Reliable Data Transfer Research Articles

Turbo encoder and decoder chip design and FPGA device analysis for communication system

<p>Turbo codes are error-correcting codes with performance that is close to the Shannon theoretical limit (SHA). The motivation for using turbo codes is that the codes are an appealing mix of a random appearance on the channel and a physically realizable decoding structure. The communication systems have the problem of latency, fast switching, and reliable data transfer. The objective of the research paper is to design and turbo encoder and decoder hardware chip and analyze its performance. Two convolutional codes are concatenated concurrently and detached by an interleaver or permuter in the turbo encoder. The expected data from the channel is interpreted iteratively using the two related decoders. The soft (probabilistic) data about an individual bit of the decoded structure is passed in each cycle from one elementary decoder to the next, and this information is updated regularly. The performance of the chip is also verified using the maximum a posteriori (MAP) method in the decoder chip. The performance of field-programmable gate array (FPGA) hardware is evaluated using hardware and timing parameters extracted from Xilinx ISE 14.7. The parallel concatenation offers a better global rate for the same component code performance, and reduced delay, low hardware complexity, and higher frequency support.</p>

Link quality and energy efficient optimal simplified cluster based routing scheme to enhance lifetime for wireless body area networks

Monitoring of patient’s health in the medical industry can be enabled using wireless body area networks (WBANs), which are already used for various purposes, including assisting in human safety. It is imperative to use better power management strategies since the body sensors are small and the battery cannot hold a charge for a long time. Due to the vast amounts of information generated by medical sensors, resource-constrained networks face a significant challenge when guaranteeing the specified quality of service (QoS). Moreover, the WBAN regularly meets the primary hassle of QoS degradation because of congestion WBAN structure can easily compromise heterogeneous and complex networks. Either inappropriate data collection or using energy effectively to transmit medical data without the expense of travel and length has become an important one. To address this issue, the present research work ‘Link Quality and Energy Efficient Optimal Clustering-Multipath (LEOC-MP)’ scheme tries to explore an answer. The main goals of the LEOC-MP (Optimal Link Quality and Energy Efficient Optimal Clustering-Multipath) system are to guarantee node-to-node link quality, lengthen network life, and compute high-performing cluster heads to guarantee reliable multi path data transfer. This work was executed in three phases. First, an optimal simplified clustering technique for data collection from body sensors using an improved pelican optimization (ICO) algorithm is introduced. Next, multiple design constraints for node rank computation, energy efficiency, link quality, path loss, distance, and delay are used. Besides, an Auto-Regressive Probabilistic Neural Network (AR-PNN) is introduced to optimize those design constraints and compute the cluster head (CH) of each cluster. Multipath firing is then performed using a moderated puffer-fish optimization (MPO) algorithm that finds the closest optimal and shortest node to transmit optimal drug data. The work is simulated using an NS-3 environment, and the results are obtained. The outcome of this work is analyzed with existing methodologies, and the results prove that the present work consistently outperforms the existing methodologies.

Opportunities of IoT in Fog Computing for High Fault Tolerance and Sustainable Energy Optimization

Today, the importance of enhanced quality of service and energy optimization has promoted research into sensor applications such as pervasive health monitoring, distributed computing, etc. In general, the resulting sensor data are stored on the cloud server for future processing. For this purpose, recently, the use of fog computing from a real-world perspective has emerged, utilizing end-user nodes and neighboring edge devices to perform computation and communication. This paper aims to develop a quality-of-service-based energy optimization (QoS-EO) scheme for the wireless sensor environments deployed in fog computing. The fog nodes deployed in specific geographical areas cover the sensor activity performed in those areas. The logical situation of the entire system is informed by the fog nodes, as portrayed. The implemented techniques enable services in a fog-collaborated WSN environment. Thus, the proposed scheme performs quality-of-service placement and optimizes the network energy. The results show a maximum turnaround time of 8 ms, a minimum turnaround time of 1 ms, and an average turnaround time of 3 ms. The costs that were calculated indicate that as the number of iterations increases, the path cost value decreases, demonstrating the efficacy of the proposed technique. The CPU execution delay was reduced to a minimum of 0.06 s. In comparison, the proposed QoS-EO scheme has a lower network usage of 611,643.3 and a lower execution cost of 83,142.2. Thus, the results show the best cost estimation, reliability, and performance of data transfer in a short time, showing a high level of network availability, throughput, and performance guarantee.

A quantum trust and consultative transaction-based blockchain cybersecurity model for healthcare systems

Many researchers have been interested in healthcare cybersecurity for a long time since it can improve the security of patient and health record data. As a result, a lot of research is done in the field of cybersecurity that focuses on the safe exchange of health data between patients and the medical setting. It still has issues with high computational complexity, increased time consumption, and cost complexity, all of which have an impact on the effectiveness and performance of the complete security system. Hence this work proposes a technique called Consultative Transaction Key Generation and Management (CTKGM) to enable secure data sharing in healthcare systems. It generates a unique key pair based on random values with multiplicative operations and time stamps. The patient data is then safely stored in discrete blocks of hash values using the blockchain methodology. The Quantum Trust Reconciliation Agreement Model (QTRAM), which calculates the trust score based on the feedback data, ensures reliable and secure data transfer. By allowing safe communication between patients and the healthcare system based on feedback analysis and trust value, the proposed framework makes a novel contribution to the field. Additionally, during communication, the Tuna Swarm Optimization (TSO) method is employed to validate nonce verification messages. Nonce message verification is a part of QTRAM that helps verify the users during transmission. The effectiveness of the suggested scheme has been demonstrated by comparing the obtained findings with other current state-of-the-art models after a variety of evaluation metrics have been analyzed to test the performance of this security model.

A Resource Efficient Software-Hardware Co-Design of Lattice-Based Homomorphic Encryption Scheme on the FPGA

Lattice-based homomorphic encryption schemes provide strong resistance against quantum and classical computer-based adversary security attacks. In this paper, we present a software-hardware co-design of two partially homomorphic encryption (PHE) schemes employing an ARM-SoC and an FPGA This provides necessary acceleration to PHE methods in the ecosystem mentioned above. The first PHE scheme is designed for generic homomorphic encryption, while the second scheme is aimed at resource optimized lightweight IoT-driven applications. For seamless assimilation, a robust and reliable low latency data transfer protocol is developed between the FPGA-based accelerator IP and ARM-SoC host system. The proposed PHE schemes are realized using Verilog HDL on multiple FPGA platforms. The proposed lightweight scheme is <inline-formula><tex-math notation="LaTeX">$52.71\times$</tex-math></inline-formula> more resource-efficient than the pipelined BGV RLWE-based method. It exhibits <inline-formula><tex-math notation="LaTeX">$1.43\times$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$1.29\times$</tex-math></inline-formula> better throughput than non-pipelined and pipelined realizations of the BGV RLWE-based scheme. The proposed hardware accelerators realized on FPGA platforms having lesser clock speed and consuming lower resources showcase significant speedup compared to their software implementations making our proposed method an efficient alternative to enhance security in edge-enabled IoT devices.

A novel scheme to improve lifetime and real-time support for IEEE 802.15.4 based wireless personal area networks

IEEE 802.15.4 defines the working of physical and media access layers of a Low-Rate Wireless Personal Area Network (LR-WPAN). A LR-WPAN is a low cost, low power, and low data-rate network that offers reasonable lifetime and reliable data transfer within a limited range. However, it faces several challenges whilst dealing with applications that are having strict timeliness, energy, and bandwidth requirements. This paper proposes an efficient superframe structure for the MAC layer of IEEE 802.15.4 networks that intends to deal with these challenges by varying the functionalities of Guaranteed Time Slot (GTS) bits. Simulations of different GTS allocation techniques show that our enhanced scheme outperforms the original standard as well as previous techniques in terms of energy consumption, average delay, maximum GTS allocation and reliability.

Comparative Review of Selected Internet Communication Protocols

Abstract With a large variety of communication methods and protocols, many software architects face the problem of choosing the best way for services to share information. For communication technology to be functional and practical, it should enable developers to define a complete set of CRUD methods for the processed data. The research team compared this paper’s most commonly used data transfer protocols and concepts: REST, WebSocket, gRPC GraphQL and SOAP. A set of web servers was implemented in Python, each using one of the examined technologies. Then, the team performed an automated benchmark measuring time and data transfer overhead for a set of defined operations: creating an entity, retrieving a list of 100 entities and fetching details of one entity. Tests were designed to avoid the results being interfered with by database connection or docker-compose environment characteristics. The research team has concluded that gRPC was the most efficient and reliable data transfer method. On the other hand, GraphQL turned out to be the slowest communication method of all. Moreover, its server and client libraries caused the most problems with proper usage in a web server. SOAP did not participate in benchmarking due to limited compatibility with Python and a lack of popularity in modern web solutions.

Generic Patient-Centered Blockchain-Based EHR Management System

Accessing healthcare services by several stakeholders for diagnosis and treatment has become quite prevalent owing to the improvement in the industry and high levels of patient mobility. Due to the confidentiality and high sensitivity of electronic healthcare records (EHR), the majority of EHR data sharing is still conducted via fax or mail because of the lack of systematic infrastructure support for secure and reliable health data transfer, delaying the process of patient care. As a result, it is critically essential to provide a framework that allows for the efficient exchange and storage of large amounts of medical data in a secure setting. The objective of this research is to develop a Patient-Centered Blockchain-Based EHR Management (PCEHRM) system that allows patients to manage their healthcare records across multiple stakeholders and to facilitate patient privacy and control without the need for a centralized infrastructure by means of granting or revoking access or viewing one’s records. We used an Ethereum blockchain and IPFS (inter-planetary file system) to store records because of its advantage of being distributed and ensuring the immutability of records and allowing for the decentralized storage of medical metadata, such as medical reports. To achieve secure a distributed, and trustworthy access control policy, we proposed an Ethereum smart contract termed the patient-centric access control protocol. We demonstrate how the PCEHRM system design enables stakeholders such as patients, labs, researchers, etc., to obtain patient-centric data in a distributed and secure manner and integrate utilizing a web-based interface for the patient and all users to initiate the EHR sharing transactions. Finally, we tested the proposed framework in the Windows environment by compiling a smart contract prototype using Truffle and deploy on Ethereum using Web3. The proposed system was evaluated in terms of the projected medical data storage costs for the IPFS on blockchain, and the execution time for a different number of peers and document sizes. The findings of the study indicate that the proposed strategy is both efficient and practicable.

НЕРОЗДІЛЬНІ БЛОЧНІ 9-РОЗРЯДНІ ЗАВАДОСТІЙКІ КОДИ ДЛЯ ВИПРАВЛЕННЯ ОДНОРАЗОВОЇ ПОМИЛКИ

With the rapid development of digital telecommunication technologies, the usage of new methods to increase the speed and reliability of data transfer is becoming more relevant. Examples may include data encoding based on the artificial introduction of redundancy and enabling the receiving side not only to detect data distortions but also to form correct values. The separable codes (for example, the Hamming codes) are inferior to non-separable error correction codes in speed. But the increase in the speed of data transmission requires utilising complex, multipoaitional algorithms for searching maximal codes. This leads to an increase in the time of static proof codes determination compared to separable codes, although the speed of data transmission in operation is increased as well, having identical capacities for fault resistant. &nbsp;Technology is proposed that is based on using 9-bit non-separable codes and the encoders/decoders for them, factoring in the fact of absence of the generalised theory of building them. Factoring in the aspects of specialised devices implementation based on an integral technology, the usage of FPGA technology is the most opportune. &nbsp;For practical implementation of universal encodecs/decoders for 9-bit non-separable codes, an approach is proposed utilising FPGA that can be configured to any of these codes with any decimal numbers (the non-separable codes do not contain informational and test parts). Such properties of non-separable codes enable increasing the transmission speed of BCD words. Additionally, the obtained results could be a basis for the further development of a theory and practice for employing the block inseparable codes when the block size increases and it is a reassuring factor as for the analysis of non-separable codes in case of two or more errors correction.

An effective adjustment approach of event reliability (EAAER) with mobile sink using shortest path routing for WSN

A crucial requirement for Wireless Sensor Networks (WSNs) is reliable data transfer. To maintain the overall reliability of the network, it is essential that the data delivered from a source node reach its intended destination without any loss or errors. In order to collect data from the sensor nodes that are deploy randomly around the sensor region, wireless sensor networks (WSNs) typically use static sinks. In the static sink-based technique, the data packets are transmitted through the network to reach the base station. The static sink is ineffective at utilizing energy as a result. This paper presents an effective adjustment approach for event reliability (EAAER) to find duplicate events using a mobile sink for homogenous wsn’s. The EAAER approach improves the routing against the base model by using shortest path routing. Simulation results show that the performance of EEAER increases battery utilization and the number of received packets while minimizing duplicate packets and packets lost during transmission compared to the base model.

The effect of reliable data transfer and efficient computer network features in Jordanian banks accounting information systems performance based on hardware and software, database and number of hosts

Reliable data transfer protocols are algorithmic techniques that guarantee the safe and secure transport of data through networks that could experience data loss or corruption. The performance of the systems and some accounting information systems (AIS) will be negatively impacted if the real-time data is not sent. The main factors that affect the performance of computer networks are the number of users, the hardware and software and the bandwidth. The computer network performance will play a role in the performance of the banks as it is an important component of the bank infrastructure. With the advancement of information technology, network technology, and computer technology, computers have been utilized to aid AIS operations, and AIS has become an unavoidable trend of development. Therefore, the purpose of this study was to investigate Data analysis in computer networks to improve AIS performance in Jordanian banks. A questionnaire was used to obtain the information. Jordanian banks account for the bulk of the participants in the survey. A total of 115 people took part in the study. According to the conclusions of this study, communication technology networks have a statistically significant impact on the growth of Jordanian banks' improved AIS performance.

Mechanisms of ensuring the accuracy and reliability of data transmission over a radio channel using relay technology and their implementation on transceivers with LoRa modulation

The article is devoted to a detailed description of the algorithms of the operation of the relay-race data transmission system over a radio channel, which ensure high reliability of transporting the results of monitoring the operation of extended objects to the central control panel. The feature of the system is operation at a low power level of transmitters, energy efficiency, which ensures a long-term operation without maintenance, the ability to replace failed elements quickly without stopping the entire system, mobility — quick installation and start-up of the system. Energy efficiency and operation of the radio channel with a low transmitter power level is ensured by the use of SX 1276 (LoRa) transceivers. The accuracy and reliability of data transmission is ensured by original algorithms, which are described in the paper. In the relay data transmission system, it is possible to use up to 255 relay nodes with their installation at a distance of up to 4 km from each other. Two options of building a system with relay-race transmission have been developed: a system with a simple handover, a system with transmission «Through one». The second option provides more reliable data transfer and higher probability of uptime. With the number of relay nodes equal to 50, the probability of failure-free operation of a simple system is 0.268, and for the system with «Through one» transmission is 0.985.

Dipper Throated Optimization for Detecting Black-Hole Attacks in MANETs

In terms of security and privacy, mobile ad-hoc network (MANET) continues to be in demand for additional debate and development. As more MANET applications become data-oriented, implementing a secure and reliable data transfer protocol becomes a major concern in the architecture. However, MANET’s lack of infrastructure, unpredictable topology, and restricted resources, as well as the lack of a previously permitted trust relationship among connected nodes, contribute to the attack detection burden. A novel detection approach is presented in this paper to classify passive and active black-hole attacks. The proposed approach is based on the dipper throated optimization (DTO) algorithm, which presents a plausible path out of multiple paths for statistics transmission to boost MANETs’ quality of service. A group of selected packet features will then be weighed by the DTO-based multi-layer perceptron (DTO-MLP), and these features are collected from nodes using the Low Energy Adaptive Clustering Hierarchical (LEACH) clustering technique. MLP is a powerful classifier and the DTO weight optimization method has a significant impact on improving the classification process by strengthening the weights of key features while suppressing the weights of minor features. This hybrid method is primarily designed to combat active black-hole assaults. Using the LEACH clustering phase, however, can also detect passive black-hole attacks. The effect of mobility variation on detection error and routing overhead is explored and evaluated using the suggested approach. For diverse mobility situations, the results demonstrate up to 97% detection accuracy and faster execution time. Furthermore, the suggested approach uses an adjustable threshold value to make a correct conclusion regarding whether a node is malicious or benign.

Low Latency Reliable Data Sharing Mechanism for UAV Swarm Missions

The use of Unmanned Aerial Vehicle (UAV) swarms is increasing in many commercial applications as well as military applications (such as reconnaissance missions, search and rescue missions). Autonomous UAV swarm systems rely on multi-node interhost communication, which is used in coordination for complex tasks. Reliability and low latency in data transfer play an important role in the maintenance of UAV coordination for these tasks. In these applications, the control of UAVs is performed by autonomous software and any failure in data reception may have catastrophic consequences. On the other hand, there are lots of factors that affect communication link performance such as path loss, interference, etc. in communication technology (WIFI, 5G, etc.), transport layer protocol, network topology, and so on. Therefore, the necessity of reliable and low latency data sharing mechanisms among UAVs comes into prominence gradually. This paper examines available middleware solutions, transport layer protocols, and data serialization formats. Based on evaluation results, this research proposes a middleware concept for mobile wireless networks like UAV swarm systems.

Reliable Wide-Area Data Transfers for Streaming Workflows

Many large science projects rely on remote clusters for (near) real-time data processing, thus they demand reliable wide-area data transfer performance for smooth end-to-end workflow executions. However, data transfers are often exposed to performance variations due to the changing network (e.g., background traffic) and dataset (e.g., average file size) conditions, necessitating adaptive solutions to meet stringent performance requirements of delay-sensitive streaming workflows. In this article, we propose <i>FStream++</i> to provide reliable transfer performance for large streaming science applications by dynamically adjusting transfer settings to adapt to changing transfer conditions. <i>FStream++</i> combines three optimization methods as <i>dynamic tuning</i> , <i>online profiling</i> , and <i>historical analysis</i> to swiftly and accurately discover optimal transfer settings that can meet workflow requirements. Dynamic tuning uses a heuristic model to predict the values of transfer parameters based on dataset characteristics and network settings. Since heuristic models fall short to incorporate many important factors such as I/O throughput and resource interference, we complement it with online profiling to execute a real-time search for a subset of transfer settings. Finally, historical analysis takes advantage of the long-running nature of streaming workflows by storing and analyzing previous performance observations to shorten the execution time of online profiling. We evaluate the performance of <i>FStream++</i> by transferring several synthetic and real-world workloads in high-performance production networks and show that it offers up to <inline-formula><tex-math notation="LaTeX">$3.6x$</tex-math></inline-formula> performance improvement over legacy transfer applications and up to 24% over our previous work <i>FStream</i> .

Efficient Communication Model for a Smart Parking System with Multiple Data Consumers

A smart parking system (SPS) is an integral part of smart cities where Internet of Things (IoT) technology provides many innovative urban digital solutions. It offers hassle-free parking convenience to the city dwellers, metering facilities, and a revenue source for businesses, and it also protects the environment by cutting down drive-around emissions. The real-time availability information of parking slots and the duration of occupancy are valuable data utilized by multiple sectors such as parking management, charging electric vehicles (EV), car servicing, urban infrastructure planning, traffic regulation, etc. IPv6 wireless mesh networks are a good choice to implement a fail-safe, low-power and Internet protocol (IP)-based secure communication infrastructure for connecting heterogeneous IoT devices. In a smart parking lot, there could be a variety of local IoT devices that consume the occupancy data generated from the parking sensors. For instance, there could be a central parking management system, ticketing booths, display boards showing a count of free slots and color-coded lights indicating visual clues for vacancy. Apart from this, there are remote user applications that access occupancy data from browsers and mobile phones over the Internet. Both the types of data consumers need not collect their inputs from the cloud, as it is beneficial to offer local data within the network. Hence, an SPS with multiple data consumers needs an efficient communication model that provides reliable data transfers among producers and consumers while minimizing the overall energy consumption and data transit time. This paper explores different SPS communication models by varying the number of occupancy data collators, their positions, hybrid power cycles and data aggregation strategies. In addition, it proposes a concise data format for effective data dissemination. Based on the simulation studies, a multi-collator model along with a data superimposition technique is found to be the best for realizing an efficient smart parking system.

ACHORD: Communication-Aware Multi-Robot Coordination With Intermittent Connectivity

Communication is an important capability for multi-robot exploration because (1) inter-robot communication (comms) improves coverage efficiency and (2) robot-to-base comms improves situational awareness. Exploring comms-restricted (e.g., subterranean) environments requires a multi-robot system to tolerate and anticipate intermittent connectivity, and to carefully consider comms requirements, otherwise mission-critical data may be lost. In this paper, we describe and analyze ACHORD (Autonomous & Collaborative High-Bandwidth Operations with Radio Droppables), a multi-layer networking solution which tightly co-designs the network architecture and high-level decision-making for improved comms. ACHORD provides bandwidth prioritization and timely and reliable data transfer despite intermittent connectivity. Furthermore, it exposes low-layer networking metrics to the application layer to enable robots to autonomously monitor, map, and extend the network via droppable radios, as well as restore connectivity to improve collaborative exploration. We evaluate our solution with respect to the comms performance in several challenging underground environments including the DARPA SubT Finals competition environment. Our findings support the use of data stratification and flow control to improve bandwidth-usage.

Effect of Messaging Model on the Reliable Data Transfer Latency in a Fog System

Effect of Messaging Model on the Reliable Data Transfer Latency in a Fog System

Efficient Hardware Architectures and Implementations of Packet-Level Erasure Coding Schemes for High Data Rate Reliable Satellite Communications

Forward error correction coding schemes have been used extensively in order to provide continuous and reliable telemetry data transfer from satellites to ground stations and guarantee reliable communications even at low signal-to-noise ratio regimes, where burst errors are dominant. Nevertheless, conventional bit-level channel coding can fail to provide downlink reliability against long error bursts in future high data rate radio frequency and optical (laser) links, especially when automatic repeat queuing strategies are either problematic or impossible due to specific service delay constraints. Packet-level erasure coding has been considered by the Consultative Committee for Space Data Systems (CCSDS) in CCSDS 131.5-O-1 experimental specification for application in high data rate near-earth and deep-space communications, since it can protect against long error bursts as they may come along with the effect of scintillation outages or transmission errors. Implementations of packet-level encoding and decoding so far exist only in software, running on a general-purpose CPU. In this article, we introduce and compare analytical descriptions of packet-level encoding algorithms suitable for hardware implementations. Based on these algorithmic descriptions, we introduce, for the first time, architectures for hardware acceleration of these functions that allow integration on a high-speed on-board data-processing chain with very low footprint. We validate our hardware implementations and demonstrate the efficiency of the proposed architectures on a Xilinx KCU105 development board, which is built around the commercial equivalent of a space-grade field-programmable gate array device. Apart from offloading packet-level encoding from the on-board embedded processor, the proposed accelerators achieve a significant speedup (over 80 times), when compared with on-board software implementations, by porting on some of the most commonly used and state-of-the-art space-qualified embedded processors.

A K-Means and Ant Colony Optimization-Based Routing in Underwater Sensor Networks

Reliable data transfer seems a quite challenging task in underwater sensor networks (UWSNs) in comparison with terrestrial wireless sensor networks due to the peculiar attributes of UWSN communication. Therefore, K-means and ant colony optimization-based routing (KACO) is proposed in this paper. In KACO, network area under water is divided into layers with regard to the depth level. And nodes of each layer are divided into clusters by the optimized K-means algorithm. The K-means algorithm is used to cluster nodes. Considering the shortcoming of K-means clustering, an improved K-means clustering is used to select the initial cluster center. In the stage of selecting cluster heads, the remaining energy of nodes and the distance from the sink node are used to calculate the competing factors of nodes, and then, the cluster heads are selected according to the competing factors. In the intercluster routing, the ant colony optimization (ACO) was improved by introducing the Gini coefficient, and the intercluster routing based on improved ACO is proposed. The simulation results show that the proposed KACO routing can effectively reduce the energy consumption of nodes and improve the efficiency of packet transmission.