Communication Algorithms Research Articles

Development and Simulation of a Fast Delay Cancellation Algorithm for Digital Multimedia Network Communication

The digital multimedia network data traffic is huge, and many end devices are applied to the digital multimedia network; therefore, the digital media network communication delay transmission must be analysed in order to improve the performance of the digital multimedia network communication transmission. Due to the presence of a large number of data packets in the communication network used, some random delays in data can occur during use. Conventional data transmission methods rely solely on extended data storage capacity to achieve this, making it difficult to achieve intelligent scheduling, resulting in delays and optimized performance degradation during communication data transmission. The aim of this paper is to enhance the communication quality of digital multimedia networks by developing an algorithmic model that rapidly mitigates communication delays. The proposed approach employs a delay cancellation algorithm in a network predictive control system. Simulation techniques are utilized to simulate and compensate for delays in multimedia communication networks. The efficacy of the network control strategy is demonstrated through simulation tests on a large-scale multimedia network communication system. The research findings indicate that the network control prediction model and elimination algorithm can substantially reduce the packet loss rate and quickly eliminate communication delays in digital multimedia networks.

Development of robust communication algorithm between machine vision and boom sprayer for spot application via ISO 11783

A communication algorithm to send data via the standard communication protocol for agricultural implements, ISO 11783, was developed and tested in this research work. The goal was to enable a universal method to integrate machine vision systems to sprayers so that sensor-based real-time spot spraying becomes possible in the future. The algorithm receives pest detection results from a machine vision and constructs messages compatible with ISO 11783 (also known as ISOBUS), which gets sent to the sprayer. This allows for simultaneous opening of different nozzles on the sprayer even when pests are detected by different cameras at different locations across the boom. The results on our spraying apparatus which consisted of 6 nozzles showed that correct spraying commands were sent to the nozzles 100% of the times for all possible 64 simultaneous nozzle opening/closing combinations. The algorithm was designed to construct CAN frames based on arithmetic rather than logic operations. Also, the increase of data load on the ISOBUS of the sprayer was limited to 5.2%. Moreover, no data loss between the machine vision system and the sprayer was observed even when the data frames were sent every 10 milliseconds. The electronic control unit (ECU) on which the algorithm was written has two interfaces, one communicates with the machine vision system using serial communication, and the other communicates with the sprayer using the ISOBUS. The universal serial communication protocol used in this development allows for immediate integration to the ECU which creates the messages according to the specifications of the nozzle control unit of the sprayer.

Preface

The 2022 2nd International Conference on Computer Technology, Information Engineering and Electron Materials (CTIEEM 2022) was successfully held in Guangzhou, China from November 25th-27th, 2022 (virtual form). The conference is a leading academic conference and has the potential to bring new horizons and insights to the researchers and practitioners in the fields related to computer technology, information engineering and electron materials.CTIEEM 2022 created an academic platform for academic sharing and scientific innovation, brought together experts, scholars, and engineering and technical personnel from all over the world to present their research results and exchange ideas, promoted the industrial cooperation of academic achievements, and facilitated future business or research contacts among all the participants.The scope of the conference covered all areas of research in computer technology, information engineering and electron materials, including Wireless Sensor Network, Array Signal Processing Technology, Intelligent and Optimal Control System, Electrical Engineering Materials, Magnetic Material, etc. The conference brought together about 50 participants, primarily from China, but also from Malaysia, Korea, and other countries.A three-day program of the conference was divided into three sessions, including keynote speeches, oral presentations, and academic investigation. Each keynote speaker was given 30-40 minutes for keynote speeches and every presenter was given 10-15 minutes. Among them, Prof. Qin Xin from University of the Faroe Islands, Denmark is one of our keynote speakers and performed a wonderful keynote speech for us. His researches mainly focus on the design and analysis of sequential, parallel and distributed algorithms for various communication and optimization problems in wireless communication networks, as well as cryptography and digital currencies including quantum money. Moreover, he also investigates the combinatorial optimization problems with applications in Bioinformatics, Data Mining and Space Research and has produced more than 111 peer reviewed scientific papers, which are mainly published in leading international conferences and journals, such as ICALP, ACM PODC, IEEE MASS, ISAAC, IEEE ICC, etc. Currently, Prof. Qin Xin is serving on Management Committee Board of Denmark for several EU ICT projects. The insightful speeches of each keynote speakers triggered interesting discussions and a good number of informal talks between all the participants.We would like to thank all the participants in the 2022 2nd International Conference on Computer Technology, Information Engineering and Electron Materials. Besides, our special acknowledgement goes to the Journal of Physics: Conference Series, for the endeavor of all its colleagues in publishing this paper volume. We are sure that the proceedings of CTIEEM 2022 will serve as an important research source for references, which will contribute to not only scientific and engineering progress but also other new products and processes.The Committee of CTIEEM 2022List of Committee member are available in this pdf

Abstract Number ‐ 278: Transient Ischemic Attack Evaluation Pathways: Inpatient Versus Expedited Outpatient Comparative Analysis

Introduction Transient Ischemic Attack (TIA) evaluation requires urgent etiology identification and targeted stroke prevention, traditionally performed via hospital admission. The literature suggests that outpatient evaluation may be safe and cost‐effective. Hence, we implemented an expedited outpatient pathway (OP) for patients presenting to our institution’s Emergency Department (ED) with TIA. To further guide future practice, we compared clinical features and outcomes between expedited OP and our well‐established inpatient pathway (IP). Methods We implemented an algorithm of direct communication between ED providers and Vascular Neurologists for all TIA patients. Certain screening studies (head CT, CT angiogram, basic laboratories) and acute therapies were implemented in the ED, whereas others (brain MRI, echocardiogram, etc) and Vascular Neurology consultations were expedited outpatient within 48–72 hours.We included all patients that underwent OP evaluation from May 2021‐May 2022. Further, we extracted patients with a final diagnosis of TIA and compared them with IP TIA patients hospitalized (2017‐2021), matched by age, gender, and clinical severity (ABCD2). Descriptive statistics were used to summarize patient demographics, clinical data, treatments, and 3‐month outcomes. Continuous variables were summarized with mean and standard deviations while categorical variables were shown as counts and percentages. Chi‐square test was used for categorical variables and Mann‐Whitney U test was used to compare continuous variables. P‐values < 0.05 were considered statistically significant and all tests were two‐sided. Statistical Analysis was completed in R 4.0.3. Results Of 43 patients who underwent expedited OP TIA workup, TIA or minor stroke was diagnosed in 21/43 (48.9%). 18 TIAs underwent comparative analyses. Mean symptom duration was longer in the IP (2.06 hours) than OP (0.99 hours), p = 0.370%. TIA was more likely to be diagnosed in the OP 14/18 (78%) versus IP 12/18 (67%), (p = 0.423). OP had more transesophageal echocardiograms (17% vs 5%, p = 0.630) and longer duration of ambulatory cardiac monitoring (mean 574.3 vs 381.7 hours, p = 0.100). IP patients were more likely to get started on anticoagulation compared to OP (38% vs 11%, p = 0.258) and high‐intensity statin (38% vs 17%, p = 0.260). All laboratories, echocardiograms and brain MR imaging were performed significantly sooner for the IP (p< 0.05 for all). IP had higher rate of return ED visits (22%) and readmissions at 3 months (11%), whereas OP had none. OP had no deaths or recurrent strokes, whereas 11% and 5.6% respectively were noted in the IP at 3 months (p = 0.310, p = 0.310). Conclusions Our study shows that routine IP evaluation for patients presenting with TIA in the ED may not offer diagnostic superiority nor lead to improvement of short‐term clinical outcomes, as compared to the expedited OP evaluation. Careful evaluation of TIA patients in the ED followed by expedited OP evaluation might be a plausible approach to help lower costs and avoid hospitalization without compromising the safety of these patients.

Ultra-Short Wave Communication Squelch Algorithm Based on Deep Neural Network

The squelch problem of ultra-short wave communication under non-stationary noise and low Signal-to-Noise Ratio (SNR) in a complex electromagnetic environment is still challenging. To alleviate the problem, we proposed a squelch algorithm for ultra-short wave communication based on a deep neural network and the traditional energy decision method. The proposed algorithm first predicts the speech existence probability using a three-layer Gated Recurrent Unit (GRU) with the speech banding spectrum as the feature. Then it gets the final squelch result by combining the strength of the signal energy and the speech existence probability. Multiple simulations and experiments are done to verify the robustness and effectiveness of the proposed algorithm. We simulate the algorithm in three situations: the typical Amplitude Modulation (AM) and Frequency Modulation (FM) in the ultra-short wave communication under different SNR environments, the non-stationary burst-like noise environments, and the real received signal of the ultra-short wave radio. The experimental results show that the proposed algorithm performs better than the traditional squelch methods in all the simulations and experiments. In particular, the false alarm rate of the proposed squelch algorithm for non-stationary burst-like noise is significantly lower than that of traditional squelch methods.

AGCM-3DLF: Accelerating Atmospheric General Circulation Model via 3-D Parallelization and Leap-Format

The atmospheric general circulation model (AGCM) has been an important research tool in the study of climate change for decades. As the demand for high-resolution simulation is becoming urgent, the scalability and simulation efficiency is faced with great challenges, especially for the latitude-longitude mesh-based models. In this paper, we propose a highly scalable 3-D atmospheric general circulation model based on leap-format, namely AGCM-3DLF. First, it utilizes a 3-D decomposition method allowing for parallelism release in all three physical dimensions. Then the leap-format difference computation scheme is adopted to maintain computational stability in grid updating and avoid additional filtering at the high latitudes. A novel shifting window communication algorithm is designed for parallelization of the unified model. Furthermore, a series of optimizations are conducted to improve the effectiveness of large-scale simulations. Experiment results in different platforms demonstrate good efficiency and scalability of the model. AGCM-3DLF scales up to the entire CAS-Xiandao1 supercomputer (196,608 CPU cores), attaining the speed of 11.1 simulation-year-per-day (SYPD) at a high resolution of 25KM. In addition, simulations conducted on the Sunway TaihuLight supercomputer exhibit a 1.06 million cores scalability with 36.1% parallel efficiency.

An Improved Energy Saving Technique for Wireless Power Transfer in Near Field Communication Systems

In this work, an improved communication algorithm was developed to reduce energy wastage in a Near Field Communication (NFC) system using dynamic field Strength scaling technique. With a variable resistor in the reader coil, the field strength of the system was scaled in real-time by adjusting the value of the resistor in relation to distance. This system was tested with the advanced design system's Application Extension Language (AEL) and simulated on Advanced Digital Technology. The results showed a responsive change in the magnetic field when the two scenarios (with and without optimization) were simulated. There was a 66% change in energy transfer within the time frame referenced. Results further indicated that the adoption of the proposed algorithm could help engineers to design a more effective NFC system.

Sum Rate Optimization Scheme of UAV-Assisted NOMA under Hardware Impairments

In the unmanned aerial vehicle (UAV) assisted non-orthogonal multiple access (NOMA) networks, the practical hardware impairments (HIs) and resource allocation is still a challenging problem. Most existing research on resource allocation algorithms for UAV communication is considered with the ideal hardware condition. However, the impact of HIs on system performance cannot be ignored, especially in the case of high bit rates. Considering the HIs, most studies are from the perspective of performance analysis. The resource allocation of UAV relay-assisted NOMA systems is investigated in this paper with HIs. We aim to maximize the sum rate by jointly optimizing the deployment of UAV and transmit power. To address this problem, we first transformed the mixed integer programming problem (MIPP) into a standard convex optimization problem based on successive convex approximation (SCA) technology. Then, we introduced the Lagrangian dual transformation and quadratic transform methods to solve the power allocation problem. Finally, we propose an effective iterative algorithm to achieve an approximate optimal solution. Numerical results demonstrate that the proposed algorithm achieved better performance in terms of the sum rate compared with other benchmark schemes.

Energy-efficient routing based on a genetic algorithm for satellite laser communication.

Low earth orbit satellite laser communication has become an important part of communications due to its large capacity and low latency. The lifetime of the satellite mainly depends on the recharge and discharge cycles of the battery. The low earth orbit satellites frequently recharge under sunlight and discharge in the shadow, which leads satellites to age quickly. This paper studies the energy-efficient routing problem for satellite laser communication and builds the satellite ageing model. Based on the model, we propose an energy-efficient routing scheme based on the genetic algorithm. Compared with shortest path routing, the proposed method improves the satellite lifetime by about 300%, and the performances of the network are only slightly degraded, the blocking ratio increases by only 1.2%, and the service delay increases by 1.3 ms.

Quantum encryption of superposition states with quantum permutation pad in IBM quantum computers

We present an implementation of Kuang and Bettenburg’s Quantum Permutation Pad (QPP) used to encrypt superposition states. The project was conducted on currently available IBM quantum systems using the Qiskit development kit. This work extends previously reported implementation of QPP used to encrypt basis states and demonstrates that application of the QPP scheme is not limited to the encryption of basis states. For this implementation, a pad of 56 2-qubit Permutation matrices was used, providing 256 bits of entropy for the QPP algorithm. An image of a cat was used as the plaintext for this experiment. The plaintext was randomized using a classical XOR function prior to the state preparation procedure. To create corresponding superposition states, we applied a novel operator defined in this paper. These superposition states were then encrypted using QPP, with 2-qubit Permutation Operators, producing superposition ciphertext states. Due to the lack of a quantum channel, we omitted the transmission and executed the decryption procedure on the same IBM quantum system. If a quantum channel existed, the superposition ciphertext states could be transmitted as qubits, and be directly decrypted on a different quantum system. We provide a brief discussion of the security, although the focus of the paper remains on the implementation. Previously we have demonstrated QPP operating in both classical and quantum computers, offering an interesting opportunity to bridge the security gap between classical and quantum systems. This work broadens the applicability of QPP for the encryption of basis states as well as superposition states. We believe that quantum encryption schemes that are not limited to basis states will be integral to a secure quantum internet, to reduce vulnerabilities introduced by using two separate algorithms for secure communication between a quantum and a classical computer.

An OFDM-Based Frequency Domain Equalization Algorithm for Underwater Acoustic Communication with a High Channel Utilization Rate

The underwater acoustic communication technique for high-speed and highly reliable information transmission in the ocean has been one of the popular research focuses facing the fast-growing information technology sector and the accelerating development of ocean resources. In order to achieve a high information transmission rate with limited underwater acoustic channel bandwidth, researchers have paid much attention to the underwater acoustic communication technique based on orthogonal frequency division multiplexing (OFDM). A traditional OFDM-based frequency domain equalization algorithm relies on cyclic prefixes for the effective resistance to the multipath effect of an underwater acoustic channel. However, a redundant cyclic prefix may lead to a severe waste of energy and bandwidth in the underwater acoustic system if it is too long. The high utilization rate of OFDM signal channel will not be practically achieved in this case. Based on the limitations of the existing frequency domain equalization algorithm, this paper studied the influence of the multipath effect on the OFDM signal transmission. Subsequently, the principles of the OFDM-based frequency domain equalization were further explored for an improved structural model design of the communication system. On this basis, a novel frequency domain adaptive equalization algorithm was put forward. In addition, the proposed algorithm was optimized to address the problem of increased computation. The simulation results proved that the novel frequency domain equalization algorithm delivers a better symbol error ratio than the existing algorithm, and the compensation for the multipath effect through frequency selective fading. The proposed algorithm can realize the information transmission at a low symbol error ratio when fewer cyclic prefixes are used, so that it takes up a lower number of channels with cyclic prefixes in the OFDM communication system.

MOCAB/HEFT algorithm of multi radio wireless communication improved achievement assessment

Network-wide conveying is vital in remote associations, and the great part of these broadcasts are built on single-channel single-radio (SC-SR) network frameworks. The problem of the current work is divided into two parts. The first part shows that increasing broadcast and redundancy lead to an increase in time consumption. The second problem is solving complexity problems when tasks are scheduled in a heterogeneous manner in a computing system, where the processors in the network may not be identical and take different time periods to carry out the same task. The goals of this work are to reduce the total cost of network-wide broadcasting to minimize the search space and to solve the complexity problem when tasks are scheduled in a heterogeneous way in the computing system. The MOCAB algorithm is used to select the best transmission path over the network in the first stage. Then, the tasks will be scheduled using the heterogeneous earliest finish time (HEFT) algorithm to extract the values of actual finish time (AFT), earliest start time (EST), and earliest finish time (EFT). The performance of the MOCAB algorithm was evaluated with that of the HEFT algorithm in terms of the delivery ratio of packets delivered. The results showed that the MOCAB algorithm outperformed the HEFT.

A Novel Approach for Integrated Shortest Path Finding Algorithm (ISPSA) Using Mesh Topologies and Networks-on-Chip (NOC)

A novel data dispatching or communication technique based on circulating networks of any network IP is suggested for multi data transmission in multiprocessor systems using Networks-On-Chip (NoC). In wireless communication network management have some negatives have heavy data losses and traffic of data sending data while packet scheduling and low performance in the varied network due to workloads. To overcome the drawbacks, in this method proposed system is Integrated Shortest Path Search Algorithm (ISPSA) using mesh topologies. The message is sent to IP (Internet Protocol) in the network until the specified bus accepts it. Integrated Shortest Path Search Algorithm for communication between two nodes is possible at any one moment. On-chip wireless communications operating at specific frequencies are the most capable option for overcoming metal interconnects multi-hop delay and excessive power consumption in Network-on-Chip (NoC) devices. Each node can be indicated by a pair of coordinates (level, position), where the level is the tree's vertical level and the view point is its horizontal arrangement in the sequence of left to right. The output gateway node's n nodes are linked to two nodes in the following level, with all resource nodes located at the bottommost vertical level and the constraint of this topology is its narrow bisection area. The software Xilinx 14.5 tool by using that overall performance analysis of mesh topology, each method are reduced data losses with better accuracy although the productivity of the delay is decreased by 21 % was evaluated and calculated..

Trans-UTPA: PSO and MADDPG based multi-UAVs trajectory planning algorithm for emergency communication.

Communication infrastructure is damaged by disasters and it is difficult to support communication services in affected areas. UAVs play an important role in the emergency communication system. Due to the limited airborne energy of a UAV, it is a critical technical issue to effectively design flight routes to complete rescue missions. We fully consider the distribution of the rescue area, the type of mission, and the flight characteristics of the UAV. Firstly, according to the distribution of the crowd, the PSO algorithm is used to cluster the target-POI of the task area, and the neural collaborative filtering algorithm is used to prioritize the target-POI. Then we also design a Trans-UTPA algorithm. Based on MAPPO 's policy network and value function, we introduce transformer model to make Trans-UTPA's policy learning have no action space limitation and can be multi-task parallel, which improves the efficiency and generalization of sample processing. In a three-dimensional space, the UAV selects the emergency task to be performed (data acquisition and networking communication) based on strategic learning of state information (location information, energy consumption information, etc.) and action information (horizontal flight, ascent, and descent), and then designs the UAV flight path based on the maximization of the global value function. The experimental results show that the performance of the Trans-UTPA algorithm is further improved compared with the USCTP algorithm in terms of the success rate of each UAV reaching the target position, the number of collisions, and the average reward of the algorithm. Among them, the average reward of the algorithm exceeds the USCTP algorithm by 13%, and the number of collisions is reduced by 60%. Compared with the heuristic algorithm, it can cover more target-POIs, and has less energy consumption than the heuristic algorithm.

Hybrid CPU–GPU implementation of the transformed spatial domain channel estimation algorithm for mmWave MIMO systems

Hybrid platforms combining multicore central processing units (CPU) with many-core hardware accelerators such as graphic processing units (GPU) can be smartly exploited to provide efficient parallel implementations of wireless communication algorithms for Fifth Generation (5G) and beyond systems. Massive multiple-input multiple-output (MIMO) systems are a key element of the 5G standard, involving several tens or hundreds of antenna elements for communication. Such a high number of antennas has a direct impact on the computational complexity of some MIMO signal processing algorithms. In this work, we focus on the channel estimation stage. In particular, we develop a parallel implementation of a recently proposed MIMO channel estimation algorithm. Its performance in terms of execution time is evaluated both in a multicore CPU and in a GPU. The results show that some computation blocks of the algorithm are more suitable for multicore implementation, whereas other parts are more efficiently implemented in the GPU, indicating that a hybrid CPU–GPU implementation would achieve the best performance in practical applications based on the tested platform.

An Artificial Intelligence-Assisted Expectation Propagation Detection for MIMO Systems

Multiple-input multiple-output (MIMO) technology is one of the key technical approaches to improve the spectrum efficiency of wireless communication. Modern communication systems employ MIMO and high-order quadrature amplitude modulation (QAM) to maximize spectral efficiency. However, with the increase in the number of antennas and modulation orders, it is very challenging to design a low-complexity and high-efficiency MIMO receiver. In recent years, with the rapid development of new technologies such as artificial intelligence, more and more researchers have tried to apply machine learning techniques in the field of communication to break through the performance of traditional communication algorithms. In this paper, we propose a new low-complexity MIMO detection algorithm: an artificial intelligence-assisted expectation propagation (EP) detection algorithm. Neural network models are used to learn and map some of the time-consuming steps in the EP detection algorithm, converting the complex operation process into a few matrix multiplication operations in order to reduce the complexity of the detection algorithm. It is verified that the method proposed in this paper can approximate the performance of the original EP detection algorithm with reduced complexity and is applicable in different scenarios.

An Advanced Robotic System for Precision Chemical Thinning of Apple Blossoms

Highlights A cartesian robotic spraying system was developed for precision apple blossom thinning. Flower clusters were detected and localized with deep learning model for target spraying. A communication algorithm was developed for positioning the spray end-effector to the target flowers. The cartesian robotic system greatly reduced chemical usage while maintaining thinning effectiveness in the final green fruit set. Abstract. Crop thinning, including blossom thinning, is one of the critical management strategies that determines the annual profitability of apple orchards. Challenges still remain for applying appropriate amounts of chemical thinner; if thinning is inadequate and too many fruits remain on the tree, fruit size will be small, fruit quality will be poor, and flower bud initiation for the following year’s crop may be either reduced or eliminated. Over-thinning also carries economic perils since yield and crop value in the year of application will be reduced. In addition, chemical thinning with excessive spray volume may cause leaf damage and fruit russeting. Thus, a robotic apple blossom thinning system was proposed, aiming to reduce the usage of chemical thinner while maintaining good thinning performance. The robotic system consisted of three major components: (1) a machine vision system that can identify and localize the apple flower clusters in tree canopies, (2) a cartesian robotic system with the guidance of a machine vision system to reach target flower clusters, and (3) a flat-shaped spraying nozzle connected with a solenoid valve as a spraying end-effector to deposit chemical thinner to the targeted flower clusters. A set of field tests was conducted to evaluate the performance of the robotic thinning system by comparing it to conventional air-blast and boom-type sprayers. In the test, the flower cluster detection reached a precision of 93.82%. The integrated robotic system used 2.3 L of chemical thinner to finish the chemical thinning for 18 apple trees, followed by the boom sprayer and air blast sprayer with 4.2 and 6.8 L usage, respectively. The robotic system also obtained an average fruit set of 2.4 per cluster after thinning, which was comparable to that of the air blast sprayer. The results showed that the robotic thinning system saved 66.7% and 45.5% of chemicals compared to the air-blast sprayer and boom-typed sprayers, respectively, while achieving a similar fruit set per cluster. The outcomes of the study provided guidance for developing a full-scale robotic chemical thinning system for modern apple orchards. Keywords: Apple orchard, Blossom thinning, Cartesian robot, Chemical thinning, Machine vision.

A Hybrid Routing Algorithm for V2V Communication in VANETs Based on Blocked Q-Learning

It is of great significance to design a stable and reliable routing protocol for Vehicular Ad Hoc Networks (VANETs) that adopt Vehicle to Vehicle (V2V) communications in the face of frequent network topology changes. In this paper, we propose a hybrid routing algorithm, RCRIQ, based on improved Q-learning. For an established cluster structure, the cluster head is used to select the gateway vehicle according to the gateway utility function to expand the communication range of the cluster further. During the link construction stage, an improved Q-learning algorithm is adopted. The corresponding neighbor vehicle is chosen according to the maximum Q value in the neighbor list. The heuristic algorithm selects the next-hop by the maximum heuristic function value when selecting the next-hop neighbor node. The above two strategies are comprehensively evaluated to determine the next hop. This way ensures the optimal selection of the next hop in terms of reachability and other communication parameters. Simulation experiments show that the algorithm proposed in this article has better performance in terms of routing stability, throughput, and communication delay in the urban traffic scene.

Large Integer Decomposition Encryption Algorithm for Computer Network Data Communication Combined with Double BP Neural Network Combination Model

Usually a complete computer network system has the following components: source of signals, signal host, cryptographic regime, attack, and interceptor. It is more vulnerable to attacks during the operation of the system, so the security of the system becomes more important. In this paper, by constructing a dual BP neural network combinatorial model and applying it to the computer data communication large integer decomposition encryption process, the constructed model is used to analyze the security against digital certificates, digital signatures, and the algorithms employed in the communication process of connected computer network.

Fr-ROA: trust-aware routing using fractional remora optimisation algorithm for secure communication in IoT

Fr-ROA: trust-aware routing using fractional remora optimisation algorithm for secure communication in IoT