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.

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.

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.

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.

MAC Layer Resource Allocation for Wireless Body Area Networks

Wireless body area networks （WBANs） can provide low-cost, timely healthcare services and are expected to be widely used for e-healthcare in hospitals. In a hospital, space is often limited and multiple WBANs have to coexist in an area and share the same channel in order to provide healthcare services to different patients. This causes severe interference between WBANs that could significantly reduce the network throughput and increase the amount of power consumed by sensors placed on the body. There-fore, an efficient channel-resource allocation scheme in the medium access control （MAC） layer is crucial. In this paper, we devel-op a centralized MAC layer resource allocation scheme for a WBAN. We focus on mitigating the interference between WBANs and reducing the power consumed by sensors. Channel and buffer state are reported by smartphones deployed in each WBAN, and channel access allocation is performed by a central controller to maximize network throughput. Sensors have strict limitations in terms of energy consumption and computing capability and cannot provide all the necessary information for channel allocation in a timely manner. This deteriorates network performance. We exploit the temporal correlation of the body area channel in order to minimize the number of channel state reports necessary. We view the network design as a partly observable optimization prob-lem and develop a myopic policy, which we then simulate in Matlab.

Wireless Body Area Networks for Pervasive Healthcare and Smart Environments

Wireless body area networks （WBANs） use RF communication for interconnection of tiny sensor nodes located in, on, or in close prox- imity to the human body. A WBAN enables physiological signals, physical activity, and body position to be continuously monitored.

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.

An Efficient Energy Aware Routing Mechanism for Wireless Body Area Networks

The accelerated development of wireless network technology has resulted in the emergence of Wireless Body Area Network(WBAN),which is a technology commonly used in the medical field.WBAN consists of tiny sensor nodes that interconnect with each other and set in the human body to collect and transmit the patient data to the physician,to monitor the patients remotely.These nodes typically have limited battery energy that led to a shortage of network lifetime.Therefore,energy efficiency is considered one of the most demanding challenges in routing design for WBAN.Many proposed routing mechanisms inWBAN did not cover the source node energy and energy harvesting techniques.Therefore,this study proposes an Efficient Energy Aware Routing(EEAR)mechanism.This paper constructs a path cost function that considers three parameters:residual energy,number of hops to the sink,and the distance between the nodes.Besides,data aggregationwith filtration and hybrid energy harvesting technique are used to extend the network lifetime,reduce the network traffic load,andmaintain the source node energy.Extensive simulations using MATLAB have been performed to evaluate the performance of the proposed mechanism.EEAR is contrasted with the two latest schemes,called Priority-based Congestion-avoidance Routing Protocol(PCRP)and Energy Efficient Routing Protocol(EERP).The results show the significant performance of theEEARmechanism in terms of network lifetime,residual energy,network stability,and throughput.

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 %.

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.

BGMM： A Body Gauss-Markov Based Mobility Model for Body Area Networks

Existing mobility models have limitations in their ability to simulate the movement of Wireless Body Area Network（WBAN） since body nodes do not exactly follow either classic mobility models or human contact distributions. In this paper, we propose a new mobility model called Body Gauss–Markov Mobility（BGMM） model,which is oriented specially to WBAN. First, we present the random Gauss-Markov mobility model as the most suitable theoretical basis for developing our new model, as its movement pattern can reveal real human body movements. Next, we examine the transfer of human movement states and derive a simplified mathematical Human Mobility Model（HMM）. We then construct the BGMM model by combining the RGMM and HMM models. Finally,we simulate the traces of the new mobility model. We use four direct metrics in our proposed mobility model to evaluate its performance. The simulation results show that the proposed BGMM model performs with respect to the direct mobility metrics and can effectively represent a general WBAN-nodes movement pattern.

Adaptive Multi-Cost Routing Protocol to Enhance Lifetime for Wireless Body Area Network

Wireless Body Area Network(WBAN)technologies are emerging with extensive applications in several domains.Health is a fascinating domain of WBAN for smart monitoring of a patient’s condition.An important factor to consider in WBAN is a node’s lifetime.Improving the lifetime of nodes is critical to address many issues,such as utility and reliability.Existing routing protocols have addressed the energy conservation problem but considered only a few parameters,thus affecting their performance.Moreover,most of the existing schemes did not consider traffic prioritization which is critical in WBANs.In this paper,an adaptive multi-cost routing protocol is proposed with a multi-objective cost function considering minimum distance from sink,temperature of sensor nodes,priority of sensed data,and maximum residual energy on sensor nodes.The performance of the proposed protocol is compared with the existing schemes for the parameters:network lifetime,stability period,throughput,energy consumption,and path loss.It is evident from the obtained results that the proposed protocol improves network lifetime and stability period by 30%and 15%,respectively,as well as outperforms the existing protocols in terms of throughput,energy consumption,and path loss.

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.

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.

A Review of Implant Intra-Body Communication

With an extending life expectancy and demand for medical healthcare,there are wide-spread and stringent requirements of implantable medical devices(IMDs)development for dia-gnostics,treatments,and therapies by emerging technologies.One of the primary targets for the IMDs is evolving a reliable,speed,and accurate communication method to provide proactive well-ness management and thereby achieve early detection,disease prevention,and even treatments.In-tra-body communication(IBC)is a potential technology envisioning a sensors/actuators network within a human body,which uses the conductive properties of a body and is categorized in the standardized IEEE 802.15.06 protocol.In the present review,the current state-of-art of implant in-tra-body communication has been surveyed.Based on the propagation mechanisms over investig-ated IBC spectrum(i.e.,0.1 MHz-100 MHz),the capacitive and galvanic coupling IBC is con-sidered,where the subfields regarding modeling method(including circuit,numerical,analytical,and filter model),measurement details(including the effect of the electrode,cable,impedance,and instrument),clinical application(including cardiac pacemaker and wireless endoscope),transceiver design(including discrete component and CMOS technology)and media access control(MAC)lay-er design have been introduced or discussed.Furthermore,the open challenges and issues have been explored as an anticipated inspiration for future development.

Defected Ground Structure Multiple Input-Output Antenna For Wireless Applications

In this paper,the investigation of a novel compact 2×2,2×1,and 1×1 Ultra-Wide Band(UWB)based Multiple-Input Multiple-Output(MIMO)antenna with Defected Ground Structure(DGS)is employed.The proposed Electromagnetic Radiation Structures(ERS)is composed of multiple radiating elements.These MIMO antennas are designed and analyzed with and without DGS.The feeding is introduced by a microstrip-fed line to significantly moderate the radiating structure’s overall size,which is 60×40×1 mm.The high directivity and divergence characteristics are attained by introducing the microstripfed lines perpendicular to each other.And the projected MIMO antenna structures are compared with others by using parameters like Return Loss(RL),Voltage Standing Wave Ratio(VSWR),Radiation Pattern(RP),radiation efficiency,and directivity.The same MIMO set-up is redesigned with DGS,and the resultant parameters are compared.Finally,the Multiple Input and Multiple Output Radiating Structures with and without DGS are compared for result considerations like RL,VSWR,RP,radiation efficiency,and directivity.This projected antenna displays an omnidirectional RP with moderate gain,which is highly recommended for human healthcare applications.By introducing the defected ground structure in bottom layer the lower cut-off frequencies of 2.3,4.5 and 6.0 GHz are achieved with few biological effects on radio propagation in human body communications.The proposed design covers numerous well-known wireless standards,along with dual-function DGS slots,and it can be easily integrated into Wireless Body Area Networks(WBAN)in medical applications.This WBAN links the autonomous nodes that may be situated either in the clothes,on-body or beneath the skin of a person.This system typically advances the complete human body and the inter-connected nodes through a wireless communication channel.

Self-powered wireless body area network for multi-joint movements monitoring based on contact-separation direct current triboelectric nanogenerators

Body area network has attracted extensive attention for its applications in athletics,medical,diagnosis,and rehabilitation training in the next generation personalized health care solutions.Here,a contact-separation direct current triboelectric nanogenerators(CSDC-TENGs)based selfpowered wireless body area network(SWBAN)is reported that enables multi-joint movements monitoring for human motion.The CSDC-TENG is designed as a flexible active sensor with an internal contact switch,and the flexible substrate makes the TENG-sensor stick onto skin easily.Due to the internal switch,the CSDC-TENG could generate a DC current,a large instantaneous output voltage exceeds 700 V,and an instantaneous power can reach 1.076 W,which is more than 23000 times higher than that of the traditional contact-separation mode TENG in same size and materials without the switch.By coupling with flexible coil,the fixed high-frequency radio signals can be modulated and emitted clearly ranging from 6 to 16 MHz,which can be wirelessly received and demodulated through a reader.Moreover,the SWBAN is demonstrated in a real time monitoring system for joints motion.This work has realized the wearable TENG for self-powered wireless real-time monitoring of body movements driven by low-frequency human daily activities,which may promote a tremendous development of intelligent healthcare,wireless sensing system and body area network.

Triple-Band Metamaterial Inspired Antenna for Future Terahertz(THz)Applications

For future healthcare in the terahertz(THz)band,a triple-band microstrip planar antenna integrated with metamaterial(MTM)based on a polyimide substrate is presented.The frequencies of operation are 500,600,and 880 GHz.The triple-band capability is accomplished by etching metamaterial on the patch without affecting the overall antenna size.Instead of a partial ground plane,a full ground plane is used as a buffer to shield the body from back radiation emitted by the antenna.The overall dimension of the proposed antenna is 484×484μm^(2).The antenna’s performance is investigated based on different crucial factors,and excellent results are demonstrated.The gain for the frequencies 500,600,880GHz is 6.41,6.77,10.1 dB,respectively while the efficiency for the same frequencies is 90%,95%,96%,respectively.Further research has been conducted by mounting the presented antenna on a single phantom layer with varying dielectric constants.The results show that the design works equally well with and without the phantom model,in contrast to a partially ground antenna,whose performance is influenced by the presence of the phantom model.As a result,the presented antenna could be helpful for future healthcare applications in the THz band.

无线体域网节能MAC协议综论(英文)

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.

A PUF-Based and Cloud-Assisted Lightweight Authentication for Multi-Hop Body Area Network

Wireless sensor technology plays an important role in the military,medical,and commercial fields nowadays.Wireless Body Area Network(WBAN)is a special application of the wireless sensor network in human health monitoring,through which patients can know their physical condition in real time and respond to emergencies on time.Data reliability,guaranteed by the trust of nodes in WBAN,is a prerequisite for the effective treatment of patients.Therefore,authenticating the sensor nodes and the sink nodes in WBAN is necessary.This paper proposes a lightweight Physical Unclonable Function(PUF)-based and cloud-assisted authentication mechanism for multi-hop body area networks,which compared with the star single-hop network,can enhance the adaptability to human motion and the integrity of data transmission.Such authentication mechanism can significantly reduce the storage overhead and resource loss in the data transmission process.