Network Coded Cooperative Communication in a Real-Time Wireless Hospital Sensor Network

The paper presents a network coded cooperative communication (NC-CC) enabled wireless hospital sensor network architecture for monitoring health as well as postural activities of a patient. A wearable device, referred as a smartband is interfaced with pulse rate, body temperature sensors and an accelerometer along with wireless protocol services, such as Bluetooth and Radio-Frequency transceiver and Wi-Fi. The energy efficiency of wearable device is improved by embedding a linear acceleration based transmission duty cycling algorithm (NC-DRDC). The real-time demonstration is carried-out in a hospital environment to evaluate the performance characteristics, such as power spectral density, energy consumption, signal to noise ratio, packet delivery ratio and transmission offset. The resource sharing and energy efficiency features of network coding technique are improved by proposing an algorithm referred as network coding based dynamic retransmit/rebroadcast decision control (LA-TDC). From the experimental results, it is observed that the proposed LA-TDC algorithm reduces network traffic and end-to-end delay by an average of 27.8% and 21.6%, respectively than traditional network coded wireless transmission. The wireless architecture is deployed in a hospital environment and results are then successfully validated.     

一种基于双功能节点的节能多跳路由协议

针对无线传感网融合节点位置欠佳和传感器节点的能量消耗不均会严重影响网络生存周期的问题,提出了一种基于双功能节点的节能多跳路由协议。该协议综合考虑节点的能量、位置以及所在层次区域等多种因素,通过引入通信节点来重组网格和中继网格间路由,减轻了网格融合节点的开销,均衡了网络的能量分布。仿真结果表明,该路由协议的网络生命周期比Multi hop EEBCDA等协议至少延长17.5%,且节点的能量消耗更加均衡。     

基于BA无标度网络的WSNs拓扑优化模型

由于无线传感器能量受限,最大化网络生命周期成为优化网络拓扑首要考虑的问题。基于BA无标度理论,提出了一种WSNs拓扑优化模型（WTOM）。在网络中引入超级节点,结合粒子群算法合理地划分整个网络;在节点间建立多因素为导向的虚拟力场,利用虚拟力调整超级节点的部署位置,实现网络能量的均衡消耗,通过对关键节点的保护,提高网络的抗毁鲁棒性。经理论分析和实验证明,该网络不仅继承了BA无标度网络的特征还具有小世界特性;同时该动态拓扑延长了网络的生命周期,提高了网络面向数据收集的节能性。     

基于能量均衡的WSN多跳非均匀分簇路由算法

在无线传感器网络路由协议中采用多跳通信的方式能够减少通讯距离、增强网络通讯的稳定性并提高网络能量利用效率,但是,由于靠近汇聚节点的簇头需要转发大量数据,容易导致能量快速衰竭而失效,造成“能量空洞”现象。提出了一种新型的基于能量均衡的多跳非均匀分簇路由算法（MUCRA）,采用逐层成簇的策略,簇头以一定的半径广播分层信号,划分下一层网络区域非均匀层次,普通的传感器节点和簇头根据分层信息选择合适的网络路径。仿真实验结果表明：与经典的LEACH协议及EEUC协议相比,该算法能有效平衡网络负载,缓解“能量空洞”问题     

A Lightweight Security Scheme for Wireless Body Area Networks: Design, Energy Evaluation and Proposed Microprocessor Design

In order for wireless body area networks to meet widespread adoption, a number of security implications must be explored to promote and maintain fundamental medical ethical principles and social expectations. As a result, integration of security functionality to sensor nodes is required. Integrating security functionality to a wireless sensor node increases the size of the stored software program in program memory, the required time that the sensor's microprocessor needs to process the data and the wireless network traffic which is exchanged among sensors. This security overhead has dominant impact on the energy dissipation which is strongly related to the lifetime of the sensor, a critical aspect in wireless sensor network (WSN) technology. Strict definition of the security functionality, complete hardware model (microprocessor and radio), WBAN topology and the structure of the medium access control (MAC) frame are required for an accurate estimation of the energy that security introduces into the WBAN. In this work, we define a lightweight security scheme for WBAN, we estimate the additional energy consumption that the security scheme introduces to WBAN based on commercial available off-the-shelf hardware components (microprocessor and radio), the network topology and the MAC frame. Furthermore, we propose a new microcontroller design in order to reduce the energy consumption of the system. Experimental results and comparisons with other works are given.     

Monitoring of Physiological Parameters from Multiple Patients Using Wireless Sensor Network

This paper presents a wireless sensor network system that has the capability to monitor physiological parameters from multiple patient bodies. The system uses the Medical Implant Communication Service band between the sensor nodes and a remote central control unit (CCU) that behaves as a base station. The CCU communicates with another network standard (the internet or a mobile network) for a long distance data transfer. The proposed system offers mobility to patients and flexibility to medical staff to obtain patient’s physiological data on demand basis via Internet. A prototype sensor network including hardware, firmware and software designs has been implemented and tested. The developed system has been optimized for power consumption by having the nodes sleep when there is no communication via a bidirectional communication.     

Secure Data Aggregation in Wireless Sensor Network-Fujisaki Okamoto(FO) Authentication Scheme against Sybil Attack

In the wireless sensor network(WSN) security is a major issue. There are several network security schemes proposed in research. In the network, malicious nodes obstruct the performance of the network. The network can be vulnerable by Sybil attack. When a node illicitly assertions multiple identities or claims fake IDs, the WSN grieves from an attack named Sybil attack. This attack threatens wireless sensor network in data aggregation, synchronizing system, routing, fair resource allocation and misbehavior detection. Henceforth, the research is carried out to prevent the Sybil attack and increase the performance of the network. This paper presents the novel security mechanism and Fujisaki Okamoto algorithm and also application of the work. The Fujisaki-Okamoto (FO) algorithm is ID based cryptographic scheme and gives strong authentication against Sybil attack. By using Network simulator2 (NS2) the scheme is simulated. In this proposed scheme broadcasting key, time taken for different key sizes, energy consumption, Packet delivery ratio, Throughput were analyzed.     

Energy-aware Gateway Selection for Increasing the Lifetime of Wireless Body Area Sensor Networks

A Wireless Body Area Sensor Network (WBASN) is composed of a set of sensor nodes, placed on, near or within a human body. WBASNs opt to continuously monitor the health conditions of individuals under medical risk, e.g., elders and chronically ill people, without keeping them in a hospital or restraining their motion. A WBASN needs to stay connected to local or wide area networks using wireless technologies in order to send sensor readings to a medical center. The WBASN nodes are implanted within the human body and would thus have limited energy supply. Since the mission of the WBASN is very critical, increasing the lifetime of nodes is essential in order to maintain both practicality and effectiveness. This paper presents a new Gateway Selection Algorithm (GSA) that factors in the use of energy harvesting technologies and dynamically picks the most suitable WBASN node that serves as a gateway to other wireless networks. The goal of GSA is to balance the load among the nodes by adaptively changing the gateway node in WBASN depending on the energy reserve of nodes. Computer modeling and simulations of the proposed GSA are carried out using OPNET. The simulation results demonstrate the effectiveness of the proposed GSA approach.     

A WBAN-based Real-time Electroencephalogram Monitoring System: Design and Implementation

In this study, a flexible wireless body area network (WBAN) node platform has been designed and implemented based on the Zigbee technology. In order to provide wide range WBAN for health monitoring, a Zigbee/Internet Gateway (ZiGW) has also been developed rather than using a PDA or a host PC to connect different WBANs by using the Internet as the communication infrastructure. The proposed body sensor node platform promises a cost-effective, flexible platform for developing physical sensor node in real-time health monitoring. The ZiGW can provide an effective method to connect WBAN with the Internet. In this work, we present the implementation of an Electroencephalogram (EEG) monitoring system using the proposed methods. In this proposed system, real-time EEG signals can be remotely monitored by physicians via Internet, and the collected EEG data is stored in the online EEG database which can be shared with physicians or researchers for further analysis.     

An Ultra Low-power and Traffic-adaptive Medium Access Control Protocol for Wireless Body Area Network

Wireless Body Area Network (WBAN) consists of low-power, miniaturized, and autonomous wireless sensor nodes that enable physicians to remotely monitor vital signs of patients and provide real-time feedback with medical diagnosis and consultations. It is the most reliable and cheaper way to take care of patients suffering from chronic diseases such as asthma, diabetes and cardiovascular diseases. Some of the most important attributes of WBAN is low-power consumption and delay. This can be achieved by introducing flexible duty cycling techniques on the energy constraint sensor nodes. Stated otherwise, low duty cycle nodes should not receive frequent synchronization and control packets if they have no data to send/receive. In this paper, we introduce a Traffic-adaptive MAC protocol (TaMAC) by taking into account the traffic information of the sensor nodes. The protocol dynamically adjusts the duty cycle of the sensor nodes according to their traffic-patterns, thus solving the idle listening and overhearing problems. The traffic-patterns of all sensor nodes are organized and maintained by the coordinator. The TaMAC protocol is supported by a wakeup radio that is used to accommodate emergency and on-demand events in a reliable manner. The wakeup radio uses a separate control channel along with the data channel and therefore it has considerably low power consumption requirements. Analytical expressions are derived to analyze and compare the performance of the TaMAC protocol with the well-known beacon-enabled IEEE 802.15.4 MAC, WiseMAC, and SMAC protocols. The analytical derivations are further validated by simulation results. It is shown that the TaMAC protocol outperforms all other protocols in terms of power consumption and delay.     

An Improved Two-Layer Authentication Scheme for Wireless Body Area Networks

Wireless body area networks (WBANs) comprises a number of sensor nodes and the portable mobile device such as smartphone. It is used to monitor the physical condition and provide a reliable healthcare system. Utilizing the wireless communication network, sensor nodes collect the physiological data of one patient to the portable mobile device and the latter analyzes and transmits them to the application providers. Therefore, the personal data confidentiality and user privacy are cores of WBANs. Recently, Shen et al. presented a multi-layer authentication protocol for WBANs, which is lightweight and much easier to implement. However, we observe that their authentication between sensor nodes and the portable mobile device could ensure the forward security property only when the sensor nodes are changed (add or delete). When the sensor nodes are constant, the security property is not satisfied. Meanwhile, the authentication between the portable mobile device and application provider is prone to mutual impersonation attack, so the critical goal of mutual authentication can not be achieved. In this paper, an improved two-layer authentication scheme is proposed to remove the flaws. The analysis shows that our method is more secure and could withstand various attacks.     

网络化多参数体征监测仪的设计

目的：设计一种基于无线传感网络的多参数体征监测仪,取代传统有线式数据传输,提高便携式心电监测仪的适应能力。方法系统采用Zigbee无线传感技术,对人体心电、血氧饱和度、无创血压等生命体征参数进行动态监测,并通过小波变换对心电监测算法进行改进,提高心电监测的分辨率和精准度。结果实现了各种医疗监测模块的即插即用功能,以及特征监测数据的网络化传输。结论网络化心电检测仪结构简单、精度高、系统功耗低。     

Variable Threshold Method for ECG R-peak Detection

In this paper, a wearable belt-type ECG electrode worn around the chest by measuring the real-time ECG is produced in order to minimize the inconvenient in wearing. ECG signal is detected using a potential instrument system. The measured ECG signal is transmits via an ultra low power consumption wireless data communications unit to personal computer using Zigbee-compatible wireless sensor node. ECG signals carry a lot of clinical information for a cardiologist especially the R-peak detection in ECG. R-peak detection generally uses the threshold value which is fixed. There will be errors in peak detection when the baseline changes due to motion artifacts and signal size changes. Preprocessing process which includes differentiation process and Hilbert transform is used as signal preprocessing algorithm. Thereafter, variable threshold method is used to detect the R-peak which is more accurate and efficient than fixed threshold value method. R-peak detection using MIT-BIH databases and Long Term Real-Time ECG is performed in this research in order to evaluate the performance analysis.     

Evaluation of Digital Compressed Sensing for Real-Time Wireless ECG System with Bluetooth low Energy

In this paper, a wearable and wireless ECG system is firstly designed with Bluetooth Low Energy (BLE). It can detect 3-lead ECG signals and is completely wireless. Secondly the digital Compressed Sensing (CS) is implemented to increase the energy efficiency of wireless ECG sensor. Different sparsifying basis, various compression ratio (CR) and several reconstruction algorithms are simulated and discussed. Finally the reconstruction is done by the android application (App) on smartphone to display the signal in real time. The power efficiency is measured and compared with the system without CS. The optimum satisfying basis built by 3-level decomposed db4 wavelet coefficients, 1-bit Bernoulli random matrix and the most suitable reconstruction algorithm are selected by the simulations and applied on the sensor node and App. The signal is successfully reconstructed and displayed on the App of smartphone. Battery life of sensor node is extended from 55 h to 67 h. The presented wireless ECG system with CS can significantly extend the battery life by 22 %. With the compact characteristic and long term working time, the system provides a feasible solution for the long term homecare utilization.     

mHealthMon: Toward Energy-Efficient and Distributed Mobile Health Monitoring Using Parallel Offloading

Although mobile health monitoring where mobile sensors continuously gather, process, and update sensor readings (e.g. vital signals) from patient’s sensors is emerging, little effort has been investigated in an energy-efficient management of sensor information gathering and processing. Mobile health monitoring with the focus of energy consumption may instead be holistically analyzed and systematically designed as a global solution to optimization subproblems. This paper presents an attempt to decompose the very complex mobile health monitoring system whose layer in the system corresponds to decomposed subproblems, and interfaces between them are quantified as functions of the optimization variables in order to orchestrate the subproblems. We propose a distributed and energy-saving mobile health platform, called mHealthMon where mobile users publish/access sensor data via a cloud computing-based distributed P2P overlay network. The key objective is to satisfy the mobile health monitoring application’s quality of service requirements by modeling each subsystem: mobile clients with medical sensors, wireless network medium, and distributed cloud services. By simulations based on experimental data, we present the proposed system can achieve up to 10.1 times more energy-efficient and 20.2 times faster compared to a standalone mobile health monitoring application, in various mobile health monitoring scenarios applying a realistic mobility model.     

基于改进的果蝇优化算法的WSN节点部署设计

针对非均匀监测点的节点部署问题,设计并实现了一种简单、实用的果蝇优化算法（WSN-IFOA）,构造了适用于节点部署的味道浓度函数。利用果蝇群体的随机寻优性,能够保证部署尽可能少的传感器节点使网络覆盖和连通。实验结果表明该算法在部署效果上优于基本蚁群算法,并证明了算法的可行性和有效性。     

Improved Particle Swarm Optimization Algorithm for Android Medical Care IOT using Modified Parameters

This study examines wireless sensor network with real-time remote identification using the Android study of things (HCIOT) platform in community healthcare. An improved particle swarm optimization (PSO) method is proposed to efficiently enhance physiological multi-sensors data fusion measurement precision in the Internet of Things (IOT) system. Improved PSO (IPSO) includes: inertia weight factor design, shrinkage factor adjustment to allow improved PSO algorithm data fusion performance. The Android platform is employed to build multi-physiological signal processing and timely medical care of things analysis. Wireless sensor network signal transmission and Internet links allow community or family members to have timely medical care network services.     

Wireless Body Sensor Network Using Medical Implant Band

A wireless body sensor network hardware has been designed and implemented based on MICS (Medical Implant Communication Service) band. The MICS band offers the advantage of miniaturized electronic devices that can either be used as an implanted node or as an external node. In this work, the prototype system uses temperature and pulse rate sensors on nodes. The sensor node can transmit data over the air to a remote central control unit (CCU) for further processing, monitoring and storage. The developed system offers medical staff to obtain patient’s physiological data on demand basis via the Internet. Some preliminary performance data is presented in the paper.     

基于突发传输的平均速率优化算法

随着互联网和移动通信的快速发展,对数据传输速率的要求也越来越高。本文针对总功率有限的慢衰落系统,在短期功率约束和长期功率约束下,提出了实现最大平均速率的优化方案。在短期功率约束下,通过研究信道增益进而得出突发传输下的最优量化方案;在长期功率约束下,提出了基于注水算法的改进功率分配算法,进而实现最大速率。理论分析及仿真结果显示,本文算法对改善传输速率有较好的表现。     

基于分簇的动态协同算法在无线传感器网络中的应用

为降低无线传感器网络中的能量开销,减少存储和网络资源,采用了一种新的信息融合机制。根据目标的当前地理位置,将无线传感器网络中的节点动态分簇,建立分布式的跟踪机制。利用一种基于信息矩阵加权的卡尔曼算法在该机制下进行目标跟踪,与无分簇机制下的信息矩阵融合算法进行性能比较,仿真实验结果表明该方法具有较高的有效性和可靠性。同时,在网络存在丢包情况下,基于Grubbs准则进行改进,能有效地提高精度。