to verify the effectiveness of designed mentality. [ABSTRACT FROM AUTHOR]

The motivation to make information more accessible in data communication – physically to the senses and culturally to different audiences – has led designers to experiment, for example, in data physicalization and data sonification. Experimentation overlapping data communication and the performance arts suggests another practice is emerging. Calling it data embodiment, I define the term as a communicative and artistic method that approaches the body as a choreographic medium to physicalize and perform abstract data. The intent of this paper is to sufficiently delineate the space where bodily movement and abstract data have begun to intermingle across several milieu under the concept. The paper begins by contextualizing data embodiment in design, then continues by observing how choreographers have previously approached dance as data, and finishes with a case study where an environmental migration dataset is choreographed. A brief section on human-centered datasets and the surveillant technologies that produce them peppers the overarching discussion on bodily movement and abstract data. By reconstituting data in time and space, especially in the context of performance, otherwise sterile datasets are shown to become more physically and culturally accessible as well as aesthetically expressive. [ABSTRACT FROM AUTHOR]

This paper proposes a MAC protocol for ad hoc networks using In-band Full-duplex (IBFD) wireless communications, which are named as AdHoc-FDMAC. To utilize IBFD communications in ad hoc networks, this protocol modifies a number of control frames in the IEEE 802.11 Distributed Coordination Function (DCF) MAC standard. Here, the detailed time sequences for all types of IBFD communications are shown for the data transmission and routing. In this paper, the probability and throughput equations for IBFD communications in different situations have been derived. The performance of the proposed AdHoc-FDMAC has been analysed in terms of probability, throughput, and routing time. The Maximum throughput of AdHoc-FDMAC has been found to be 48.34 Mbps, and it is compared with a recently published ad hoc MAC as well as with the conventional HD MAC. The AdHoc-FDMAC outperforms the recently published ad hoc MAC and conventional HD MAC by 16.80% and 66.50% throughput gain, respectively. AdHoc-FDMAC incorporates the existing Ad hoc On-demand Distance Vector (AODV) routing protocol, but this AODV routing is utilized here using IBFD communications. This paper also compares the routing time of the IBFD-based AODV with the conventional AODV. The result shows that the IBFD-based AODV requires 33.33% less routing time than that of the conventional AODV for 3-hop distance between the transmitter and receiver. This paper suggests that the AdHoc-FDMAC protocol provides much more throughput in ad hoc networks by utilizing IBFD communications. [ABSTRACT FROM AUTHOR]

The present industrial Internet platform (IIP) is subjected to numerous complex security issues, and thus technologies that focus on achieving data security of the IIP has become top priority. The data security crisis of IIP gets mainly reflected in the malicious deletion and theft of data, the random access of terminal devices, and the low security of traditional security authentication methods. Blockchain technology adopts distributed network architecture, wherein through asymmetric encryption mechanism, it helps to solve problems associated with single point of downtime and privacy data leakage of central management of industrial Internet. In addition, considering the accept of random access and deletion of industrial interconnection terminal equipment, this paper uses the role access control mechanism based on Hyperledger, thereby regulating user access according to the user's role in the platform and management of terminal equipment through chain code. The paper includes the following contributions: (1) firstly, it expounds the research background and significance of the IIP and introduces the research status of the industrial Internet and blockchain at home and abroad. (2) Secondly, the IIP architecture is designed based on blockchain technology and implements a sensor node management and monitoring system. (3) Thirdly, the paper uses the gateway to preprocess the collected data, thereby reducing the data transmission delay and improving the real-time and effectiveness of the data. The paper finally implements neural network to evaluate the construction quality of industrial Internet sensor nodes and obtains promising test results. [ABSTRACT FROM AUTHOR]

The occurrence of 'sensing holes' not only hinders seamless data collection but also leads to misinterpretation of information in certain areas under extensive data analysis. In order to overcome this, various sensor relocation strategies have been proposed, but the existing relocation strategies revealed problems such as the ping-pong, shaded area, network disconnection, etc. This paper conducted research on relocation protocols in a distributed environment that is very suitable for real-world situations and efficiently recovering the problem of sensing holes. First, a simulation was performed on the distribution of the shaded area for data collection, which is a problem with the existing representative relocation protocol. After that, a data collection capability was newly added to the relay node, which had been in charge of only communication between cluster zones so far, and with this additional functionality, the performance of the revised sensor relocation algorithm was dramatically improved to overcome the existing problems. In addition, the performance and validity of the proposed algorithm were verified through various simulations. [ABSTRACT FROM AUTHOR]

The mixed reality conference system proposed in this paper is a robust, real-time video conference application software that makes up for the simple interaction and lack of immersion and realism of traditional video conference, which realizes the entire process of holographic video conference from client to cloud to the client. This paper mainly focuses on designing and implementing a video conference system based on AI segmentation technology and mixed reality. Several mixed reality conference system components are discussed, including data collection, data transmission, processing, and mixed reality presentation. The data layer is mainly used for data collection, integration, and video and audio codecs. The network layer uses Web-RTC to realize peer-to-peer data communication. The data processing layer is the core part of the system, mainly for human video matting and human-computer interaction, which is the key to realizing mixed reality conferences and improving the interactive experience. The presentation layer explicitly includes the login interface of the mixed reality conference system, the presentation of real-time matting of human subjects, and the presentation objects. With the mixed reality conference system, conference participants in different places can see each other in real-time in their mixed reality scene and share presentation content and 3D models based on mixed reality technology to have a more interactive and immersive experience. [ABSTRACT FROM AUTHOR]

This research paper examines the Information Visualization in Library and Information Science: Exploring Principles, Types, and Tools for Effective Data Communication. The paper provides a historical overview of information visualization, including its evolution, milestones, and key figures. It also explores different types of information visualization, including data visualization, scientific visualization, information design, visual analytics, infographics, and geospatial visualization. The paper then discusses the principles of information visualization, including visual perception, cognitive load, design principles, interaction principles, and usability principles. It also reviews different data visualization tools, such as web-based visualization tools, open-source visualization tools, and commercial visualization tools, and emerging technologies in information visualization. Additionally, the paper highlights challenges and opportunities in information visualization research, such as data quality and reliability, user-cantered design, ethical considerations, interdisciplinary collaboration, and emerging trends. Finally, the paper provides a summary of findings, implications for LIS practice, recommendations for future research, and a conclusion. [ABSTRACT FROM AUTHOR]

Review of the "Knowledge Organization and Cultural Heritage: Perspectives of the Semantic Web" conference held at the Academia Sinica Center for Digital Cultures in Taipei on June 2, 2016 and a special journal issue of academic papers related to the conference. Speakers came from mainland China and Taiwan across the Taiwan Strait, as well as the United States. Topics included methods and theories of Linked Open Data (LOD), the modeling of ontologies and knowledge bases, the historical and structural review of knowledge organization and representation, practical approaches used in exploring cultural assets, and the efforts of standards development for preservation and management of digital data. Speakers were encouraged to submit full papers to the peer-reviewed Journal of Library and Information Science (ISSN 0363-3640). These led to the publication of a whole special issue of the journal (vol. 43/no.1) in April 2017. [ABSTRACT FROM AUTHOR]

Digital ethnography can be defined as a contemporary form of ethnography which considers online social spaces of discussion following the advances in data transmission technology. In the last few years, various attempts of considering online spaces in ethnographic research have been made producing different styles of online ethnography, each identified by a different label. This paper aims to provide a systematic review of the topic to map the practice of digital ethnography. The research process followed four key steps: search, selection, analysis and synthesis. In the search phase, we searched contributions iteratively in Web of Science and Scopus by using a variety of keywords corresponding to the different labels used to refer to digital ethnography. In the selection phase, we adopted a selective stance that aims to provide a critical review of the existing research and practices in the context of digital ethnography. In the analysis phase, we carried out a content analysis of the papers combining deductive and inductive coding. The synthesis phase involves a process of typology development to pragmatically reduce and systematize an extensive set of features and digital ethnography practices. Basing on the type of data collected (Small vs Big Data) and the type of fieldwork (meta or contextual field), we detected four types of ethnographic research: social media ethnography, contextual digital ethnography, meta digital ethnography, crossmedia ethnography. [ABSTRACT FROM AUTHOR]

In the past two years, the demand for the use of mobile networks has increased, due to what the world has been exposed to in the face of the COVID-19 pan-demic and the lack of communication between people. People resorted to using of mobile networks in light of the pandemic, and their importance has appeared in several aspects, such as automotives, media and entertainment, and healthcare. This growing demand for the mobile network led to the actual development of the 4G network in terms of providing the speed of transmission and encryption data to maintain security. In this paper, a new member of the SNOW 3G family was proposed, which is one of the fourth generation algorithms called SNOW 3G-M, which has a higher encryption speed in line with the capacity of modern CPUs and is expected to be a move to the fifth generation communication system in the future. The SNOW 3G-M keystream passes all of the tests for long key stream data, short key stream data, and initialization vector data sets. [ABSTRACT FROM AUTHOR]

The number of sensor nodes in the sensor network is massive, and the network running time is relatively long, with a large number of data sampled, forming the big data of the sensor network. As the energy and communication capacities of the sensor nodes are highly limited, the design of an effective optimization algorithm for the wireless transmission of distributed cable tunnel data and the application of the mobile edge computing method to accomplish the task of big data transmission efficiently has become a major challenge faced by the wireless sensor network design. In this paper, the mobile edge computing method is used to estimate the packet reception ratio (PRR) of the wireless link, and the average number of data transmission times in the wireless link is calculated based on the reception rate. On this basis, a mobile edge computing method is proposed, which can determine the optimal path from all sensor nodes to sink nodes, so as to ensure the minimum sum of the average link transmission times in the optimal path. According to the distributed environment of the sensor network, the mobile edge computing method is improved. The distributed implementation protocol of the mobile edge computing method is proposed to identify the optimal path with the smallest average number of transmission times. The smallest number of transmission times means the minimum energy consumption. This study is of important practical significance for the wireless sensor network with limited energy. Finally, the experiment has verified that the optimization model for the wireless transmission of the distributed cable tunnel data in this paper has relatively high performance and feasibility. [ABSTRACT FROM AUTHOR]

Safety helmet wearing detection based on video surveillance is an important means of safety monitoring in many industrial scenes. The training of safety helmet wearing detection models requires large and well-labeled dataset. However, the incidence of security violations is relatively low, which results in insufficient samples for training deep detection models. Safety helmet wearing detection is a common requirement in many scenarios such as construction sites, substations, and factory workshops. Aggregating data from multiple companies for model training would improve the performance of the detection model. Traditional centralized training methods are not feasible because aggregating data in centralized locations (such as the cloud) can raise concerns about data privacy and the high cost of data communication and storage. This paper proposes FedSH, a novel cloud-edge-based federated learning framework, which learns a shared global safety helmet wearing detection model in the cloud from multiple companies at the network edges and achieves data privacy protection by keeping company data locally. In addition, this paper designs reweighting mechanisms and applies transfer learning to address class imbalance and non-IID problems in the training data, so as to obtain an accurate and personalized detection model. Extensive experiments have been conducted on real surveillance video datasets. The experimental results demonstrate that FedSH outperforms the existing widely used federated learning methods with an accuracy improvement of at least 3.4%; the reduction in accuracy is within the range of 5% compared with centralized learning methods. FedSH effectively achieves a good balance between model performance, privacy protection, and communication efficiency. [ABSTRACT FROM AUTHOR]

In recent years, the substantial growth in satellite data transmission tasks and volume, coupled with the limited availability of ground station hardware resources, has exacerbated conflicts among missions and rendered traditional scheduling algorithms inadequate. To address this challenge, this paper introduces an improved tabu genetic hybrid algorithm (ITGA) integrated with heuristic rules for the first time. Firstly, a constraint satisfaction model for satellite data transmission tasks is established, considering multiple factors such as task execution windows, satellite–ground visibility, and ground station capabilities. Leveraging heuristic rules, an initial population of high-fitness chromosomes is selected for iterative refinement. Secondly, the proposed hybrid algorithm iteratively evolves this population towards optimal solutions. Finally, the scheduling plan with the highest fitness value is selected as the best strategy. Comparative simulation experimental results demonstrate that, across four distinct scenarios, our algorithm achieves improvements in the average task success rate ranging from 1.5% to 19.8% compared to alternative methods. Moreover, it reduces the average algorithm execution time by 0.5 s to 28.46 s and enhances algorithm stability by 0.8% to 27.7%. This research contributes a novel approach to the efficient scheduling of satellite data transmission tasks. [ABSTRACT FROM AUTHOR]

The rapid development of the Industrial Internet of Things (IIoT) has brought enormous opportunities to the industrial environment, but has also posed significant challenges to network security, especially physical layer security, which is crucial for the reliable transmission of messages among interconnected devices and sensors. Focusing on enhancing the physical layer security in IIoT communication, this paper proposes a mechanism for the Spatial Secrecy Outage Probability (SSOP) to ensure the secure transmission of data. The SSOP algorithm assumes that the location of legitimate devices is known, while the eavesdropper devices have a random distribution of locations, forming the SSOP model related to the device locations from the perspective of insecure regions (ISRs) and secure regions (SRs), and the closed-form expression for its upper bound is derived. Subsequently, under the constraint of the SSOP conditions, we establish an optimization model with the objective of system throughput maximization based on the Spatial Secrecy Outage Probability (SRM-SSOP). By optimizing the transmission rate of legitimate channels or controlling the transmission power, the maximization of the system throughput can be achieved, thus reducing the consumption of communication resources. Through sophisticated modeling and simulation in MATLAB, we verified the accuracy of the definition and derived the upper bound of the SSOP. The experimental results also show that the SSOP algorithm gradually converges to a specific value as the number of antenna elements increases. In addition, we observed that, when the receiver device is aligned with the normal direction of the transmit antenna array, the SSOP reaches a minimum value. This performance is crucial for understanding and optimizing the security performance of IIoT communication systems. [ABSTRACT FROM AUTHOR]

Internet of vehicles (IoV) technology connects various types of vehicles through the Internet of Things to achieve mutual communication and data sharing, thereby promoting the development of intelligent transportation systems. Present data sharing in IoV mainly relies on complicated centralized certificate management and modern public-key cryptosystems, which are insecure and inefficient because the rapid development of quantum computing has put the security of modern public-key cryptosystems under serious threat. Considering the potential quantum adversaries, this paper proposes a quantum blockchain-based data sharing scheme called quantum blockchain for IoV (QBIoV) to realize secure and efficient data sharing in IoV. Specifically, QBIoV discards vulnerable modern cryptographic components, such as classical hash functions, public key signatures, and voting protocols, and innovatively introduces quantum replacement items, such as a quantum hash function (QHF), a quantum public key signature, and a quantum binary voting (QBV) protocol, to eliminate potential quantum cyberspace attack hazards. Furthermore, QBIoV improves the conventional proof of authority (PoA) consensus algorithm and introduces a more secure and fair consensus mechanism called quantum proof of authority (QPoA). QPoA enhances the efficiency of the blockchain system, enabling the secure and efficient sharing of data in IoV. Additionally, a security analysis of QBIoV is conducted, demonstrating that QBIoV is secure against both classic and quantum adversaries, with performance comparisons proving that QBIoV outperforms peer work regarding resource efficiency. In conclusion, this paper provides an effective solution for enhancing data security protection in IoV, assisting in designing blockchain systems in the post-quantum era. [ABSTRACT FROM AUTHOR]

Intrusion detection has become a research focus in internet information security, with deep learning algorithms playing a crucial role in its development. Typically, intrusion detection data are transformed into a two-dimensional matrix by segmenting, stacking and padding them with zeros for input into deep learning models. However, this method consumes computational resources and fails to consider the correlation between features. In this paper, we transform the data into images through visualization operations and propose an information entropy weighted scheme to optimize the collision element problem during the transformation process. This method enhances the correlation between pixel frame features, leading to approximately 2% improvement in accuracy of the classification model when using the generated image samples for detection in experiments. To address the issues of insensitivity to target feature locations and incomplete feature extraction in traditional neural networks, this paper introduces a new network model called CBAM-CapsNet, which combines the advantages of the lightweight Convolutional Block Attention Module and capsule networks. Experimental results on the UNSW-NB15 and IDS-2017 datasets demonstrate that the proposed model achieves accuracies of 92.94% and 99.72%, respectively. The F1 scores obtained are 91.83% and 99.56%, indicating a high level of detection. [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 rapid development of wireless technology has led to the availability of a wide range of networked devices that support numerous applications. Small wireless devices that are powered by batteries create a Wireless Sensor Network (WSN), which collaborates to communicate data through wireless channels to a Base Station (BS). However, a WSN system faces a number of difficulties, with energy efficiency being the most critical one. In order to provide energy efficiency and increase network lifespan, it is crucial to lessen the energy required for data transmission. This research suggests an energy-efficient optimal cluster-based routing strategy to extend the lifespan of a network. Energy conservation is of paramount importance in WSNs featuring mobile nodes. Numerous routing techniques have been proposed to reduce packet loss and boost energy efficiency in such networks. These protocols are not particularly energy-efficient though, because they cannot build the right clusters. In this paper, the tree-based Hybrid Fuzzy C-Means Genetic Algorithm (HFCM-GA) is presented in an attempt to reduce energy loss and increase the packet delivery ratio. Using node mobility and the node energy attribute, this protocol proposes a centralized cluster creation mechanism that produces optimal clusters. Node mobility, node energy, and node distance are additional criteria that a detached node considers while choosing its ideal cluster head. Simulation outcomes demonstrate that the recommended HFCM-GA is superior to the conventional routing protocols regarding the residual energy and coverage ratio. [ABSTRACT FROM AUTHOR]