物联网中医疗保健数据聚合的高能效重复数据删除机制

Future Internet Pub Date : 2024-02-19 DOI:10.3390/fi16020066
Muhammad Nafees Ulfat Khan, Weiping Cao, Zhiling Tang, A. Ullah, Wanghua Pan
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引用次数: 0

摘要

物联网(IoT)的快速发展为包括医疗保健在内的众多领域带来了变革性的进步。基于物联网的医疗保健系统为收集患者的实时数据并适时做出适当决策提供了前所未有的机遇。然而,所部署的传感器在大部分时间都会生成正常读数,并将这些读数传输给簇头(CH)。处理这些大量重复的数据具有相当大的挑战性。现有技术的能耗、存储成本和通信成本都很高。为了克服这些问题,本文提出了一种创新的高能效模糊数据聚合系统(EE-FDAS)。在该系统中,首先要检查传感器是否产生正常或临界读数。在第一种情况下,读数被转换为布尔数字 0。这样减少的数据量只需 1 位数,大大降低了能耗。在第二种情况下,产生不规则读数的传感器以原始的 16 位或 32 位形式传输。然后,数据被汇总并传输到相应的 CH。然后,这些数据被进一步传输到雾服务器,医生可以从那里访问这些数据。最后,数据存储在云服务器中,以供日后使用。为了验证所提出的 EE-FDAS 方案的准确性,我们使用 NS-2.35 进行了大量模拟。结果表明,EE-FDAS 在聚合系数、能耗、数据包丢失率、通信和存储成本方面表现良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Energy-Efficient De-Duplication Mechanism for Healthcare Data Aggregation in IoT
The rapid development of the Internet of Things (IoT) has opened the way for transformative advances in numerous fields, including healthcare. IoT-based healthcare systems provide unprecedented opportunities to gather patients’ real-time data and make appropriate decisions at the right time. Yet, the deployed sensors generate normal readings most of the time, which are transmitted to Cluster Heads (CHs). Handling these voluminous duplicated data is quite challenging. The existing techniques have high energy consumption, storage costs, and communication costs. To overcome these problems, in this paper, an innovative Energy-Efficient Fuzzy Data Aggregation System (EE-FDAS) has been presented. In it, at the first level, it is checked that sensors either generate normal or critical readings. In the first case, readings are converted to Boolean digit 0. This reduced data size takes only 1 digit which considerably reduces energy consumption. In the second scenario, sensors generating irregular readings are transmitted in their original 16 or 32-bit form. Then, data are aggregated and transmitted to respective CHs. Afterwards, these data are further transmitted to Fog servers, from where doctors have access. Lastly, for later usage, data are stored in the cloud server. For checking the proficiency of the proposed EE-FDAS scheme, extensive simulations are performed using NS-2.35. The results showed that EE-FDAS has performed well in terms of aggregation factor, energy consumption, packet drop rate, communication, and storage cost.
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