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基于区块链的延迟和能量收集感知的 WBAN 环境中的医疗保健监测系统。

Blockchain Based Delay and Energy Harvest Aware Healthcare Monitoring System in WBAN Environment.

机构信息

School of Computer Science and Engineering, Vellore Institute of Technology (VIT), Vellore 632014, India.

出版信息

Sensors (Basel). 2022 Aug 2;22(15):5763. doi: 10.3390/s22155763.

Abstract

Wireless body area networks (WBANs) are a research area that supports patients with healthcare monitoring. In WBAN, the Internet of Things (IoT) is connected with WBAN for a smart/remote healthcare monitoring system in which various medical diseases are diagnosed. Quality of service (), security and energy efficiency achievements are the major issues in the WBAN-IoT environment. Existing schemes for these three issues fail to achieve them since nodes are resource constrained and hence delay and the energy consumption is minimized. In this paper, a blockchain-assisted delay and energy aware healthcare monitoring (B-DEAH) system is presented in the WBAN-IoT environment. Both body sensors and environment sensors are deployed with dual sinks for emergency and periodical packet transmission. Various processes are involved in this paper, and each process is described as follows: Key registration for patients using an extended version of the PRESENT algorithm is proposed. Cluster formation and cluster head selection are implemented using spotted hyena optimizer. Then, cluster-based routing is established using the MOORA algorithm. For data transmission, the patient block agent (PBA) is deployed and authenticated using the four Q curve asymmetric algorithm. In PBA, three entities are used: classifier and queue manager, channel selector and security manager. Each entity is run by a special function, as packets are classified using two stream deep reinforcement learning (TS-DRL) into three classes: emergency, non-emergency and faulty data. Individual packets are put into a separate queue, which is called emergency, periodical and faulty. Each queue is handled using Reyni entropy. Periodical packets are forwarded by a separate channel without any interference using a multi objective based channel selection algorithm. Then, all packets are encrypted and forwarded to the sink nodes. Simulation is conducted using the OMNeT++ network simulator, in which diverse parameters are evaluated and compared with several existing works in terms of network throughput for periodic (41.75 Kbps) and emergency packets (42.5 Kbps); end-to-end delay for periodic (0.036 s) and emergency packets (0.028 s); packet loss rate (1.1%); residual energy in terms of simulation rounds based on periodic (0.039 J) and emergency packets (0.044 J) and in terms of simulation time based on periodic (8.35 J) and emergency packets (8.53 J); success rate for periodic (87.83%) and emergency packets (87.5%); authentication time (3.25 s); and reliability (87.83%).

摘要

无线体域网 (WBAN) 是支持医疗保健监测的患者的一个研究领域。在 WBAN 中,物联网 (IoT) 与 WBAN 相连,形成一个用于智能/远程医疗保健监测的系统,其中可以诊断各种医疗疾病。服务质量 (QoS)、安全性和能源效率的提高是 WBAN-IoT 环境中的主要问题。现有的针对这三个问题的方案都未能实现它们,因为节点的资源受到限制,因此延迟和能耗被最小化。在本文中,在 WBAN-IoT 环境中提出了一种基于区块链的延迟和能量感知的医疗保健监测 (B-DEAH) 系统。身体传感器和环境传感器都部署了双汇点,用于紧急和定期数据包传输。本文涉及多个过程,每个过程如下所述:使用 PRESENT 算法的扩展版本为患者进行密钥注册。使用斑点鬣狗优化器进行簇形成和簇头选择。然后,使用 MOORA 算法建立基于簇的路由。对于数据传输,部署了患者块代理 (PBA) 并使用四 Q 曲线不对称算法进行身份验证。在 PBA 中,使用三个实体:分类器和队列管理器、信道选择器和安全管理器。每个实体都由一个特殊功能运行,因为数据包使用两流深度强化学习 (TS-DRL) 分为三类:紧急、非紧急和错误数据。个别数据包放入单独的队列中,称为紧急、定期和错误。每个队列都使用 Reyni 熵进行处理。定期数据包使用多目标信道选择算法通过单独的信道转发,没有任何干扰。然后,所有数据包都被加密并转发到汇节点。使用 OMNeT++网络模拟器进行仿真,在该模拟器中,根据网络吞吐量(周期性为 41.75 Kbps,紧急为 42.5 Kbps)、端到端延迟(周期性为 0.036 s,紧急为 0.028 s)、数据包丢失率(1.1%)、基于周期性(0.039 J)和紧急(0.044 J)的模拟轮次的剩余能量和基于周期性(8.35 J)和紧急(8.53 J)的模拟时间、周期性(87.83%)和紧急(87.5%)的数据包成功率、身份验证时间(3.25 s)和可靠性(87.83%)对各种参数进行评估和比较。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdde/9371143/a17332224615/sensors-22-05763-g001.jpg

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