Reliable Data Collection Model and Transmission Framework in Large-Scale Wireless Medical Sensor Networks

Large-scale wireless sensor networks(WSNs)play a critical role in monitoring dangerous scenarios and responding to medical emergencies.However,the inherent instability and error-prone nature of wireless links present significant challenges,necessitating efficient data collection and reliable transmission services.This paper addresses the limitations of existing data transmission and recovery protocols by proposing a systematic end-to-end design tailored for medical event-driven cluster-based large-scale WSNs.The primary goal is to enhance the reliability of data collection and transmission services,ensuring a comprehensive and practical approach.Our approach focuses on refining the hop-count-based routing scheme to achieve fairness in forwarding reliability.Additionally,it emphasizes reliable data collection within clusters and establishes robust data transmission over multiple hops.These systematic improvements are designed to optimize the overall performance of the WSN in real-world scenarios.Simulation results of the proposed protocol validate its exceptional performance compared to other prominent data transmission schemes.The evaluation spans varying sensor densities,wireless channel conditions,and packet transmission rates,showcasing the protocol’s superiority in ensuring reliable and efficient data transfer.Our systematic end-to-end design successfully addresses the challenges posed by the instability of wireless links in large-scaleWSNs.By prioritizing fairness,reliability,and efficiency,the proposed protocol demonstrates its efficacy in enhancing data collection and transmission services,thereby offering a valuable contribution to the field of medical event-drivenWSNs.

Research on Total Electric Field PredictionMethod of Ultra-High Voltage Direct Current Transmission Line Based on Stacking Algorithm

Ultra-high voltage(UHV)transmission lines are an important part of China’s power grid and are often surrounded by a complex electromagnetic environment.The ground total electric field is considered a main electromagnetic environment indicator of UHV transmission lines and is currently employed for reliable long-term operation of the power grid.Yet,the accurate prediction of the ground total electric field remains a technical challenge.In this work,we collected the total electric field data from the Ningdong-Zhejiang±800 kV UHVDC transmission project,as of the Ling Shao line,and perform an outlier analysis of the total electric field data.We show that the Local Outlier Factor(LOF)elimination algorithm has a small average difference and overcomes the performance of Density-Based Spatial Clustering of Applications with Noise(DBSCAN)and Isolated Forest elimination algorithms.Moreover,the Stacking algorithm has been found to have superior prediction accuracy than a variety of similar prediction algorithms,including the traditional finite element.The low prediction error of the Stacking algorithm highlights the superior ability to accurately forecast the ground total electric field of UHVDC transmission lines.

Development and prospect of downhole monitoring and data transmission technology for separated zone water injection

This article outlines the development of downhole monitoring and data transmission technology for separated zone water injection in China.According to the development stages,the principles,operation processes,adaptability and application status of traditional downhole data acquisition method,cable communications and testing technology,cable-controlled downhole parameter real-time monitoring communication method and downhole wireless communication technology are introduced in detail.Problems and challenges of existing technologies in downhole monitoring and data transmission technology are pointed out.According to the production requirement,the future development direction of the downhole monitoring and data transmission technology for separated zone water injection is proposed.For the large number of wells adopting cable measuring and adjustment technology,the key is to realize the digitalization of downhole plug.For the key monitoring wells,cable-controlled communication technology needs to be improved,and downhole monitoring and data transmission technology based on composite coiled tubing needs to be developed to make the operation more convenient and reliable.For large-scale application in oil fields,downhole wireless communication technology should be developed to realize automation of measurement and adjustment.In line with ground mobile communication network,a digital communication network covering the control center,water distribution station and oil reservoir should be built quickly to provide technical support for the digitization of reservoir development.

Secure and Efficient Data Transmission Scheme Based on Physical Mechanism

Many Internet of things application scenarios have the characteristics of limited hardware resources and limited energy supply,which are not suitable for traditional security technology.The security technology based on the physicalmechanism has attracted extensive attention.How to improve the key generation rate has always been one of the urgent problems to be solved in the security technology based on the physical mechanism.In this paper,superlattice technology is introduced to the security field of Internet of things,and a high-speed symmetric key generation scheme based on superlattice for Internet of things is proposed.In order to ensure the efficiency and privacy of data transmission,we also combine the superlattice symmetric key and compressive sensing technology to build a lightweight data transmission scheme that supports data compression and data encryption at the same time.Theoretical analysis and experimental evaluation results show that the proposed scheme is superior to the most closely related work.

Autonomous UAV 3D trajectory optimization and transmission scheduling for sensor data collection on uneven terrains

This paper considers a time-constrained data collection problem from a network of ground sensors located on uneven terrain by an Unmanned Aerial Vehicle(UAV),a typical Unmanned Aerial System(UAS).The ground sensors harvest renewable energy and are equipped with batteries and data buffers.The ground sensor model takes into account sensor data buffer and battery limitations.An asymptotically globally optimal method of joint UAV 3D trajectory optimization and data transmission schedule is developed.The developed method maximizes the amount of data transmitted to the UAV without losses and too long delays and minimizes the propulsion energy of the UAV.The developed algorithm of optimal trajectory optimization and transmission scheduling is based on dynamic programming.Computer simulations demonstrate the effectiveness of the proposed algorithm.

Data Aggregation-based Transmission Method in Ultra-Dense Wireless Networks

As the Internet of Things(IoT)advances,machine-type devices are densely deployed and massive networks such as ultra-dense networks(UDNs)are formed.Various devices attend to the network to transmit data using machine-type communication(MTC),whereby numerous,various are generated.MTC devices generally have resource constraints and use wireless communication.In this kind of network,data aggregation is a key function to provide transmission efficiency.It can reduce the number of transmitted data in the network,and this leads to energy saving and reducing transmission delays.In order to effectively operate data aggregation in UDNs,it is important to select an aggregation point well.The total number of transmitted data may vary,depending on the aggregation point to which the data are delivered.Therefore,in this paper,we propose a novel data aggregation scheme to select the appropriate aggregation point and describe the data transmission method applying the proposed aggregation scheme.In addition,we evaluate the proposed scheme with extensive computer simulations.Better performances in the proposed scheme are achieved compared to the conventional approach.

Data secure transmission intelligent prediction algorithm for mobile industrial IoT networks

Mobile Industrial Internet of Things(IIoT)applications have achieved the explosive growth in recent years.The mobile IIoT has flourished and become the backbone of the industry,laying a solid foundation for the interconnection of all things.The variety of application scenarios has brought serious challenges to mobile IIoT networks,which face complex and changeable communication environments.Ensuring data secure transmission is critical for mobile IIoT networks.This paper investigates the data secure transmission performance prediction of mobile IIoT networks.To cut down computational complexity,we propose a data secure transmission scheme employing Transmit Antenna Selection(TAS).The novel secrecy performance expressions are first derived.Then,to realize real-time secrecy analysis,we design an improved Convolutional Neural Network(CNN)model,and propose an intelligent data secure transmission performance prediction algorithm.For mobile signals,the important features may be removed by the pooling layers.This will lead to negative effects on the secrecy performance prediction.A novel nine-layer improved CNN model is designed.Out of the input and output layers,it removes the pooling layer and contains six convolution layers.Elman,Back-Propagation(BP)and LeNet methods are employed to compare with the proposed algorithm.Through simulation analysis,good prediction accuracy is achieved by the CNN algorithm.The prediction accuracy obtains a 59%increase.

A Novel Secure Data Transmission Scheme in Industrial Internet of Things

The industrial Internet of Things(IoT)is a trend of factory development and a basic condition of intelligent factory.It is very important to ensure the security of data transmission in industrial IoT.Applying a new chaotic secure communication scheme to address the security problem of data transmission is the main contribution of this paper.The scheme is proposed and studied based on the synchronization of different-structure fractional-order chaotic systems with different order.The Lyapunov stability theory is used to prove the synchronization between the fractional-order drive system and the response system.The encryption and decryption process of the main data signals is implemented by using the n-shift encryption principle.We calculate and analyze the key space of the scheme.Numerical simulations are introduced to show the effectiveness of theoretical approach we proposed.

L2-LBMT:A Layered Load Balance Routing Protocol for Underwater Multimedia Data Transmission

Providing highly efficient underwater transmission of mass multimedia data is challenging due to the particularities of the underwater environment. Although there are many schemes proposed to optimize the underwater acoustic network communication protocols, from physical layer, data link layer, network layer to transport layer, the existing routing protocols for underwater wireless sensor network(UWSN) still cannot well deal with the problems in transmitting multimedia data because of the difficulties involved in high energy consumption, low transmission reliability or high transmission delay. It prevents us from applying underwater multimedia data to real-time monitoring of marine environment in practical application, especially in emergency search, rescue operation and military field. Therefore, the inefficient transmission of marine multimedia data has become a serious problem that needs to be solved urgently. In this paper, A Layered Load Balance Routing Protocol(L2-LBMT) is proposed for underwater multimedia data transmission. In L2-LBMT, we use layered and load-balance Ad Hoc Network to transmit data, and adopt segmented data reliable transfer(SDRT) protocol to improve the data transport reliability. And a 3-node variant of tornado(3-VT) code is also combined with the Ad Hoc Network to transmit little emergency data more quickly. The simulation results show that the proposed protocol can balance energy consumption of each node, effectively prolong the network lifetime and reduce transmission delay of marine multimedia data.

Blockchain-based data transmission control for Tactical Data Link

Tactical Data Link(TDL)is a communication system that utilizes a particular message format and a protocol to transmit data via wireless channels in an instant,automatic,and secure way.So far,TDL has shown its excellence in military applications.Current TDL adopts a distributed architecture to enhance anti-destruction capacity.However,It still faces a problem of data inconsistency and thus cannot well support cooperation across multiple militarily domains.To tackle this problem,we propose to leverage blockchain to build an automatic and adaptive data transmission control scheme for TDL.It achieves automatic data transmission and realizes information consistency among different TDL entities.Besides,applying smart contracts based on blockchain further enables adjusting data transmission policies automatically.Security analysis and experimental results based on simulations illustrate the effectiveness and efficiency of our proposed scheme.

Power Line Monitoring Data Transmission Using Wireless Sensor Network

The WSN used in power line monitoring is long chain structure, and the bottleneck near the Sink node is more obvious. In view of this, A Sink nodes’ cooperation mechanism is presented. The Sink nodes from different WSNs are adjacently deployed. Adopting multimode and spatial multiplexing network technology, the network is constructed into multi-mode-level to achieve different levels of data streaming. The network loads are shunted and the network resources are rationally utilized. Through the multi-sink nodes cooperation, the bottlenecks at the Sink node and its near several jump nodes are solved and process the competition of communication between nodes by channel adjustment. Finally, the paper analyzed the method and provided simulation experiment results. Simulation results show that the method can solve the funnel effect of the sink node, and get a good QoS.

Enhanced Data Transmission Rate of XCTD Profiler Based on OFDM

An expendable conductivity-temperature-depth profiler(XCTD)is one of the most important instruments used to obtain hydrological data,such as temperature and conductivity,and detect ocean depth in a large area.However,the XCTD channel provides poor time-varying performance,narrowband,and low signal-to-noise ratio(SNR),which severely restricts the data transmission rate.In contrast to conventional single-carrier modulation techniques,such as amplitude-shift keying and differential phase-shift keying,this article provides a new method,based on orthogonal frequency division multiplexing(OFDM)to enhance the data transmission rate of deep-sea abandoned profilers.We apply the OFDM to enhance the SNR of the XCTD,which is achieved by reducing the data transmission rate of each sub-channel.Moreover,the bandwidth utilization may be improved by increasing the number of subcarriers in a given bandwidth,which enhances the data transmission rate.Based on analysis of the XCTD channel model,OFDM with different parameters such as constellation mapping,number of subcarriers,subcarrier spacing,signal period and cyclic prefix are achieved.To verify the effectiveness of the OFDM,this study investigates the influence of different parameters on the data transmission rate at different noise levels,i.e.,-20 dB and-40 d B.

Fast Web - Based Data Transmission

Since web based GIS processes large size spatial geographic information on internet, we should try to improve the efficiency of spatial data query processing and transmission. This paper presents two efficient methods for this purpose: division transmission and progressive transmission methods. In division transmission method, a map can be divided into several parts, called “tiles”, and only tiles can be transmitted at the request of a client. In progressive transmission method, a map can be split into several phase views based on the significance of vertices, and a server produces a target object and then transmits it progressively when this spatial object is requested from a client. In order to achieve these methods, the algorithms, “tile division”, “priority order estimation” and the strategies for data transmission are proposed in this paper, respectively. Compared with such traditional methods as “map total transmission” and “layer transmission”, the web based GIS data transmission, proposed in this paper, is advantageous in the increase of the data transmission efficiency by a great margin.

A method for rapid transmission of multi-scale vector river data via the Internet

Due to the conflict between huge amount of map data and limited network bandwidth, rapid trans- mission of vector map data over the Internet has become a bottleneck of spatial data delivery in web-based environment. This paper proposed an approach to organizing and transmitting multi-scale vector river network data via the Internet progressively. This approach takes account of two levels of importance, i.e. the importance of river branches and the importance of the points belonging to each river branch, and forms data packages ac- cording to these. Our experiments have shown that the proposed approach can reduce 90% of original data while preserving the river structure well.

Simulation analysis of a method to improve data-transmission performance of Nanshan 26 m Radio Telescope based on Software-Defined Networks

Data Center of Xinjiang Astronomical Observatory(XAO-DC)commenced operating in 2015,and provides services including archiving,releasing and retrieving precious astronomical data collected by the Nanshan 26 m Radio Telescope(NSRT)over the years,and realises the open sharing of astronomical observation data.The observation data from NSRT are transmitted to XAO-DC 100 km away through dedicated fiber for long-term storage.With the continuous increase of data,the static architecture of the current network cannot meet NSRT data-transmission requirements due to limited network bandwidth.To get high-speed data-transmission using the existing static network architecture,a method for reconstruction data-transmission network using Software-Defined Networks(SDN)is proposed.Benefit from the SDN’s data and control plane separation,and open programmable,combined with the Mininet simulation platform for experiments,the TCP throughput(of single thread)was improved by~24.7%,the TCP throughput(of multi threads)was improved by~9.8%,~40.9%,~35.5%and~11.7%.Compared with the current network architecture,the Latency was reduced by~63.2%.

A new method for improving the inductively coupled data transmission rate of mooring buoy based on carrier signal frequency selection

In the inductively coupled data transmission system of the mooring buoy, the carrier signal frequency of the transmission channel is limited due to the inherent characteristics of the system, resulting in limited channel bandwidth. The limited channel bandwidth limits the increase in inductively coupled data transmission rate.In order to improve the inductively coupled data transmission rate of mooring buoy as much as possible without damaging the data transmission performance, a new method was proposed in this paper. The method is proposed to improve the data transmission rate by selecting the appropriate carrier signal frequencies based on the principle of maximizing the amplitude value of amplitude-frequency characteristic curve of the system. Research has been done according to this method as follows. Firstly, according to the inductively coupled transmission mooring buoy structure, the inductively coupled data transmission circuit model was established. The binary frequency shift keying(2FSK) digital signal modulation mode was selected. Through theoretical analysis, the relation between the carrier signal frequency and the data transmission performance, the relation between the carrier signal frequency and the 2FSK signal bandwidth were obtained. Secondly, the performance and the bandwidth of the signal transmission were studied for the inherent characteristics of the actual inductively coupled data transmission system. The amplitude-frequency characteristic of the system was analyzed by experiments. By selecting the appropriate carrier signal frequency parameters, an excellent data transmission performance was guaranteed and a large 2FSK signal bandwidth was obtained. Finally, an inductively coupled data transmission rate optimization experiment and a bit error rate analysis experiment were designed and carried out. The results show that the high-speed and reliable data transmission of the system was realized and the rate can reach 100 kbps.

Channel Estimation and Data Transmission in Massive MIMO TDD Systems

This paper mainly elaborates the studies of channel estimation and downlink data transmission in Massive MIMO. As there are different types of interference in single-cell and multi-cell systems, this paper establishes different models for them separately. In terms of uplink training, for getting channel state information, we introduce LS and MMSE channel estimation algorithms and make a comparison between them. At the same time, the problem of pilot contamination is solved by cell classification and pilot identification. Next, this paper defines mathematical models for downlink data transmission. We use pre-coding methods (including Zero-forcing and Maximal Ratio Combining schemes) and optimize power distribution to improve channel capacity and transmission rate. Furthermore, this paper provides numerical results to show the simulation performance in both single-cell and multi-cell systems and extends to prospects in the future.

Dynamic Encryption and Secure Transmission of Terminal Data Files

Data is the last defense line of security,in order to prevent data loss,no matter where the data is stored,copied or transmitted,it is necessary to accurately detect the data type,and further clarify the form and encryption structure of the data transmission process to ensure the accuracy of the data,so as to prevent data leakage,take the data characteristics as the core,use transparent encryption and decryption technology as the leading,and According to the data element characteristics such as identity authentication,authority management,outgoing management,file audit and external device management,the terminal data is marked with attributes to form a data leakage prevention module with data function,so as to control the data in the whole life cycle from creation,storage,transmission,use to destruction,no matter whether the data is stored in the server,PC or mobile device,provide unified policy management,form ecological data chain with vital characteristics,and provide comprehensive protection system for file dynamic encryption transmission,such as prevention in advance,control in the event,and audit after the event,so as to ensure the security of dynamic encryption in the process of file transmission,ensure the core data of the file,and help the enterprise keep away from the risk of data leakage.

Distributed Asynchronous Learning for Multipath Data Transmission Based on P-DDQN

Adaptive packet scheduling can efficiently enhance the performance of multipath Data Transmission.However,realizing precise packet scheduling is challenging due to the nature of high dynamics and unpredictability of network link states.To this end,this paper proposes a distributed asynchronous deep reinforcement learning framework to intensify the dynamics and prediction of adaptive packet scheduling.Our framework contains two parts:local asynchronous packet scheduling and distributed cooperative control center.In local asynchronous packet scheduling,an asynchronous prioritized replay double deep Q-learning packets scheduling algorithm is proposed for dynamic adaptive packet scheduling learning,which makes a combination of prioritized replay double deep Q-learning network(P-DDQN)to make the fitting analysis.In distributed cooperative control center,a distributed scheduling learning and neural fitting acceleration algorithm to adaptively update neural network parameters of P-DDQN for more precise packet scheduling.Experimental results show that our solution has a better performance than Random weight algorithm and Round-Robin algorithm in throughput and loss ratio.Further,our solution has 1.32 times and 1.54 times better than Random weight algorithm and Round-Robin algorithm on the stability of multipath data transmission,respectively.

Real-time performance of periodic data transmission in EPA industrial Ethernet

To evaluate and improve the real-time performance of Ethernet for plant automation（EPA） industrial Ethernet,the real-time performance of EPA periodic data transmission was theoretically and experimentally studied.By analyzing information transmission regularity and EPA deterministic scheduling mechanism,periodic messages were categorized as different modes according to their entering-queue time.The scheduling characteristics and delivery time of each mode and their interacting relations were studied,during which the models of real-time performance of periodic information transmission in EPA system were established.On this basis,an experimental platform is developed to test the delivery time of periodic messages transmission in EPA system.According to the analysis and the experiment,the main factors that limit the real-time performance of EPA periodic data transmission and the improvement methods were proposed.