Medical data quality management using butterfly optimization with adaptive threshold sensitive energy-efficient routing protocol and multidimensional chaotic blowfish encryption in wireless body networks,Transactions on Emerging Telecommunications Technologies

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Medical data quality management using butterfly optimization with adaptive threshold sensitive energy-efficient routing protocol and multidimensional chaotic blowfish encryption in wireless body networks
Transactions on Emerging Telecommunications Technologies ( IF 2.5 ) Pub Date : 2022-08-03 , DOI: 10.1002/ett.4619
M. Santhalakshmi ₁ , P. Kavitha ₂

Affiliation

Nowadays, medical applications require much medical information to analyze various diseases. To collect various medical data, wearable devices collect patient health and medical details using a wireless body area network. The collected details consist of several critical details: oxygen level, heart attack information, blood pressure, airflow and so forth. These details are broadcast to the healthcare centers using wireless technologies to make clinical decisions. During medical information transfer, the data quality and critical events are difficult to maintain because it reduces the packet delivery, transmission delay, and high energy. So, this article introduces bacterial optimization and adaptive threshold-sensitive energy-efficient routing protocol (BOATSEE) to transmit the medical data. The method aggregates the sensitive data by selecting the cluster head and effectively broadcasts the critical data. In addition, the optimized method manages the network lifetime and energy using an energy-efficient method. Also, we have proposed a multidimensional chaotic blowfish encryption (MCBE) algorithm to enhance the system's security. Then the system's efficiency is computed based on metrics like energy consumption, packet delivery ratio, end-to-end delay, and QoS metric-associated restraints. The results reveal that the proposed system is efficient in managing the medical data quality with minimum energy utilization, packet loss rate, delay, and maximum packet delivery ratio when compared with the conventional approaches. Our method also proved to be more secure than the traditional systems.

中文翻译：

在无线人体网络中使用自适应阈值敏感节能路由协议和多维混沌河豚加密的蝶形优化进行医疗数据质量管理

如今，医学应用需要大量的医学信息来分析各种疾病。为了收集各种医疗数据，可穿戴设备使用无线体域网络收集患者的健康和医疗详细信息。收集的细节包括几个关键细节：氧气水平、心脏病发作信息、血压、气流等。这些细节使用无线技术广播到医疗中心，以做出临床决策。在医疗信息传输过程中，数据质量和关键事件难以维护，因为它减少了数据包的传递、传输延迟和高能量。因此，本文介绍了细菌优化和自适应阈值敏感节能路由协议（BOATSEE）来传输医疗数据。该方法通过选择簇头来聚合敏感数据，并有效地广播关键数据。此外，优化的方法使用节能方法管理网络寿命和能量。此外，我们提出了一种多维混沌河豚加密（MCBE）算法来增强系统的安全性。然后根据能耗、数据包传递率、端到端延迟和与 QoS 度量相关的约束等指标计算系统的效率。结果表明，与传统方法相比，所提出的系统在以最小的能量利用率、丢包率、延迟和最大的数据包传递率管理医疗数据质量方面是有效的。我们的方法也被证明比传统系统更安全。

更新日期：2022-08-08

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