A Method of Catchments Health Assessment under Value-pressure Model and Its Application in Urbanized River Network Area:A Case Study in Shanghai,China

Catchments health assessment is fundamental to effective catchments management. Generally, an assessment method should be selected to reflect both the purpose of assessment and local characteristics. A trial in Shanghai was conducted to test the method for catchments health assessment in urbanized fiver network area. Seven indicators that described four dimensions of river, river network, land use and function, and local feature were used to assess catchments values; while possible change rate of urbanization and industrialization in the next 3 years were chosen for catchments pressure assessment in the value-pressure model. Factors related to catchments classification, indicators measurement and protection priority have been considered in the development strategies for catchments health management. The results showed that value-pressure assessment was applicable in urbanized catchments health management, particularly when both human and catchments had multiple demands. As a result of over 30-year rapid urbanization, more than 70% of Shanghai fiver network area was still in a healthy condition with high catchments values, among them, 39.3% was under high pressure. Poor water quality, simplified river system and weakened local feature of fiver pattern had largely affected catchments health in Shanghai. Lack of long-term monitoring data would seriously restrict the development and validity of catchments health assessment.

DNBP-CCA:A Novel Approach to Enhancing Heterogeneous Data Traffic and Reliable Data Transmission for Body Area Network

The increased adoption of Internet of Medical Things (IoMT) technologies has resulted in the widespread use ofBody Area Networks (BANs) in medical and non-medical domains. However, the performance of IEEE 802.15.4-based BANs is impacted by challenges related to heterogeneous data traffic requirements among nodes, includingcontention during finite backoff periods, association delays, and traffic channel access through clear channelassessment (CCA) algorithms. These challenges lead to increased packet collisions, queuing delays, retransmissions,and the neglect of critical traffic, thereby hindering performance indicators such as throughput, packet deliveryratio, packet drop rate, and packet delay. Therefore, we propose Dynamic Next Backoff Period and Clear ChannelAssessment (DNBP-CCA) schemes to address these issues. The DNBP-CCA schemes leverage a combination ofthe Dynamic Next Backoff Period (DNBP) scheme and the Dynamic Next Clear Channel Assessment (DNCCA)scheme. The DNBP scheme employs a fuzzy Takagi, Sugeno, and Kang (TSK) model’s inference system toquantitatively analyze backoff exponent, channel clearance, collision ratio, and data rate as input parameters. Onthe other hand, the DNCCA scheme dynamically adapts the CCA process based on requested data transmission tothe coordinator, considering input parameters such as buffer status ratio and acknowledgement ratio. As a result,simulations demonstrate that our proposed schemes are better than some existing representative approaches andenhance data transmission, reduce node collisions, improve average throughput, and packet delivery ratio, anddecrease average packet drop rate and packet delay.

Priority Based Energy Efficient MAC Protocol by Varying Data Ratefor Wireless Body Area Network

Wireless Body Area Network(WBAN)is a cutting-edge technology that is being used in healthcare applications to monitor critical events in the human body.WBAN is a collection of in-body and on-body sensors that monitor human physical parameters such as temperature,blood pressure,pulse rate,oxygen level,body motion,and so on.They sense the data and communicate it to the Body Area Network(BAN)Coordinator.The main challenge for the WBAN is energy consumption.These issues can be addressed by implementing an effective Medium Access Control(MAC)protocol that reduces energy consumption and increases network lifetime.The purpose of the study is to minimize the energy consumption and minimize the delay using IEEE 802.15.4 standard.In our proposed work,if any critical events have occurred the proposed work is to classify and prioritize the data.We gave priority to the highly critical data to get the Guarantee Tine Slots(GTS)in IEEE 802.15.4 standard superframe to achieve greater energy efficiency.The proposed MAC provides higher data rates for critical data based on the history and current condition and also provides the best reliable service to high critical data and critical data by predicting node similarity.As an outcome,we proposed a MAC protocol for Variable Data Rates(MVDR).When compared to existing MAC protocols,the MVDR performed very well with low energy intake,less interruption,and an enhanced packet-sharing ratio.

An Efficient Heterogeneous Ring Signcryption Scheme for Wireless Body Area Networks

Wireless body area networks(WBANs)are an emerging technology for the real-time monitoring of physiological signals.WBANs provide a mechanism for collecting,storing,and transmitting physiological data to healthcare providers.However,the open wireless channel and limited resources of sensors bring security challenges.To ensure physiological data security,this paper provides an efficient Certificateless Public Key Infrastructure Heterogeneous Ring Signcryption(CP-HRSC)scheme,in which sensors are in a certificateless cryptosystem(CLC)environment,and the server is in a public key infrastructure(PKI)environment.CLC could solve the limitations of key escrow in identity-based cryptography(IBC)and certificate management for public keys in PKI.While PKI is suited for the server because it is widely used on the Internet.Furthermore,this paper designs a ring signcryption method that allows the controller to anonymously encrypt physiological data on behalf of a set of sensors,but the server does not exactly know who the sensor is.The construction of this paper can achieve anonymity,confidentiality,authentication,non-repudiation,and integrity in a logically single step.Under the computational Diffie-Hellman(CDH)problem,the formal security proof is provided in the random oracle model(ROM).This paper demonstrates that this scheme has indistinguishability against adaptive chosen ciphertext attacks(IND-CCA2)and existential unforgeability against adaptive chosen message attacks(EUF-CMA).In terms of computational cost and energy usage,a comprehensive performance analysis demonstrates that the proposed scheme is the most effective.Compared to the three existing schemes,the computational cost of this paper’s scheme is reduced by about 49.5%,4.1%,and 8.4%,and the energy usage of our scheme is reduced by about 49.4%,3.7%,and 14.2%,respectively.

Analysis of Mobile and Internet Network Coverage: Propagation of Electromagnetic Waves and Concept of Digital Divide in Burundi

Mobile and Internet network coverage plays an important role in digital transformation and the exploitation of new services. The evolution of mobile networks from the first generation (1G) to the 5th generation is still a long process. 2G networks have developed the messaging service, which complements the already operational voice service. 2G technology has rapidly progressed to the third generation (3G), incorporating multimedia data transmission techniques. It then progressed to fourth generation (4G) and LTE (Long Term Evolution), increasing the transmission speed to improve 3G. Currently, developed countries have already moved to 5G. In developing countries, including Burundi, a member of the East African Community (ECA) where more than 80% are connected to 2G technologies, 40% are connected to the 3G network and 25% to the 4G network and are not yet connected to the 5G network and then still a process. The objective of this article is to analyze the coverage of 2G, 3G and 4G networks in Burundi. This analysis will make it possible to identify possible deficits in order to reduce the digital divide between connected urban areas and remote rural areas. Furthermore, this analysis will draw the attention of decision-makers to the need to deploy networks and coverage to allow the population to access mobile and Internet services and thus enable the digitalization of the population. Finally, this article shows the level of coverage, the digital divide and an overview of the deployment of base stations (BTS) throughout the country to promote the transformation and digital inclusion of services.

A Human Body Posture Recognition Algorithm Based on BP Neural Network for Wireless Body Area Networks

Human body posture recognition has attracted considerable attention in recent years in wireless body area networks(WBAN). In order to precisely recognize human body posture,many recognition algorithms have been proposed.However, the recognition rate is relatively low. In this paper, we apply back propagation(BP) neural network as a classifier to recognizing human body posture, where signals are collected from VG350 acceleration sensor and a posture signal collection system based on WBAN is designed. Human body signal vector magnitude(SVM) and tri-axial acceleration sensor data are used to describe the human body postures. We are able to recognize 4postures: Walk, Run, Squat and Sit. Our posture recognition rate is up to 91.67%. Furthermore, we find an implied relationship between hidden layer neurons and the posture recognition rate. The proposed human body posture recognition algorithm lays the foundation for the subsequent applications.

A novel nest-based scheduling method for mobile wireless body area networks

Wireless Body Area Networks(WBANs)comprise various sensors to monitor and collect various vital signals,such as blood pressure,pulse,heartbeat,body temperature,and blood sugar.A dense and mobile WBAN often suffers from interference,which causes serious problems,such as wasting energy and degrading throughput.In reality,not all of the sensors in WBAN need to be active at the same time.Therefore,they can be divided into different groups so that each group works in turn to avoid interference.In this paper,a Nest-Based WBAN Scheduling(NBWS)algorithm is proposed to cluster sensors of the same types in a single or multiple WBANs into different groups to avoid interference.Particularly,we borrow the graph coloring theory to schedule all groups to work using a Time Division for Multimodal Sensor(TDMS)group scheduling model.Both theoretical analysis and experimental results demonstrate that the proposed NBWS algorithm performs better in terms of frequency of collisions,transmission delay,system throughput,and energy consumption compared to the counterpart methods.

Distributed privacy protection strategy for MEC enhanced wireless body area networks

With the rapid development and widespread application of Wireless Body Area Networks(WBANs),the traditional centralized system architecture cannot handle the massive data generated by the edge devices.Meanwhile,in order to ensure the security of physiological privacy data and the identity privacy of patients,this paper presents a privacy protection strategy for Mobile Edge Computing(MEC)enhanced WBANs,which leverages the blockchain-based decentralized MEC paradigm to support efficient transmission of privacy information with low latency,high reliability within a high-demand data security scenario.On this basis,the Merkle tree optimization model is designed to authenticate nodes and to verify the source of physiological data.Furthermore,a hybrid signature algorithm is devised to guarantee the node anonymity with unforgeability,data integrity and reduced delay.The security performance analysis and simulation results show that our proposed strategy not only reduces the delay,but also secures the privacy and transmission of sensitive WBANs data.

Power Allocation for Energy Harvesting in Wireless Body Area Networks

Wireless Body Area Networks(WBANs) are expected to achieve high reliable communications among a large number of sensors.The outage probability can be used to measure the reliability of the WBAN.In this paper,we optimize the outage probability with the harvested energy as constraints.Firstly,the optimal transmit power of the sensor is obtained while considering a single link between an access point(AP) located on the waist and a sensor attached on the wrist over the Rayleigh fading channel.Secondly,an optimization problem is formed to minimize the outage probability.Finally,we convert the non-convex optimization problem into convex solved by the Lagrange multiplier method.Simulations show that the optimization problem is solvable.The outage probability is optimized by performing power allocation at the sensor.And our proposed algorithm achieves minimizing the outage probability when the sensor uses energy harvesting.We also demonstrate that the average outage probability is reduced with the increase of the harvested energy.

An Experimental Study of Network-based Language Learning in Less-developed Areas

The advent of the Age of Information brings about bright prospects to Network-based Language Learning(NBLL).The thesis adopts the Engagement Theory as guided principles.The purpose is to use the novel NBLL model effectively with the help of modern technology especially in less-developed areas.This thesis focuses on network-based experimental study.The research shows that the students under NBLL environment have cultivated the capabilities in information collection,computer operation,and information evaluation,as well as the abilities in problem solving,reasoning with criticism,and cooperating with others.

Remote Health Monitoring Using IoT-Based Smart Wireless Body Area Network

A wireless body area network(WBAN)consists of tiny healthmonitoring sensors implanted in or placed on the human body.These sensors are used to collect and communicate human medical and physiological data and represent a subset of the Internet of Things(IoT)systems.WBANs are connected to medical servers that monitor patients’health.This type of network can protect critical patients’lives due to the ability to monitor patients’health continuously and remotely.The inter-WBAN communication provides a dynamic environment for patients allowing them to move freely.However,during patient movement,the WBAN patient nodes may become out of range of a remote base station.Hence,to handle this problem,an efficient method for inter-WBAN communication is needed.In this study,a method using a cluster-based routing technique is proposed.In the proposed method,a cluster head(CH)acts as a gateway between the cluster members and the external network,which helps to reduce the network’s overhead.In clustering,the cluster’s lifetime is a vital parameter for network efficiency.Thus,to optimize the CH’s selection process,three evolutionary algorithms are employed,namely,the ant colony optimization(ACO),multi-objective particle swarm optimization(MOPSO),and the comprehensive learning particle swarm optimization(CLPSO).The performance of the proposed method is verified by extensive experiments by varying values of different parameters,including the transmission range,node number,node mobility,and grid size.A comprehensive comparative analysis of the three algorithms is conducted by extensive experiments.The results show that,compared with the other methods,the proposed ACO-based method can form clusters more efficiently and increase network lifetime,thus achieving remarkable network and energy efficiency.The proposed ACO-based technique can also be used in other types of ad-hoc networks as well.

Black Hole and Sink Hole Attack Detection in Wireless Body Area Networks

In Wireless Body Area Networks(WBANs)with respect to health care,sensors are positioned inside the body of an individual to transfer sensed data to a central station periodically.The great challenges posed to healthcare WBANs are the black hole and sink hole attacks.Data from deployed sensor nodes are attracted by sink hole or black hole nodes while grabbing the shortest path.Identifying this issue is quite a challenging task as a small variation in medicine intake may result in a severe illness.This work proposes a hybrid detection framework for attacks by applying a Proportional Coinciding Score(PCS)and an MK-Means algorithm,which is a well-known machine learning technique used to raise attack detection accuracy and decrease computational difficulties while giving treatments for heartache and respiratory issues.First,the gathered training data feature count is reduced through data pre-processing in the PCS.Second,the pre-processed features are sent to the MK-Means algorithm for training the data and promoting classification.Third,certain attack detection measures given by the intrusion detection system,such as the number of data packages trans-received,are identified by the MK-Means algorithm.This study demonstrates that the MK-Means framework yields a high detection accuracy with a low packet loss rate,low communication overhead,and reduced end-to-end delay in the network and improves the accuracy of biomedical data.

A Game Theoretic Approach for Inter-Network Interference Mitigation in Wireless Body Area Networks

Wireless Body Area Network(WBAN) is an emerging technology to provide real-time health monitoring and ubiquitous healthcare services. In many applications, multiple wireless body area networks have to coexist in a small area, resulting in serious inter-network interference. This not only reduces network reliability that is especially important in emergency medical applications, but also consumes more power of WBANs. In this paper, an inter-network interference mitigation approach based on a power control algorithm is proposed. Power control is modeled as a non-cooperative game, in which both inter-network interference and energy efficiency of WBANs are considered. The existence and uniqueness of Nash Equilibrium in the game are proved, and an optimal scheme based on best response is proposed to find its Nash Equilibrium. By coordinating the transmission power levels among networks under interference environment, the total system throughput can be increased with minimum power consumed. The effectiveness of the proposed method has been illustrated by simulation results, where the performance of the proposed approach is evaluated in terms of overall utility and power efficiency and convergence speed.

Optimization of Air Route Network Nodes to Avoid ″Three Areas″ Based on An Adaptive Ant Colony Algorithm

Air route network(ARN)planning is an efficient way to alleviate civil aviation flight delays caused by increasing development and pressure for safe operation.Here,the ARN shortest path was taken as the objective function,and an air route network node(ARNN)optimization model was developed to circumvent the restrictions imposed by″three areas″,also known as prohibited areas,restricted areas,and dangerous areas(PRDs),by creating agrid environment.And finally the objective function was solved by means of an adaptive ant colony algorithm(AACA).The A593,A470,B221,and G204 air routes in the busy ZSHA flight information region,where the airspace includes areas with different levels of PRDs,were taken as an example.Based on current flight patterns,a layout optimization of the ARNN was computed using this model and algorithm and successfully avoided PRDs.The optimized result reduced the total length of routes by 2.14% and the total cost by 9.875%.

Energy-Efficient Area Coverage in Heterogeneous Energy Wireless Sensor Networks

Sensing coverage and energy consumption are two primary issues in wireless sensor networks. Sensing coverage is closely related to network energy consumption. The performance of a sensor network depends to a large extent on the sensing coverage, and its lifetime is determined by its energy consumption. In this paper, an energy-efficient Area Coverage protocol for Heterogeneous Energy sensor networks (ACHE) is proposed. ACHE can achieve a good performance in terms of sensing area coverage, lifetime by minimizing energy consumption for control overhead, and balancing the energy load among all nodes. Adopting the hierarchical clustering idea, ACHE selects the active nodes based on the average residual energy of neighboring nodes and its own residual energy parameters. Our simulation demonstrates that ACHE not only provide the high quality of sensing coverage, but also has the good performance in the energy efficiency. In addition, ACHE can better adapt the applications with the great heterogeneous energy capacities in the sensor networks, as well as effectively reduce the control overhead.

Priority-based adaptive transmission algorithm for medical devices in wireless body area networks(WBANs)

A wireless body area network offers cost-effective solutions for healthcare infrastructure. An adaptive transmission algorithm is designed to handle channel efficiency, which adjusts packet size according to the difference in feature-point values that indicate biomedical signal characteristics. Furthermore, we propose a priority-adjustment method that enhances quality of service while guaranteeing signal integrity. A large number of simulations were carried out for performance evaluation. We use electrocardiogram and electromyogram signals as reference biomedical signals for performance verification. From the simulation results, we find that the average packet latency of proposed scheme is enhanced by 30% compared to conventional method. The simulation results also demonstrate that the proposed algorithm achieves significant performance improvement in terms of drop rates of high-priority packets around 0.3%-0.9 %.

A novel intrusion detection model for the CAN bus packet of in-vehicle network based on attention mechanism and autoencoder

The attacks on in-vehicle Controller Area Network(CAN)bus messages severely disrupt normal communication between vehicles.Therefore,researches on intrusion detection models for CAN have positive business value for vehicle security,and the intrusion detection technology for CAN bus messages can effectively protect the invehicle network from unlawful attacks.Previous machine learning-based models are unable to effectively identify intrusive abnormal messages due to their inherent shortcomings.Hence,to address the shortcomings of the previous machine learning-based intrusion detection technique,we propose a novel method using Attention Mechanism and AutoEncoder for Intrusion Detection(AMAEID).The AMAEID model first converts the raw hexadecimal message data into binary format to obtain better input.Then the AMAEID model encodes and decodes the binary message data using a multi-layer denoising autoencoder model to obtain a hidden feature representation that can represent the potential features behind the message data at a deeper level.Finally,the AMAEID model uses the attention mechanism and the fully connected layer network to infer whether the message is an abnormal message or not.The experimental results with three evaluation metrics on a real in-vehicle CAN bus message dataset outperform some traditional machine learning algorithms,demonstrating the effectiveness of the AMAEID model.

Application of Wireless Local Area Network Technology in Mobile Robot for Finned Tube Inspection

This paper introduces a novel robot for outer surface inspection of boiler tubes. The paper describes the hardware system, wireless communication strategy, communication procedure and system software of the robot. The WLAN technology is used in the robot. It solves the problem of shielding generated by iron boiler and 11Mbps bandwidth made it possible for video and control stream real-time transmit within the same channel. Though TCP/IP protocol is robust, serial server is a transparent channel but cannot detect error and retransmit the data. In order to improve the reliability of serial communication, a new communication protocol is proposed. Key words boiler tubes - mobile robotics - wireless local area network Project Supported by the National High-Tech Program (Grant No. 2002AA420080)

Error Control Strategy in Ultrasonic Body Area Networks

Recently,ultrasonic waves had been introduced as the transmission medium in Body Area Networks(BANs) to reduce the incalculable damage caused by radio waves. However,the communications based on ultrasonic waves suffer from poor propagation of signals in air and consume too much energy. To address these limitations,firstly,we make the theoretical analysis to ensure ultrasonic waves could be used in BANs(UBANs). Then,we propose an error control strategy in UBANs to dynamically adjust the error control scheme and the Max-Retries based on the current channel state,which is called UECS. The UECS is based on IEEE 802.15.6 standards and considering the characteristics of ultrasonic waves in BANs. Simulation results show that UECS achieves better performance in terms of packet delivery ratio and energy consumption compared with the traditional strategies.

Energy-Efficieng MAC Protocols for Wireless Body Area Networks: A Survey

In this paper, we provide a comprehensive survey of key energy-efficient Medium Access Control (MAC) protocols for Wireless Body Area Networks (WBANs). At the outset, we outline the crucial attributes of a good MAC protocol for WBAN. Several sources that contribute to the energy inefficiency of WBAN are identified, and features of the various MAC protocols qualitatively compared. Then, we further investigate some representative TDMA-based energy-efficient MAC protocols for WBAN by emphasizing their strengths and weaknesses. Finally, we conclude with a number of open research issues with regard to WBAN MAC layer.