Transmission Success Rate Research Articles

Quota‐based routing and buffer management with heuristic strategies in opportunistic ad hoc networks

SummaryOpportunistic ad hoc networks (OppNets) are characterized by intermittent and infrastructure‐less connectivity among mobile nodes with limited internode communication and buffer space. Without persistent end‐to‐end routing information, replication‐based routing techniques are often used to distribute duplicate messages in OppNets, which unfortunately leads to enormous costs of transmission, storage, and energy resources. Prior replication‐based routing schemes were mainly based on several premises, for example, the availability of global network knowledge, unlimited bandwidth capacity, and homogeneous contact patterns. In this paper, we propose a quota‐based routing scheme with finite buffer management, named QRBP, regardless of these weak premises. The QRBP scheme comprises two essential functions. First, only a portion of nodes with higher mobility are delegated to carry a certain quota of message replicas and disseminate those messages to nodes with lower mobility. The message traffic can be evenly diverted to relay nodes, which reduces the transmission overhead in the network. Second, nodes can manipulate message scheduling and dropping to improve the successful delivery rate according to heuristic strategies based on several measures of the quota value, remaining time‐to‐live, and contact rate with the destination. Furthermore, our study conducts extensive simulations under both synthetic and real mobility scenarios. In terms of transmission overhead ratio and successful delivery rate, the QRBP scheme performs better than Epidemic, Spray and Wait, and Temporal Closeness and Centrality‐Based (TCCB) routing schemes, as well as common buffer management policies like Drop Oldest, Drop Newest, Drop Random, and Space‐Time Drop.

Research on Optimization of Adaptive Positioning and Routing Algorithm for Industrial Internet of Things Engineering Based on Improved Neural Network

The Internet of Things is one of the key technologies leading the development of modern industry. There is great uncertainty in the industrial production process, which causes great difficulties in the process of node perception and information transmission. Therefore, based on the improved neural network, this study designed the industrial Internet of Things engineering adaptive positioning and routing algorithm optimization methods. Based on the analysis of industrial IoT wireless sensor network node type, on the basis of exploring the advantages of back propagation neural network for the shortcomings of slow convergence speed and so on, we establish a discrete time Markov chain, determine its transition probability and the matrix, through interval differentiate, and calculate the estimate step error correction neural network. Then, training samples are selected to build an adaptive positioning model to obtain the absolute position of engineering nodes. Then, the shortest path constraints are set and independent variables are selected. After establishing the matrix form of the two-layer recursive neural network, the route traffic is updated by calculating the connection weight, so as to complete the routing optimization. The experimental results show that this method has high positioning accuracy and low overhead, and the optimized routing algorithm has a higher transmission success rate.

Dynamic Routing Strategy for Directed Transmissions of High-Valued Contents in NGSO Satellite-Based Internet

Nongeostationary orbit (NGSO) satellite-based Internet is an important part of the future network. One single NGSO satellite has the characteristics of high-speed movement, small coverage area, and short connection time; therefore, the method of multisatellite collaboration is adopted in NGSO satellite-based Internet. Caching is an effective technique to reduce the transmission load and delay, especially for high-value content. However, the traditional caching cannot be applied to the NGSO satellite network directly due to the frequent switching of service satellites. As a result, some high-valued cached data need to be transmitted among satellites, such that an effective routing between the source and destination node needs to be established orderly in the satellite network. This paper proposes a dynamic routing strategy based on multilayer satellite architecture for unicast and multicast scenarios, respectively. For the unicast, a routing strategy based on Q -learning is proposed to optimize bandwidth and delay simultaneously, and the effectiveness is verified by the comparison against the traditional routing strategy. For the multicast, an advanced Q -learning multicast routing algorithm based on spatial directionality is proposed to optimize the overall transmission success rate and resource cost, and the superiority of the proposed routing strategy is verified by simulation results.

A Formal Modeling and Verification Scheme with an RNN-Based Attacker for CAN Communication System Authenticity

To enhance the attack resistance of the Controller Area Network (CAN) system and optimize the communication software design, a comprehensive model that combines a variable attacker with the CAN bus (VACB) is proposed to evaluate the bus communication risk. The VACB model consists of a variable attacker and the CAN bus model. A variable attacker is a visualized generation of the attack traffic based on a recurrent neural network (RNN), which is used to evaluate the anti-attack performance of the CAN bus; the CAN bus model combines the data link layer and the application layer to analyze the anomalies in CAN bus data transmission after the attack message. The simulation results indicate that the transmission accuracy and successful response rate decreased by 1.8% and 4.3% under the constructed variable attacker. The CAN bus’s authenticity was promoted after the developers adopted this model to analyze and optimize the software design. The transmission accuracy and the successful response rate were improved by 2.5% and 5.1%, respectively. Moreover, the model can quantify the risk of potential attacks on the CAN bus, prompting developers to avoid it in early development to reduce the loss caused by system crashes. The comprehensive model can provide theoretical guidance for the timing design of embedded software.

Investigation into the Reliability and Encryption Performance of Wireless Signal Transmission by Network Coding Combined with Blockchain in Natural Disaster Scenarios

To enhance the reliability and encryption of unmanned aerial vehicle (UAV) wireless signals in natural disaster scenarios, firstly, the present work analyzes the current wireless signal transmission mode of UAV. In addition, it discusses the efficient network coding of wireless signal transmission model and blockchain with strong encryption ability. Secondly, the signal transmission model of network coding is explored. Finally, the network coding wireless signal transmission model is combined with the blockchain wireless signal transmission model to realize efficient and encrypted data transmission. The research results show that the network coding wireless signal transmission model combined with blockchain technology realizes the maximum difference of network coding wireless signal transmission rate of 1.5 Mb/s. The model also encrypts the data in the simulation scenario of natural disasters through blockchain technology. After encryption, the data protection effect of the transmission model is significantly improved and meets the requirements of standard data transmission. Meanwhile, the wireless signal transmission model can reduce the resource occupation rate in the process of data transmission and improve the success rate and universality of data transmission in natural disaster scenarios. The probability of data being successfully protected in disaster is more than 90%. The results provide technical support for the stable transmission of wireless signals in natural disaster scenarios and provide a reference for improving the reliability and encryption of wireless signal transmission.

The Interactive Design of Library Information Sharing in View of Network Communication Technology

From the perspective of data viewing, interactive design is to present abstract information and data in a visual form through a computer interface. It is formulated based on a humanized and flexible human-computer interaction model. The interaction process between computers and humans requires careful thinking and design. It must follow the principle of “user first, machine second.” Understanding the audience’s psychology and behavior characteristics can effectively enhance computer vision interaction and expand the scope of the audience. The research in this study aimed at the interactive design of library information sharing based on network communication technology. It introduces the organizational structure of the library and analyzes in detail the problems that the current library information resource sharing still faces. Then, this study proposes a dynamic differentiated service mechanism of DDSM to improve the success rate of information transmission in the interactive design system. This study designs an experiment on the interactive design of library information sharing by multiple types of users. The results of the experiment show that students of all grades and teachers use the library and library websites more frequently. For the interactive information service of the library, users are most satisfied with the project attitude of the book recommendation service method. Its satisfaction rate reaches 68%, and it is also the most popular among users. The main purpose of the interaction between library users is to share knowledge. However, the current domestic academic libraries have a general sense of interactive information services, and the development speed has always been slower than that in foreign countries.

DESIGN OF WIRELESS SENSOR NETWORK USING STATISTICAL FRACTAL MEASUREMENTS

To further expand the application range of fractal theory and promote the application of sensors in the era of intelligent interconnection, we design a wireless sensor network (WSN) using statistical fractal measurements in simulation. Fractal features and network complexity of the WSN are analyzed. Besides, the related influencing factors of the WSN transmission success rate are explored. When the box size is smaller than 100, the relationship between the box size and the number of boxes tends to be a straight line, the relationship between them is more stable when the number of nodes increases gradually. Moreover, the degree distribution of nodes presents more obvious symmetry with the increase of network nodes. The simulation results of the network transmission success rate show that under certain other conditions, with the increase of node hops, the network transmission success rate can be promoted significantly. When the transmission failure probability [Formula: see text] is 0.1 and hop count is 6, the transmission success rate can reach more than 90%. This exploration can provide a scientific and effective reference for the follow-up research of the fractal theory.

Low power optimization method for contactless micro intelligent voltage sensor communication network

Aiming at the problems of high power consumption and low success rate in contactless micro voltage sensor communication network, a low power consumption optimization method of contactless micro voltage sensor communication network is proposed. By calculating the average power consumption of micro voltage sensor nodes in the communication network area, the energy balance degree of micro voltage sensor nodes is obtained. When the micro voltage sensor nodes meet the sleep probability of communication network area coverage factor, the power consumption of voltage sensor communication network is calculated. By defining the information entropy of communication network data set, the conditional entropy of data feature classification of communication network is obtained, and the high-power data is eliminated by using the validity kernel function of data features. Combined with the low-power optimization algorithm of micro voltage sensor communication network, the low-power optimization of micro voltage sensor communication network is realized. The experimental results show that the optimization method in this paper can not only reduce the power consumption of data transmission in contactless micro voltage sensor communication network, but also improve the success rate of data transmission, and has better optimization effect.

A Stochastic Geometry Analysis for Energy-Harvesting-Based Device-to-Device Communication

The rapidly developing energy harvesting (EH) technology is a promising solution to the durability issue in the battery-powered Internet of Things (IoT) systems. In this article, underlaid device-to-device (D2D) transmission powered by radio signals harvested from cellular systems is studied. By considering the dilemmas among EH, D2D transmission opportunity, and interference management, we propose two transmission policies: 1) Policy 1 requires that the available power in the battery should be no less than the D2D transmission power and 2) Policy 2 not only sets the constraint on available power but also introduces the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">guard zone</i> rule to protect D2D transmissions from severe interference. The employment of a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">guard zone</i> in this situation is technically challenging since the original distribution of energy arrival will thereby be changed. We derive expressions in closed or semiclosed forms for the considered D2D transmission performance metrics with the stochastic geometry framework and Poisson hole process. With numerical simulation results, the influences of varying network parameters on D2D performances are illustrated. The results show that by introducing a guard zone, the D2D successful transmission rate can be increased by 41.2%. All the developed D2D frameworks and the summarized useful remarks are used to provide meaningful design insights and guidelines for the deployment strategies of EH-based D2D wireless networks.

An Intelligent Anti-Jamming Mechanism against Rule-based Jammer in Cognitive Radio Network

Cognitive Radio Network (CRN) has become a promising technology to overcome the problem of insufficient spectrum utilization. However, the CRN is susceptible to the well-known jamming attack, which reduces its spectrum utilization efficiency. Existing jamming identification schemes and their countermeasure typically require prior statistical information about the communication channel and jamming pattern. This is quite an impractical assumption in the real context. The prime research problem is that the existing schemes are mainly associated with higher computational costs and communication overhead. Hence, the proposed manuscript presents a non-device-centric and efficient anti-jamming mechanism in the form of higher spectrum utilization driven by reinforcement learning techniques to address this above-stated problem. The proposed anti-jamming mechanism is modeled in two phases of implementation. First, the design of the customized environment is introduced as a single wideband cognitive-communication channel where a jammer signal sweeps transversely in the entire band of interest. Secondly, an intelligent agent is designed based on a model-free off-policy algorithm that operates over the same spectrum band. The agent uses its frequency-band knowledge discovery capability to learn frequency band selection and preference strategies to detect and avoid jamming signals, maximizing its successful transmission rate. The simulation results show that the proposed anti-jamming mechanism can effectively eliminate interference and is efficient in power usage and Signal to Noise Ratio (SNR) compared to other existing advanced algorithms.

Comparison of different grafting methods on the effect of '&lt;i&gt;Candidatus&lt;/i&gt; Liberibacter asiaticus' transmission

Grafting is a commonly used method for citrus propagation and transmitting "<italic>Candidatus</italic> Liberibacter asiaticus" (CLas), the putative causing agent of citrus Huanglongbing (HLB). Optimization of the grafting inoculation methods facilitates the material preparation in HLB research. Citrus buds with CLas were grafted onto healthy sour tangerine (<italic>Citrus</italic>. <italic>sunki</italic> Hort. ex Tanaka) seedlings by different methods such as top grafting ("T" grafting and "V" grafting) and side grafting (abdominal grafting). Along with the symptom observation, titers of CLas in the leaves were detected by RT-qPCR monthly. The correlation between the growth status of buds or different grafting methods and the success rate of HLB transmission were analyzed. Our results suggest that sufficient DNA could be extracted to accurately detect the CLas from even only 0.0125 g leaf midrib or branch bark. The probability of CLas transmission was higher in plants inoculated with buds in better growth conditions. The success rate of "T" grafting was significantly higher than that of side grafting and "V" grafting. Additionally, in terms of HLB transmission efficiency, the two-bud grafting scheme was superior to the single-bud and three-bud grafting schemes. Conclutionly, the grafting combinations with the highest HLB transmission efficiency were screened to provide a methodological reference for the practice or research of grafting to obtain plant material.

Stochastic Modeling and Convergence Analysis of Internet Routers

The existent route convergence models are mainly deterministic ones, and various phenomena, such as packet losses, link noises, and sudden changes in interconnecting topology will occur in the route convergence process. Aimed at these random problems, a new stochastic dynamic system model was proposed by means of the Bernoulli white sequence distribution, the Wiener process and the Markov process. Based on the stochastic differential equation theory and the stochastic analysis methods, the sufficient conditions for the route convergence were given. The results prove that, the convergence of the routing state in a random environment is closely related to the Laplacian matrix of the router connection topology, the smooth distribution of the Markov switching, the successful transmission rate of the data packets, and the noise intensity in the network. Finally, a numerical example illustrates the effectiveness of the results.

Community Clustering Routing Algorithm Based on Information Entropy in Mobile Opportunity Network

Aiming at the difficulty of traditional routing clustering algorithms to deal with the different characteristics between communities and the inefficient nodes after community clustering, this paper proposes a Community clustering Routing protocol based on information Entropy in mobile opportunity Networks(CREN). The proposed protocol uses the K-Modes algorithm with unsupervised learning, combined with the pre-selected initial clustering center node to divide the network nodes into the initial clustering community. Then, the communities with similar characteristics are clustered and merged according to the change of information entropy. At the end, a number of different types of communities are formed in the network, and the nodes in the community have a high degree of similarity, which improves the efficiency of message forwarding. At the same time, in order to eliminate the inefficient nodes in the community, based on the information entropy and the social attributes of the nodes, this paper proposes a mechanism for dynamically updating the community to ensure the efficiency of the nodes in the community. The simulation results show that the transmission success rate of this algorithm is better than other classic routing algorithms, meanwhile, it also has lower transmission delay and routing overhead.

Machine Learning Enables Radio Resource Allocation in the Downlink of Ultra-Low Latency Vehicular Networks

Autonomous driving and intelligent transportation demand ultra-low latency and high reliability communication in future vehicular networks. Proactive wireless communication can facilitate minimal latency by open-loop communication, which discards traditional feedback control mechanisms. However, appropriate radio resource allocation in such proactive mobile networks has not been fully studied due to lacking channel state information (CSI) and the alleviation of multiple access interference (MAI) in multiple virtual cells. This paper aims to ensure the reliability of downlink communication by a novel radio resource allocation scheme in proactive vehicular networks with ultra-low latency. We regard data transmission success rate as the reliability indicator and propose a joint radio resource allocation model based on the “generalized closed-loop”, where anchor node (AN) uses the radio resource utilization information (RRUI) from the vehicle in the immediate past uplink as a guide to assist resource allocation. Subsequently, we study the radio resource allocation model solution on the vehicle side and the network side respectively. On the vehicle side, vehicles use the local or global data transmission experience to select the radio resource with the best quality as the RRUI. On the network side, according to the latest RRUI of vehicle and resource occupancy information, deep reinforcement learning is proposed to make appropriate radio resource allocation decisions. Simulations demonstrate the effectiveness of the intelligent joint radio resource allocation scheme under the cooperation between vehicles and AN. When the resource load rate reaches 40%, the joint radio resource allocation scheme can achieve a data transmission success rate of more than 98%.

A novel gateway node reconfiguration method of IOT based on hierarchical coding particle swarm optimization

In order to overcome the problems of low channel utilization, low transmission success rate and high data transmission delay in current gateway node reconfiguration methods of IOT, this paper proposes a novel gateway node reconfiguration method of IOT based on hierarchical coding particle swarm optimization. Based on the IOT network model, this paper analyzes the delay characteristics of the IOT, and constructs the object function of the gateway node reconfiguration of IOT. By monotone decreasing inertia weight strategy, the coding particle swarm optimization is optimized, and the reconfiguration objective function of the gateway node of IOT by using the optimized particle swarm optimization algorithm is solved. Experimental results show that the channel utilization ratio of the proposed method is higher than 90%, the success rate of information transmission is more than 80%, and the data transmission delay is less than 0.5 s, which indicates that the proposed method has high channel utilization, high transmission success rate and low data transmission delay.

Environmental Perception Q-Learning to Prolong the Lifetime of Poultry Farm Monitoring Networks

The reduction of the effects of heat-stress phenomena on poultry health and energy conservation of poultry farm monitoring networks are highly related problems. To address these problems, we propose environmental perception Q-learning (EPQL) to prolong the lifetime of poultry farm monitoring networks. EPQL consists of an environmental-perception module and Q-learning. According to the temperature and humidity model of heat stress, an environmental-perception module determines the transmission rate, while Q-learning adjusts the transmission rate according to the success rate of packet transmission and the remaining energy. In real-world tests, our poultry farm monitoring networks used only about 8% of energy in a month. The real-time information of these monitoring networks was available on smartphones. In laboratory tests, compared with CSMA/CA (23.67 days), S-MAC (109.37 days), and T-MAC (252.79 days) under real systems with 2000 mAh battery, the battery-life performance of EPQL (436.48 days) was better. Moreover, EPQL reduces the packet loss rate by about 60% while simultaneously decreasing the average delay by about 20%. Generally, based on the framework of EPQL, the implemented temperature and humidity model of heat stress for poultry could be replaced by other models to extend its applicability range.

Wireless Network of Silver Film Lysozyme Aptasensor Based on Fractal Measurement

In this work, we reported a wireless network composed of silver film-based graphene oxide-fluorescence resonance energy transfer (GO-FRET) lysozyme aptasensor nodes. At the sensor node level, we optimized silver substrate structure, concentrations of the aptamers, and graphene oxide and tested lysozyme detection performance with a model analyte. At the network level, we analyzed the complexity and transmission success rate using fractal measurements. We implemented the wireless network composed of the aptasensor with a portable Wi-Fi fluorescent reader. Transmission success rate testing results show that an increase in node hops can promote the rate of transmission success dramatically. When the hop count is larger than 6, the rate of transmission success can reach more than 90% if the transmission failure probability and sleep probability are 0.1 and 0.5, respectively.

PORTABLE AVIATION NAVIGATION CALIBRATION SYSTEM BASED ON RASPBERRY PI, HACK RF ONE, AND SOFTWARE DEFINED RADIO COMMUNICATION SYSTEM

Calibration procedures for the aviation navigation system which involve full size aircraft and its crew may be considered risky and high cost . This paper introduces the state of the art communication system to provide lower cost and flexible solutions based on Raspberry Pi, and SDR device Hack RF One, equipped with proper and aviation-related sensors, which later may be treated as unmanned aerial vehicle payload to replace flying aircraft aviation instruments. Design principles which mainly consist of both flexible communication and operating feasibility are explained in early of this paper. As a preliminary method, simple FSK modulation coupled with data integrity mechanisms are implemented to realize reliable but fast sensor data transmission. Data communication rate under a single board computer environment may achieve 40 kbps. Proposed system achieved a data transmission success rate as high as 88% in reasonable condition. In addition, the discussion of further system development is presented.

Design of Sports Training System and Motion Monitoring and Recognition under Wireless Sensor Network

In conventional sports training, coaches record and observe athletes' sports data and judge whether it is reasonable based on their own experience. This qualitative analysis method is highly subjective, has large errors, and is susceptible to interference. To solve the above problems, the design of the sports training system under the wireless sensor network and the research of movement monitoring and recognition become very important. This article aims to study the design of sports training system and the monitoring and recognition of actions under the wireless sensor network technology. This paper simulates the implementation of the proposed data collection protocol and the two basic protocols, the direct transfer algorithm and the flooding algorithm, and compares the protocol proposed in this paper with the other two algorithms in terms of average information transmission success rate and average network overhead. Among them, the average information transmission success rate represents the ratio of the number of messages successfully arriving at the base station to the total amount of information generated by all nodes, and the average network overhead represents the average number of messages sent by each node. Experimental results show that the data collection protocol proposed in this paper can dynamically provide different transmission qualities for information of different importance levels, effectively reducing network overhead, and the reduced overhead is 11% of the original.

Distributed robust H∞ adaptive fault-tolerant control of amorphous and flat air-to-ground wireless self-organizing network system

PurposeThe paper takes the air-ground integrated wireless ad hoc network-integrated system as the research object, this paper aims to propose a distributed robust H∞ adaptive fault-tolerant control algorithm suitable for the system to distribute to solve the problem of control and communication failure at the same time.Design/methodology/approachIn the paper, the authors propose a distributed robust H∞ adaptive fault-tolerant control algorithm suitable for the air-ground integrated wireless ad hoc network-integrated system.FindingsThe results show that the integrated system has good robustness and fault tolerance performance indicators for flight control and wireless signal transmission when confronted with external disturbances, internal actuator failures and wireless network associated failures and the flight control curve of the quadrotor unmanned aerial vehicle (UAV) is generally smooth and stable, even if it encounters external disturbances and actuator failures, its fault tolerance performance is very good. Then in the range of 400–800 m wireless communication distance, the success rate of wireless signal loop transmission is stable at 80%–100% and the performance is at least relatively improved by 158.823%.Originality/valueThis paper takes the air-ground integrated wireless ad hoc network-integrated system as the research object, based on the robust fault-tolerant control algorithm, the authors propose a distributed robust H∞ adaptive fault-tolerant control algorithm suitable for the system and through the Riccati equation and linear matrix inequation method, the designed distributed robust H∞ adaptive fault-tolerant controller further optimizes the fault suppression factor γ, so as to break through the limitation of only one Lyapunov matrix for different fault modes to distribute to solve the problem of control and communication failure at the same time.