Robust Data Transmission Research Articles

Thermally tunable add-drop filter based on valley photonic crystals for optical communications

Abstract Valley photonic crystals (VPCs) provide an intriguing approach to suppress backscattering losses and enable robust transport of light against sharp bends, which could be utilized to realize low-loss and small-footprint devices for on-chip optical communications. However, there are few studies on how to achieve power-efficient tunable devices based on VPCs, which are essential for implementing basic functions such as optical switching and routing. Here, we propose and experimentally demonstrate a thermally tunable add-drop filter (ADF) based on VPCs operating at telecommunication wavelengths. By leveraging the topological protection of the edge state and the distinct property of negligible scattering at sharp bends, a small footprint of 17.4 × 28.2 μm2 and a low insertion loss of 2.7 dB can be achieved for the proposed device. A diamond-shaped microloop resonator is designed to confine the light and enhance its interaction with the thermal field generated by the microheater, leading to a relatively low power of 23.97 mW needed for switching the output signal from one port to the other. Based on the thermally tunable ADF under the protection of band topology, robust data transmission is implemented with an ultrahigh data rate of 132 Gb/s. Our work shows great potential for developing high-performance topological photonic devices with the thermally tunable silicon-based VPCs, which offers unprecedented opportunities for realizing topologically protected and reconfigurable high-speed datalinks on a chip.

Worker Presence Monitoring in Complex Workplaces Using BLE Beacon-Assisted Multi-Hop IoT Networks Powered by ESP-NOW

The increasing adoption of Internet of Things (IoT) technologies has facilitated the creation of advanced applications in various industries, notably in complex workplaces where safety and efficiency are paramount. This paper addresses the challenge of monitoring worker presence in vast workplaces such as shipyards, large factories, warehouses, and other construction sites due to a lack of traditional network infrastructure. In this context, we developed a novel system integrating Bluetooth Low Energy (BLE) beacons with multi-hop IoT networks by using the ESP-NOW communications protocol, first introduced by Espressif Systems in 2017 as part of its ESP8266 and ESP32 platforms. ESP-NOW is designed for peer-to-peer communication between devices without the need for a WiFi router, making it ideal for environments where traditional network infrastructure is limited or nonexistent. By leveraging the BLE beacons, the system provides real-time presence data of workers to enhance safety protocols. ESP-NOW, a low-power communications protocol, enables efficient, low-latency communication across extended ranges, making it suitable for complex environments. Utilizing ESP-NOW, the multi-hop IoT network architecture ensures extensive coverage by deploying multiple relay nodes to transmit data across large areas without Internet connectivity, effectively overcoming the spatial challenges of complex workplaces. In addition, the Message Queuing Telemetry Transport (MQTT) protocol is used for robust and efficient data transmission, connecting edge devices to a central Node-RED server for real-time remote monitoring. Moreover, experimental results demonstrate the system’s ability to maintain robust communication with minimal latency and zero packet loss, enhancing worker safety and operational efficiency in large, complex environments. Furthermore, the developed system enhances worker safety by enabling immediate identification during emergencies and by proactively identifying hazardous situations to prevent accidents.

Robust and secure data transmission using artificial intelligence techniques in Ad-Hoc networks

Robust and secure data transmission using artificial intelligence techniques in Ad-Hoc networks

Enhancing wireless sensor network connectivity and coverage using Hybrid GWO‐HSA algorithm

SummaryWireless sensor networks (WSNs) are essential in environmental monitoring, healthcare, and industrial automation. Persistent connectivity and coverage challenges in WSN stem from intermittent node connectivity due to obstacles, signal interference, node failures, and compromised data reliability. Existing solutions, while useful, exhibit limitations in fully addressing these concerns. To confront these challenges, a proposed system introduces the Hybrid Grey Optimizer–Harmony Search Algorithm (Hybrid GWO‐HSA), merging adaptive routing protocols and efficient deployment techniques. The Hybrid GWO‐HSA system conducts an initial environmental analysis to pinpoint factors affecting node communication. It strategically deploys additional nodes to bridge coverage gaps, using the Grey Wolf Algorithm's capabilities to optimize node placement. Moreover, it employs the Harmony Search Algorithm to dynamically adjust communication paths based on real‐time network conditions, ensuring robust data transmission. The system workflow involves an environmental assessment followed by node deployment guided by the Grey Wolf Algorithm. Subsequently, the Harmony Search adapts communication paths to enhance connectivity. Simulations and practical experiments across diverse environments validate the Hybrid GWO‐HSA system's effectiveness. Results showcase substantial improvements: network lifetime of 13,200 s, a network delay of 37 ms, a coverage rate of 0.88, and an energy consumption of 590 J. This Hybrid GWO‐HSA‐based system establishes a resilient and efficient WSN infrastructure vital for reliable data collection and transmission in challenging settings. The Hybrid GWO‐HSA system offers a comprehensive approach to WSN connectivity and coverage issues by leveraging firefly and genetic algorithms, and it significantly enhances WSN performance and reliability across multifaceted application domains.

Artificial self-attention rabbits battle royale multiscale network based robust and secure data transmission in mobile Ad Hoc networks

In a Mobile Ad hoc Network (MANET), the network structure constantly evolves due to the movement of devices, users, or nodes. The Black Hole Attack (BHA) is recognized as the most impactful threat in MANETs, where an attacker node intentionally discards all data traffic, hence minimizing the network performance. Therefore, developing a secure and robust routing protocol is vital for efficient data transmission in a MANET. Although existing solutions have been designed to counteract malicious nodes, these solution presents drawbacks such as the need for additional hardware, notable delivery delays, limited throughput, increased energy consumption, and minimum packet delivery ratio. Thus, this research work introduces a new updated Ad hoc On-demand Distance Vector (AODV) routing protocol that integrates the benefits of the Artificial Rabbits Battle Royale Optimization (ARBRO), and Self-attention Multiscale Network (SMNet). The role of the ARBRO algorithm is to optimize the route by selecting the most appropriate node properties. Then, SMNet identifies the BHA node using these node properties. The proposed scheme is implemented in MATLAB. Experimental results determines that the introduced approach attains a delay of 0.039 s, a throughput of 94.57 Kbps, and a packet delivery ratio of 98.76 %, which are better than the existing techniques. Simulation results demonstrate that the introduced method improves network performance by enhancing the quality of service in the presence of a BHA.

EWFAIGF: Design of an Efficient Model for Enhancing Energy Efficiency in IoT-Based Wireless Sensor Networks through Fuzzy AHP and Iterative Grey Wolf Jelly Fish Optimization

In the realm of Wireless Sensor Networks (WSNs), the quest for enhanced energy efficiency remains paramount, given their pivotal role in facilitating the Internet of Things (IoT) applications. Existing methodologies often grapple with the dual challenge of optimizing energy consumption while ensuring robust data transmission, thereby limiting their efficacy in dynamic, resource-constrained environments. This work introduces a novel paradigm that meticulously addresses these constraints, thereby heralding a significant leap towards optimizing WSNs' operational efficiency. At the core of our proposed model lies the integration of Fuzzy Analytic Hierarchy Process (Fuzzy AHP)-based clustering, which ingeniously segregates nodes by leveraging multi-criteria such as location, energy efficiency, and temporal performance. This clustering serves as a precursor to the application of an innovative Iterative Grey Wolf Jelly Fish Optimizer (GWJFO). The GWJFO stands out by its strategic prowess in delineating optimal routing paths, thus minimizing energy expenditure and enhancing data relay efficiency. Furthermore, our model is fortified with a Q Learning Method, ingeniously designed to identify and execute optimal alternate routing paths through a Make Before Break strategy. This addition not only mitigates potential faults but also significantly boosts computational efficiency and packet delivery performance. Empirical validation through real-time network simulations underscored the model's superiority, demonstrating a 9.5% improvement in communication speed, an 8.5% increase in energy efficiency, a 4.5% improvement in packet delivery performance under fault conditions, a 10.4% rise in throughput, and a 5.9% enhancement in network consistency over existing benchmarks. This groundbreaking work not only paves the way for more energy-efficient WSNs but also sets a new standard in achieving high-performance metrics essential for the next generation of IoT applications. The implications of these advancements extend beyond mere technical enhancements, offering a beacon for future research in the domain, potentially revolutionizing the way we deploy and manage sensor networks in an array of applications.

Analysis of Cooperative Operating Concepts for Robust Data Transmission in Periodically Disturbed CAN FD Networks

Analysis of Cooperative Operating Concepts for Robust Data Transmission in Periodically Disturbed CAN FD Networks

Physical layer security analysis for RIS-aided NOMA systems with non-colluding eavesdroppers

Within the realm of sixth-generation (6G) wireless systems, there exist two primary imperatives: establishing massive connections and ensuring robust data transmission security. Therefore, this paper delves into the realm of physical layer security (PLS) within the context of a reconfigurable intelligent surface (RIS)-assisted Non-Orthogonal Multiple Access (NOMA) network coupled with the Internet of Things (IoTs), while addressing the challenge of non-concluding eavesdroppers. Specifically, the utilization of NOMA technology is anticipated to yield a substantial enhancement in spectrum efficiency for 6G and forthcoming wireless networks. Furthermore, this study investigates the security aspects through metrics such as the secrecy outage probability (SOP) and the average secrecy capacity (ASC), with the derivation of closed-form approximations for these metrics. Based on these mathematical expressions, we unveil the asymptotic Secrecy Outage Probability (SOP) to extract comprehensive insights into the RIS-assisted NOMA system’s behavior. Furthermore, we employ an algorithm based on the Golden Section to showcase the optimal SOP for a more in-depth analysis. Our findings highlight that the number of RIS metasurface components and the average signal-to-noise ratio at the access point are the primary factors driving improvements in system performance. Finally, we confirmed the correctness of our derived expressions by conducting a comparative analysis between Monte-Carlo simulations and analytical results.

Efficient VLSI Implementation of Hybrid LDPC-STBC Codes for Enhanced Satellite Communication Systems

Satellite communication systems play a pivotal role in facilitating global connectivity, necessitating the development of robust error correction codes to ensure reliable data transmission. In contemporary communication systems, the demand for higher data rates and improved spectral efficiency has led to the integration of advanced error correction techniques. However, existing systems often face challenges in striking a balance between complexity, power consumption, and performance. This work addresses the limitations of current systems by proposing a hybrid approach that combines the advantages of LDPC (Low-Density Parity-Check) codes and STBC (Space-Time Block Coding) techniques. The hybrid LDPC-STBC codes aim to enhance the error correction capabilities of satellite communication systems, ensuring robust data transmission in the presence of channel impairments. Despite the advancements in error correction coding, current systems encounter drawbacks such as increased computational complexity, higher power consumption, and potential performance degradation under adverse channel conditions. The proposed hybrid LDPC-STBC codes mitigate these issues by leveraging the strengths of both coding schemes, achieving a synergistic balance between error correction performance and computational efficiency.

Recent Survey on Internet of Vehicles: Architecture, Applications, Challenges, and Its Solutions

Abstract The fame of the Internet of vehicles (IOV) increases the complexity of managing the vast network of interconnected vehicles, devices, and systems, which causes the need for seamless connectivity among vehicles and infrastructure. Developing robust and efficient data transmission technologies is imperative to ensure that IOV functions smoothly and can not only handle the substantial volume of data generated by IOV but also address factors of latency, bandwidth, and scalability to meet the evolving demands of modern transportation systems. Therefore, experts are actively exploring novel solutions and advancements to tackle these challenges to promote IOV to new heights in transportation. In this survey paper, the authors surveyed the IOV of different architectures, provided a comprehensive overview of the Internet of things, vehicular ad hoc networks, and IOV networks, and compared the various networks. Similarly, they studied the multiple challenges of IOV and the corresponding solution available in recent literature. This paper describes the IOV evolution and examines several research papers related to the IOV and research guidance, such as high mobility, load balancing, security, heterogeneity, location accuracy, secure routing, etc.

Towards secure IoT system from a smart city perspective: An optimized algorithm and implementation

AbstractSecuring Internet of Things (IoT) systems is crucial for maintaining the resilience and trustworthiness of smart cities. In this context, the routing protocol's efficiency is pivotal for large‐scale IoT applications. However, achieving dependable and energy‐efficient routing in wireless sensor networks (WSNs) poses significant challenges due to limited and non‐rechargeable node energy resources. Also, traditional approaches often fell short of ensuring robust security and efficient data transmission. Hence, the purpose of this research was to address these shortcomings by introducing the Blowfish Honey‐Improved Spotted Hyena Optimization (BONY‐ISHO) protocol aimed at bolstering the security and efficiency of clustering and data routing in WSNs. Firstly, it introduces blockchain technology to establish secure and authenticated clustering, ensuring that only legitimate cluster heads and member nodes can participate. This innovation significantly enhances network security. Secondly, our protocol incorporates a hybrid Blowfish‐Honey cryptographic technique for data protection within the Area of Interest (AOI). This dual‐layer security approach, comprising Blowfish encryption and Honey encryption for key management, guarantees robust privacy and security. Thirdly, we have optimized data routing through the Improved Spotted Hyena Optimization (ISHO) algorithm, extending the network's lifetime and conserving energy resources. Performance evaluations confirm the superiority of the BONY‐ISHO protocol and existing solutions. It achieves a higher packet delivery ratio (99.8%), increased throughput (45 000 kbps), reduced energy consumption (1.68 joules), and minimized latency (0.068 sec) when compared to traditional methods. These performance enhancements make the BONY‐ISHO protocol a compelling choice for securing and optimizing IoT‐based WSNs. Our study concludes that the BONY‐ISHO protocol is a highly effective solution for addressing security and efficiency challenges in IoT‐based WSNs. By combining blockchain‐based authentication, hybrid cryptography, and intelligent routing algorithms, we have achieved a comprehensive enhancement of network security and data transmission efficiency. The protocol's ability to thwart malicious nodes and optimize routing pathways ensures the integrity and reliability of IoT‐based WSNs.

Enhancing Packet Reliability in Wireless Multimedia Sensor Networks using a Proposed Distributed Dynamic Cooperative Protocol (DDCP) Routing Algorithm

Wireless Multimedia Sensor Networks (WMSNs) are being extensively utilized in critical applications such as environmental monitoring, surveillance, and healthcare, where the reliable transmission of packets is indispensable for seamless network operation. To address this requirement, this work presents a pioneering Distributed Dynamic Cooperation Protocol (DDCP) routing algorithm. The DDCP algorithm aims to enhance packet reliability in WMSNs by prioritizing reliable packet delivery, improving packet delivery rates, minimizing end-to-end delay, and optimizing energy consumption. To evaluate its performance, the proposed algorithm is compared against traditional routing protocols like Ad hoc On-Demand Distance Vector (AODV) and Dynamic Source Routing (DSR), as well as proactive routing protocols such as Optimized Link State Routing (OLSR). By dynamically adjusting the transmission range and selecting optimal paths through cooperative interactions with neighboring nodes, the DDCP algorithm offers effective solutions. Extensive simulations and experiments conducted on a wireless multimedia sensor node testbed demonstrate the superior performance of the DDCP routing algorithm compared to AODV, DSR, and OLSR, in terms of packet delivery rate, end-to-end delay, and energy efficiency. The comprehensive evaluation of the DDCP algorithm against multiple routing protocols provides valuable insights into its effectiveness and efficiency in improving packet reliability within WMSNs. Furthermore, the scalability and applicability of the proposed DDCP algorithm for large-scale wireless multimedia sensor networks are confirmed. In summary, the DDCP algorithm exhibits significant potential to enhance the performance of WMSNs, making it a suitable choice for a wide range of applications that demand robust and reliable data transmission.

SDN-IoT: SDN-based efficient clustering scheme for IoT using improved Sailfish optimization algorithm.

The Internet of Things (IoT) includes billions of different devices and various applications that generate a huge amount of data. Due to inherent resource limitations, reliable and robust data transmission for a huge number of heterogenous devices is one of the most critical issues for IoT. Therefore, cluster-based data transmission is appropriate for IoT applications as it promotes network lifetime and scalability. On the other hand, Software Defined Network (SDN) architecture improves flexibility and makes the IoT respond appropriately to the heterogeneity. This article proposes an SDN-based efficient clustering scheme for IoT using the Improved Sailfish optimization (ISFO) algorithm. In the proposed model, clustering of IoT devices is performed using the ISFO model and the model is installed on the SDN controller to manage the Cluster Head (CH) nodes of IoT devices. The performance evaluation of the proposed model was performed based on two scenarios with 150 and 300 nodes. The results show that for 150 nodes ISFO model in comparison with LEACH, LEACH-E reduced energy consumption by about 21.42% and 17.28%. For 300 ISFO nodes compared to LEACH, LEACH-E reduced energy consumption by about 37.84% and 27.23%.

A multi-sensory real-time data transmission method with sustainable and robust 5G energy signals for smart cities

New generation technologies like Fifth Generation (5G) access technology have great potential to provide a sustainable Quality of Service (QoS) for Electric Vehicles (EVs) in smart cities. The environmental features of urban cities mean that signal transmission can be affected across communication networks, with packet delays, packet loss and higher error rates occurring during data exchange. There is a need for sustainable and robust low-energy signals for smart EV communication. The present paper proposes a novel method for continuous, robust video data transmission at low energy via multi-sensory-enabled 5G technology. The transceivers (transmitters and receivers) are designed with multiple low-energy sensors for detecting data availability at the receiver device. By applying a threshold level detection technique, data availability is identified dependent upon energy level and successive data exchange occurs between transceivers. The application of low-energy signal transmission reduces power usage during video data transmission and leads to a sustainable solution for intelligent EV applications. The performance of the proposed multi-sensory technique is tested and verified using various calibrated parameters considering key metrics including collision error, propagation error, sensing error and accuracy. The proposed model significantly improves accuracy, with higher sensing capabilities and lower delays and propagation errors compared to the existing buffer model.

Feasibility Analysis of Data Transmission in Partially Damaged IoT Networks of Vehicles

Nowadays, vehicle-oriented Internet of Things (IoT) is a new generation of IoT networks in which sensors are deployed on electronic hardware modules of vehicles. A secure and feasible IoT-assisted vehicle environment should include a robust data transmission mechanism for transferring and collecting data packets from both onboard and roadside sensors, resulting in the accurate delivery of packages without delay. When designing such Internet of Vehicles (IoV) networks, the vulnerability of the network should be considered to facilitate data transmission in the remaining network under the condition that some nodes (e.g., vehicles) and channels are damaged due to the dynamic environmental factors and unpredicted failures at various nodes. Fractional Critical Deleted Graph (FCDG), which is used in graph theory, can act as Fractional Factor (FF) in the IoV networks to maintain the IoT network stable and provide reliable network connectivity when a part of data transmission network is damaged. Toughness is an important condition to measure the sturdiness of such FF-encoded network. In this work, we study the relationship between toughness and FCDG in IoV networks. Moreover, the graph conditions are considered together with the tight lower bound of the toughness for the existence of path factor. Such feasibility analysis of IoV networks help to find the bound in the effort to recover or realign lost links in networks, which is critical for the next generation of intelligent transportation systems where all vehicles are connected seamlessly.

Digital Non-Linear Transmitter Equalization for PAM-N-Based VCSEL Links Enabling Robust Data Transmission of 100 Gbit/s and Beyond

This paper demonstrates why VCSEL-based transmitter systems are not able to capitalize on higher-order PAM modulation formats (such as PAM-4) to push the link data rate towards 100 Gbit/s with BER of better than 10−5. First, the non-linear and biasing-dependent VCSEL behavior is analyzed in great detail to prove why state-of-the-art VCSELs with linear equalization are not able to reach these bandwidth targets. Consequently, based on an enhanced VCSEL model, a digital non-linear transmit equalizer is proposed to overcome voltage-dependent relaxation frequency shifts as well as data-dependent VCSEL bandwidth variations. The proposed digital non-linear equalizer is compared with a standard linear FFE structure using PAM-4 transmission experiments of 100 Gbit/s and beyond. This way, the proposed non-linear equalizer reveals a BER improvement of more than 30-fold compared to a linear FFE at a data rate of 80 Gbit/s. Finally, at 112 Gbit/s PAM-4 the non-linear equalizer was successfully demonstrated at a BER of 1.5·10−7.

Characterizing the wireless data transmission of biosignals within a health-care environment

Advancements in implantable medical devices have created the need for more robust continuous data transmission abilities. Implantable medical device wireless data transmission within a health-care setting is beneficial, as it has the potential to increase safety, broaden independence, and increase mobility for patients. Minimizing the need for an individual to be tethered to electrical equipment restores movement, improves the quality of life for him or her, and may reduce the safety risk profile.

Performance Evaluation of Integrated Antennas on Photovoltaic Solar Cells

The performance of antennas is critical to ensuring reliable wireless communication and robust data transmission. Unfortunately, antennas’ performance gets degraded when loaded with lossy materials. This paper presents the numerical and experimental evaluation of low-profile antennas’ performance when integrated with photovoltaic (PV) solar cells for potential use in smart grid and green power networks. Such integrated antennas can serve as a communication unit and sensors to monitor PV solar cells. For convenience, a microstrip patch antenna was used in this assessment study, where the antenna was designed, numerically simulated, and experimentally tested. After which, it was installed on top of a PV solar cell at different orientations. The antenna is designed to operate within the 2.45 GHz ISM band. Based on the results, the antenna performed well when placed at the middle of the PV solar cell with a peak gain of 2.58 dBi compared to other placements within the PV solar cell. Moreover, creating a small air gap between the antenna and the PV solar cell results in better performance. Based on the findings of this study, the antenna has satisfactory performance when integrated with PV cells, which is promising to deploy in many applications, including smart grid networks.

A Measurement-Aided Control System for Stabilization of the Real-Life Stewart Platform.

In the paper, an innovative control system devoted to the stabilization of the parallel manipulator-type Hexapod is presented. The device consists of three main parts, allowing us to reach the desired location during various external disturbances. Indeed, the telescopic boom located on the car along with the system providing the correction of the boom column deflection as well as the gyroscopic self-leveling head constitute a complex tool covering a plethora of modern techniques and solutions. Through the application of advanced issues strictly derived from nonlinear identification and multivariable control theory branches, the dynamical behavior of the discussed device has been handled in order to achieve a proper reference operation. Naturally, it has been supported by a set of accompanying approaches related to the processes of the real-time measurement and robust data transmission. It should be emphasized that the proposed computer-aided system is intended for the film industry, where image stabilization plays a crucial role. Such a statement has additionally been confirmed by other innovative products introduced by a company placed in Opole, Poland, called MovieBird International.

Adaptive VR Video Data Transmission Method Using Mobile Edge Computing Based on AIoT Cloud VR

Aiming at the high requirements of cloud service-based virtual reality in AIoT for data transmission rate and delay sensitivity, a cloud VR system scheme based on MEC (Mobile Edge Computing) is proposed, which mainly incorporates viewpoint-based VR video data processing and hybrid digital-to-analog (HDA) transmission optimization and can be served for AIoT transmission filed. Firstly, a learning-driven multiaccess MEC offloading strategy is designed, in which the VR terminal automatically selects the optimal MEC server for task offloading, thereby effectively improving network efficiency and reducing service delay. Secondly, the progressive transmission of the VR data is realized through viewpoint-aware dynamic streaming based on RoI (region of interest) and the priorities of different objects. The transmission priority of each object in the scene is determined through the ROI layering, which effectively solves the contradiction between the large data volume in the VR scenes and the network bandwidth limitation when applied in AIoT domain, and further improves the real-time performance of the system. Then, the HDA (hybrid digital-analog) technique is introduced to optimize the transmission. Finally, the base station protocol stack is modified on the basis of the LTE (Long-Term Evolution) system, and the MEC technology is integrated to realize a complete cloud VR system in AIoT. The experimental results show that compared with other advanced schemes, the proposed scheme can achieve more robust and efficient data transmission performance and provide better VR user experience.