Reliable Data Transfer Research Articles

Broadband Rectangular Microstrip Antenna with Slits for W-Band Applications

This work introduces a broadband rectangular patch antenna optimized for efficient data transmission in the W-band, particularly for 5G applications. By integrating two I-shaped slits with the radiating element, the antenna achieves an impressive performance, exhibiting wide bandwidth and excellent radiation characteristics. Utilizing Rogers RT5880 as the substrate material with a relative permittivity (εr) of 2.2, a small antenna with a size of 3.7 × 4.1 × 0.16 mm³ is realized. Extensive simulations are conducted using CST software in both frequency and time domains to optimize the antenna. The results show a notable 16% fractional bandwidth from 80.75 GHz to 94.79 GHz, with dual resonance frequencies at 84.5 GHz and 91.5 GHz, primarily a result of the incorporated slits. At 84.5 GHz, the antenna demonstrates an outstanding reflection coefficient of -66.37 dB, a Voltage Sanding Wave Ratio (VSWR) of 1.00096, a gain of 9.71 dBi, a directivity of 9.75 dB, and a high radiation efficiency of 91.8%. Similar trends are observed at 91.5 GHz, where the return loss remains at an impressive value of 55.92 dB and the VSWR maintains a very low value of 1.0032, indicating continued excellent impedance matching. While the gain (6.98 dBi) and directivity (7.05 dB) are slightly lower at this frequency, the radiation efficiency remains remarkably high at 94.9%, indicating efficient energy utilization. The wide bandwidth of the proposed design enables high data transfer rates, a crucial requirement for 5G networks. This translates to significant improvements in network capacity, allowing for more connected devices and data traffic. Additionally, the design exhibits excellent signal transmission characteristics, ensuring reliable data transfer. Finally, the antenna's compact size and efficient radiation have the potential to reduce power consumption in 5G devices, contributing to improved battery life and sustainability.

Generative adversarial networks based adaptive modulation and coding for next-generation 5G communication systems

In 5G based communication systems, adaptive modulation and coding (AMC) is a key approach that optimizes data transmission by constantly modifying modulation schemes and error correction coding by the current channel circumstances. AMC’s main objective is to increase data transfer efficiency and reliability while adjusting to the frequently fluctuating and unexpected nature of wireless channels. However, the channel's quality can be impacted by several variables, including distance, fading, noise, and interference in the time-varying channel. Hence it won't be easy to approximate the channel state information (CSI) accurately for time-varying channels. This paper discusses the novel rate adaptation approach that leverages generative adversarial networks (GAN) along with AMC to ensure efficient and reliable data transfer in a dynamic and often challenging environment, that maximizes data throughput even under varying conditions and offers robustness under adverse ones.

A Reliable and Secure Permissioned Blockchain‐Assisted Data Transfer Mechanism in Healthcare‐Based Cyber‐Physical Systems

ABSTRACTHealthcare systems are highly sensitive to cyberattacks as these systems possess most of the sensitive information compared to other systems relying on internet facilities. Due to the stronger security merits and efficiency of blockchain, it is integrated with the healthcare sector to ensure reliable data transfer. However, to improve the reliability and efficiency of the integrated system, a permissioned blockchain‐based security framework combining several techniques is proposed. To enable storing and validating blocks containing medical data on the blockchain, the miner is administered using the delegated proof of stake (DPoS) consensus protocol. This protocol is efficient in choosing the miner from the list of participants. Then, the blocks are created using recursive indexing with an Even–Rodeh (RI‐ER) coding hashing scheme. This algorithm is an indexing scheme that is much more efficient than the normal hashing algorithms. The validation process is carried out by the miner using the hash values provided to the users. By using the kidney disease dataset from Kaggle, the performance of the proposed method is evaluated. The performance analysis proved the effectiveness of the proposed approach compared to other schemes.

A Scalable Framework for Secure and Reliable Wireless-based Fog Cloud Communication

—Wireless telecommunication systems are essential in transferring data through fog cloud servers. However, the fog cloud servers suffer from unreliable and non-secure routing and limited power resources when mobile users are mobile. This paper introduces a scalable framework (SFRRDC) for reliable wireless routing and secure data transfer. We aim to address security and reliability issues by combining pheromone termite (PT) characteristics and ant colony optimization (ACO) algorithms for high-performance, more secure, highly reliable data transfer among the fog cloud servers. For that, the proposed SFRRDC supports a user authentication mining (UAM) algorithm to secure the confidentiality of the users. Based on testing results, it is confirmed that the proposed SFRRDC provides a better solution for confidentiality and fast routing for a wireless telecommunication system. The results show that the proposed SFRRDC framework’s energy consumption outperforms competing frameworks’ energy consumption with a better-achieved latency. For example, the suggested SFRRDC method uses 748.5 Joules during 72 hours of operation, competing frameworks use more energy, and DDFQFR uses 976.22 Joules. It also shows that the proposed SFRRDC is immune to malicious attacks. The results show that with 3,600 Fog cloud users, the proposed HEE protocol reduces the number of attacks to only 48 compared to 58, 72, and 77415 expected malicious attacks when using the ICDRP-F-SDVN, ACO, and DDFQFR frameworks, respectively.

EVM-Aware relay path decision with hierarchical modulation for reliable data transmission in cooperative relay networks

This paper presents a novel approach of integrating an error vector magnitude with hierarchical modulation in which HM dynamically adjusts modulation schemes to optimize spectral efficiency under varying channel conditions. Relay nodes are strategically selected based on Signal-to-Noise Ratio (SNR), with a focus on prioritizing high-SNR relays to ensure reliable data forwarding. To further enhance the reliability of the communication system, an EVM-aware relay path decision is proposed which selects the most suitable path based on EVM, considering the quality of the transmitted signal. By considering both SNR-based relay selection and EVM-aware path selection, the proposed system aims to minimize errors and optimize the overall performance of the network. The effectiveness of the proposed system is evaluated through extensive simulations in MATLAB, demonstrating that the proposed adaptive modulation scheme significantly outperforms fixed schemes, particularly under fluctuating channel conditions, ensuring robust and reliable communication across different SNR levels. This shows the potential of the proposed protocol to enhance performance in dynamic, making it particularly relevant for applications where reliable data transfer is critical.

An Explainable Deep Learning-Enhanced IoMT Model for Effective Monitoring and Reduction of Maternal Mortality Risks

Maternal mortality (MM) is considered one of the major worldwide concerns. Despite the advances of artificial intelligence (AI) in healthcare, the lack of transparency in AI models leads to reluctance to adopt them. Employing explainable artificial intelligence (XAI) thus helps improve the transparency and effectiveness of AI-driven healthcare solutions. Accordingly, this article proposes a complete framework integrating an Internet of Medical Things (IoMT) architecture with an XAI-based deep learning model. The IoMT system continuously monitors pregnant women’s vital signs, while the XAI model analyzes the collected data to identify risk factors and generate actionable insights. Additionally, an efficient IoMT transmission model is developed to ensure reliable data transfer with the best-required system quality of service (QoS). Further analytics are performed on the data collected from different regions in a country to address high-risk cities. The experiments demonstrate the effectiveness of the proposed framework by achieving an accuracy of 80% for patients and 92.6% for regional risk prediction and providing interpretable explanations. The XAI-generated insights empower healthcare providers to make informed decisions and implement timely interventions. Furthermore, the IoMT transmission model ensures efficient and secure data transfer.

IoT-based framework for optimizing energy efficiency and reliability in acoustic sensor networks using mobile sinks

In today’s world, there is an increasing demand for environmental monitoring, surveillance, and oceanographic research, which poses challenges in improving energy efficiency and data transfer reliability in Acoustic Sensor Networks. Existing methods face hurdles due to limited energy resources and unreliable data transmission. We propose a Reliable and Energy-Efficient Framework with Sink Mobility (REEFSM) to address these issues. This framework optimizes energy consumption and enhances data reliability by incorporating advanced energy management strategies such as adaptive duty cycling and efficient data transmission mechanisms by minimizing forwarding nodes. Simulation results demonstrate that REEFSM reduces energy consumption by up to 43% and increases data reliability by 35% compared to protocols like EERBCR and DEADS. REEFSM ensures zero dead nodes, minimizes packet drops, and maintains high data accuracy throughout the simulation. This research outcome provides a sustainable and reliable solution for energy-efficient data collection in underwater environments. The future research directions, including integrating autonomous path planning, energy harvesting, and machine learning techniques, hold great potential for further advancements in the field.

Relay Assisted Device-to-Device Communication for Future Generation Wireless Networks: A Review from Architectural and Challenges Perspective

The rapid evolution of wireless communication technologies, along with the increasing demand for efficient and reliable data transfer, has driven the rethinking of traditional cellular network architectures in the context of next-generation networks. In conventional cellular systems, communication between users typically occurs through base stations. However, to improve efficiency, scalability, and spectral utilization, device-to-device (D2D) communication has been introduced, enabling direct data transmission between users without base station involvement. In this paper, we present a comprehensive review of D2D communication from architectural and challenges perspective for future generation networks. Additionally, the study focuses on relay-assisted D2D (RAD2D) communication, examining the role of machine learning (ML) and artificial intelligence (AI) in optimizing relay selection processes. In light of the existing literature, challenges for implementing RAD2D are discussed from different perspectives such as relay selection, energy efficiency, secure communication, resource allocation, and the management of dynamic network conditions

FAIR ADCP data with OSADCP: a workflow to process ocean current data from vessel-mounted ADCPs

This paper presents the open-source Python software OSADCP developed for the processing of vessel-mounted Acoustic Doppler Current Profiler (VMADCP) data. At this stage, the toolbox is designed for processing VMADCP measurements from open-ocean applications of Teledyne RDI Ocean Surveyor ADCPs and the data acquisition software VMDAS. Based on the VMDAS ENX binary output format, the software contains implementations for cleaning and vector-averaging of single-ping velocity data, verification of the position data, and applying misalignment and amplitude corrections. The procedures of OSADCP are described in detail to encourage the scientific community to use it for their own purposes. The toolbox is an integral part of a workflow implemented on the German marine research vessels in the framework of the Underway Research Data project of the German Marine Research Alliance (DAM). It aims to ensure standardized data acquisition measures, reliable data transfer from the ADCP to shore both near-real-time and in delayed-mode, processing and quality control, and dissemination of the curated data product in the data repository PANGAEA. From PANGAEA, data sets are forwarded to the European marine data hubs Copernicus Marine Service and EMODnet. The workflow that forms the framework for OSADCP is described here as an example of scientific data management that follows the FAIR data guidelines.

DRTP: A generic Differentiated Reliable Transport Protocol

With rapid development of network communications, the performance requirements of applications are getting more differentiated. Many applications like high-definition video transfer require high throughput but do tolerate occasional packet losses. Traditional generic transport protocols however, only provide inflexible data transfer guarantees (TCP (Transmission Control Protocol) offers full reliability guarantees and UDP (User Datagram Protocol) offers no guarantees). Moreover, TCP pays a significant price to ensure a full reliability guarantee over lossy wireless communications environment like 5G millimeter wave (mmWave) communications. While existing, “partially” reliable transport protocols are either specifically designed for certain applications or need router’s support. In this paper, we design a new generic Differentiated Reliable Transport Protocol (DRTP), aiming to provide a differentiated and deterministic reliability guarantee for upper layer applications while maximizing the throughput under the constraint of guaranteeing a required reliability of data transfer. DRTP is a generic and pure end-to-end partially reliable transport protocol, and as such is easy to deploy regardless of the application in use and with no need for router’s support. The performance of DRTP is evaluated under various network conditions using extensive NS-3 (Network Simulator) simulations and practical experiments over the mmWave communications environment. The results show much higher throughput compared to typical transport protocols while guaranteeing the required transfer reliability.

Low-Cost 3D Indoor Visible Light Positioning: Algorithms and Experimental Validation

Visible light technology presents significant advancement for indoor IoT applications. These systems offer enhanced bit rate transmission, enabling faster and reliable data transfer. Moreover, optical-based visible light systems facilitate improved location services within indoor environments. However, many of these systems still exhibit limited accuracy within several centimeters, even when relying on costly high-resolution cameras. This paper introduces a novel low-cost visible light system for 3D positioning, designed to enhance indoor positioning accuracy using low-resolution images. Initially, we propose a non-integer pixel (NI-P) algorithm to enhance precision without the need for higher-resolution images. This algorithm allows the system to identify the precise light spot coordinates on the low-resolution images, enabling accurate positioning. Subsequently, we present an algorithm leveraging the precise coordinate data from the previous step to determine the 3D position of objects even in front of errors in the measures. Benefiting from high accuracy, reduced cost, and low complexity, the proposed system is suitable for implementation on low-end hardware platforms, thereby increasing the versatility and feasibility of visible light technologies in indoor settings. Experimental results show an average 2D positioning error of 1.08 cm and 3D error within 1.4 cm at 2.3 m separation between the object and camera, achieved with an average positioning time of 20 ms on a low-end embedded device. Consequently, the proposed system offers fast and highly accurate indoor positioning and tracking capabilities, making it suitable for applications like mobile robots, automated guided vehicles, and indoor parking management. Furthermore, it is easy to deploy and does not require re-calibration.

Research collaboration data platform ensuring general data protection

Translational data is of paramount importance for medical research and clinical innovation. It has the potential to benefit individuals and organizations, however, the protection of personal data must be guaranteed. Collecting diverse omics data and electronic health records (EHR), re-using the minimized data, as well as providing a reliable data transfer between different institutions are mandatory steps for the development of the promising field of big data and artificial intelligence in medical research. This is made possible within the proposed data platform in this research project. The established data platform enables the collaboration between public and commercial organizations by data transfer from various clinical systems into a cloud for supporting multi-site research while ensuring compliant data governance.

A Review on Design and Verification of Programmable UART with AXI

A Review on Design and Verification of Programmable UART with AXI

BlockSD‐5GNet: Enhancing security of 5G network through blockchain‐SDN with ML‐based bandwidth prediction

AbstractThe fifth generation (5G) of mobile communications is the most exciting emerging technology for researchers and scientists to get the full benefit of a network system. However, 5G networks confront massive threats and vulnerabilities including protection, privacy, and secrecy. To face these challenges in the increasingly interconnected Internet of Things (IoT) scenario, we aim to leverage state‐of‐the‐art technologies as software defined networking (SDN) in conjunction with network function virtualization (NFV), blockchain, and machine learning (ML). Indeed, these technologies convey a robust and secure setting in the networking platform enabling to manage several criticalities related to security, privacy, flexibility, and performance. In light of these considerations, in this article, we propose the “BlockSD‐5GNet” architecture to efficiently improve the security of a 5G network and to exploit the combined advantages of Blockchain, SDN, NFV, and ML. In the proposed architecture, the SDN helps to manage the network by dividing it into data plane and control plane, while the Blockchain guarantees improved security and confidentiality. Therefore, the “BlockSD‐5GNet” architecture can both secure sensitive data and attain reliable data transfer within and between the 5G network‐infrastructure planes. Additionally, an ML module is integrated into the SDN controller to estimate network bandwidth and assist the administrator in taking effective decisions and satisfying high‐bandwidth demand. We assess the performance of the “BlockSD‐5GNet” architecture via an experimental evaluation performed in a simulation environment, and show the effectiveness of the proposed solution in comparison with baseline schemes. Finally, we also demonstrate the capability of different ML models in bandwidth prediction.

Enhancing Secure and Reliable Data Transfer through Robust Integrity

Cloud computing has emerged as a highly efficient platform that allows multiple users to access various services through virtualization on a shared physical network. The participants in a Cloud Computing (CC) environment include Cloud Service Providers (CSP), Consumers, Brokers, and Auditors. The advantages of cloud storage, such as universal network access, convenience, and scalability, have led to data owners preferring to store their data on remote servers. However, the transfer of outsourced data has become a critical requirement for cloud users due to the availability of different cloud storage services with varying quality of services.
 One major challenge in this context is ensuring the security of secret keys and data integrity. There is no guarantee of data integrity when storing data on an untrusted cloud server. To address this issue, this paper proposes a secure and efficient data integrity verification scheme for cloud storage services. The scheme utilizes a key-homomorphic cryptographic primitive to reduce system complexity and eliminate the need for a public key authentication framework based on a public key infrastructure (PKI) in the data integrity checking protocol. By employing this approach, the proposed method ensures the integrity of remote data stored on cloud servers. Through security analysis and empirical evaluation, it is demonstrated that our scheme is both practical and effective for securely sharing records with multiple owners in cloud computing.

Securing the Transmission While Enhancing the Reliability of Communication Using Network Coding in Block-Wise Transfer of CoAP

The practical employment of network coding (NC) has shown major improvements when it comes to the transmission reliability of sender data and bandwidth utilization. Moreover, network coding has been employed recently to secure the transmission of data and prevent unauthorized recovery of sender packets. In this paper, we employ network coding (NC) in a practical way in networks with constrained resources with the goal of improving the reliability and security of data transfer. More specifically, we apply NC on the recent options of block-wise transfer (BWT) of the constrained application protocol (CoAP). The goal is to enhance the reliability of CoAP when used to transfer larger data blocks using BWT. Also, we employ an innovative homomorphic encryption approach to secure the BWT of CoAP.

Подворные переписи Екатеринбурга 1728 и 1788 гг. как источник по истории населения города

The article presents the results of the research aimed at studying the source potential of the sub-ward censuses of early Yekaterinburg, created in 1728 and 1788. These documents were found by the authors in fond 271 “Berg-Collegium” of the Russian State Archive of Ancient Acts (RGADA) and fond 8 “Yekaterinburg City Duma of Perm Province / Yekaterinburg, Perm Province (January 12, 1787 - May 1919)” of the State Archive of the Sverdlovsk Region (GASO). State Archive of the Sverdlovsk Region (GASO). Despite the long tradition of studying documentary materials containing information about the population of the Russian Empire, not all of them are currently involved in the scientific turnover. In historical and demographic studies, priority attention is paid to censuses and revision tales - documents that had fiscal significance. At the same time, the so-called police or administrative censuses, as a rule, are out of the scientists' field of vision. However, they may contain more accurate data on the inhabitants of a particular settlement, as they include information on the actual, rather than legal, population of the territory. The authors analyzed the purposes of creation and information capabilities of two administrative censuses of Yekaterinburg at different stages of the fortress factory's existence: in the first years of its creation and at the stage of official consolidation of its status as a city. The formulary analysis of the documents allowed us to establish their peculiarities, similarities and differences. The census of 1728 can be called the first document, which recorded data on the class and professional affiliation of the yard owners of the emerging city, the structure of the settlement, the ratio of the number of men and women living in it. The materials of the 1788 census are in the form of a draft. Nevertheless, they help to get an idea of the changes in the employment structure of the population of the city, which became a district center in 1781, the number of men and women. Both censuses allow us to learn not only about the population of Ekaterinburg, but also about the number of households, as well as the composition of the inhabitants living in each household. In addition, the documents provide information on the number of farmsteads in public and private ownership. The authors came to the conclusion that the household censuses of Yekaterinburg are important sources on the history of the city, which are characterized by the comprehensiveness and reliability of data transfer. The information obtained from the census documents makes it possible to reconstruct the socio-demographic history of the city: changes in the population size, sex and age composition, property status of residents, employment structure.

A novel multipath QUIC protocol with minimized flow complete time for internet content distribution

The rapid growth of network services and applications has led to an exponential increase in data flows on the internet. Given the dynamic nature of data traffic in the realm of internet content distribution, traditional TCP/IP network systems often struggle to guarantee reliable network resource utilization and management. The recent advancement of the Quick UDP Internet Connect (QUIC) protocol equips media transfer applications with essential features, including structured flowcontrolled streams, quick connection establishment, and seamless network path migration. These features are vital for ensuring the efficiency and reliability of network performance and resource utilization, especially when network hosts transmit data flows over end-to-end paths between two endpoints. QUIC greatly improves media transfer performance by reducing both connection setup time and transmission latency. However, it is still constrained by the limitations of single-path bandwidth capacity and its variability. To address this inherent limitation, recent research has delved into the concept of multipath QUIC, which utilizes multiple network paths to transmit data flows concurrently. The benefits of multipath QUIC are twofold: it boosts the overall bandwidth capacity and mitigates flow congestion issues that might plague individual paths. However, many previous studies have depended on basic scheduling policies, like round-robin or shortest-time-first, to distribute data transmission across multiple paths. These policies often overlook the subtle characteristics of network paths, leading to increased link congestion and transmission costs. In this paper, we introduce a novel multipath QUIC strategy aimed at minimizing flow completion time while taking into account both path delay and packet loss rate. Experimental results demonstrate the superiority of our proposed method compared to standard QUIC, Lowest-RTT-First (LRF) QUIC, and Pluginized QUIC schemes. The relative performance underscores the efficacy of our design in achieving efficient and reliable data transfer in real-world scenarios using the Mininet simulator.

FlexCP: A Scalable Multipath TCP Proxy for Cellular Networks

Research has shown that Multipath TCP (MPTCP) improves the quality of a TCP connection by exploiting multiple paths, but its adoption in the wide area network is still fledgling. While MPTCP-TCP proxying is often employed as a practical solution, the performance of a split-connection proxy is suboptimal – it wastes CPU cycles on content relaying between two connections while it does not efficiently leverage multiple CPU cores in packet processing. We present FlexCP, a high-performance MPTCP-TCP proxy based on the following properties. First, FlexCP operates by translating the two protocols on a packet level. This approach not only avoids the overhead of flow reassembly and memory copying, but it greatly simplifies the implementation as the proxy stays away from reliable data transfer, socket buffer management, and per-hop congestion/flow control. Second, FlexCP maintains connection-to-core affinity for multiple subflows of the same MPTCP connection and its corresponding TCP connection by leveraging SmartNIC. This enables a lock-free implementation for packet processing, which significantly improves the performance. Our evaluation demonstrates that FlexCP achieves 281 Gbps of connection proxying on a single machine, outperforming existing proxies by up to 6.3× in terms of throughput while it incurs little extra latency over direct TCP/MPTCP connections.

Official Control in Slaughter and Game Handling: Expectations and Prerequisites for Implementation of Remote Meat Inspection in Sweden

Remote meat inspection is currently not permitted under the European Union food control legislation. However, the environmental impact of travelling to and from abattoirs and increasing shortages of qualified veterinary staff make remote controls a potential future scenario. This paper reports the results of a qualitative study conducted with a sample of nineteen official veterinarians and food business operators in Sweden. We investigated attitudes, perceived risks, and prerequisites for remote meat controls in semi-structured interviews.Results indicate both positive attitudes towards remote meat inspection, and concerns related to technical challenges, reliability and security of data transfer, and possibilities of manipulation of the remote system. Respondents also noted both negative effects, such as physical hurdles for good control, and positive impacts on animal welfare, such as shortened waiting times for slaughter. Considering the current regulatory framework, only 21% of the respondents have had any prior experience with (pilot) remote meat inspections and the additional 11% carried out remote inspections of Food Chain Information documents. Nevertheless, all participants, including the majority without any prior experience in remote inspections, assumed that remote inspections would be done via video streaming. The optimal setting for a remote meat inspection, according to our respondents, seems to be a combination of cameras at fixed locations with body cameras worn by assisting abattoir personnel. Overall, remote meat inspections are possible to introduce but not without significant legal and technical adaptations as well as definition of the conditions for this type of control flexibility.