医疗保健4.0中用于雾计算的高效非基于dht的基于rc的体系结构

Indranil Roy, Reshmi Mitra, Nick Rahimi, B. Gupta
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引用次数: 0

摘要

云计算功能彻底改变了医疗保健数据爆炸式增长的远程处理方式。然而,当数据在远程服务器中处理和存储时,基于云的分析功能会受到缺乏上下文感知和不必要的访问延迟问题的困扰。新兴的雾计算网络基础设施层可以通过使存储、处理和网络更靠近传感器节点来减少昂贵的延迟。由于医疗数据和服务类型的日益多样化,连接到雾节点的基于传感器的健康监测设备非常需要高效和安全的体系结构。在本文中,我们提出了基于发布/订阅和基于兴趣/资源的非基于dhs的点对点(P2P)基于rc的资源发现体系结构。发布/订阅通信模型提供了一种可伸缩的方式来实时处理大量数据和消息,同时允许对消息进行细粒度访问控制,从而实现更高的安全性。我们的二层覆盖网络由(1)一个包含代表特定资源类型的组头的传输环和(2)一个完全连接的对等体组组成。我们的理论分析表明,我们的搜索延迟与对等体的数量无关。此外,组内数据查找协议的复杂性是恒定的,组间数据查找的复杂性是O(n),其中n是网络中存在的资源类型的总数。总体而言,它使系统能够以灵活,经济高效且安全的方式处理医疗物联网系统的大数据吞吐量。
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Efficient Non-DHT-Based RC-Based Architecture for Fog Computing in Healthcare 4.0
Cloud-computing capabilities have revolutionized the remote processing of exploding volumes of healthcare data. However, cloud-based analytics capabilities are saddled with a lack of context-awareness and unnecessary access latency issues as data are processed and stored in remote servers. The emerging network infrastructure tier of fog computing can reduce expensive latency by bringing storage, processing, and networking closer to sensor nodes. Due to the growing variety of medical data and service types, there is a crucial need for efficient and secure architecture for sensor-based health-monitoring devices connected to fog nodes. In this paper, we present publish/subscribe and interest/resource-based non-DHT-based peer-to-peer (P2P) RC-based architecture for resource discovery. The publish/subscribe communication model provides a scalable way to handle large volumes of data and messages in real time, while allowing fine-grained access control to messages, thus enabling heightened security. Our two − level overlay network consists of (1) a transit ring containing group-heads representing a particular resource type, and (2) a completely connected group of peers. Our theoretical analysis shows that our search latency is independent of the number of peers. Additionally, the complexity of the intra-group data-lookup protocol is constant, and the complexity of the inter-group data lookup is O(n), where n is the total number of resource types present in the network. Overall, it therefore allows the system to handle large data throughput in a flexible, cost-effective, and secure way for medical IoT systems.
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