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A cloud-based interference-aware remote health monitoring system for non-hospitalized patients

机译:非住院患者的基于云的干扰感知远程健康监测系统

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Distance health monitoring is becoming an attractive option for both the patients and the medical sector staff. However, these systems face many design challenges including the large amount of processed data, users' mobility, and network coverage area. Accordingly, integrating cloud computing with Wireless Body Area Networks (WBANs) is amongst the best solutions to promote health monitoring systems. In this paper, we propose a cloud-based real-time remote health monitoring system. Several novel techniques are developed to optimize the performance of the proposed system. First, we utilize the concept of data classification and aggregation to reduce the traffic flow in the cloud. Second, a dynamic channel assignment policy is developed to distribute the users' WBANs among the available frequency channels to manage interference. Third, to optimize the delay of the delivered data a delay-aware routing metric is proposed to be used in the multi-hop routing. In addition, this metric is further utilized by the association protocols used by the WBANs to connect with the cloud. The simulation results prove the efficiency of the proposed architecture in optimizing the end-to-end delay, managing interference, maximizing the network capacity, and tracking the mobility of the users.
机译:距离健康监测正在成为患者和医疗部门工作人员的有吸引力的选择。然而,这些系统面临许多设计挑战,包括大量处理数据,用户的移动性和网络覆盖区域。因此,通过无线体积网络(WBANs)集成云计算是促进健康监测系统的最佳解决方案。在本文中,我们提出了一种基于云的实时远程健康监测系统。开发了几种新颖的技术来优化所提出的系统的性能。首先,我们利用数据分类和聚合的概念来减少云中的流量。其次,开发了动态信道分配策略以在可用频率信道中分配用户的WBANs来管理干扰。第三,为了优化传递的数据的延迟,提出了在多跳路由中使用延迟感知路由度量。此外,该度量通过WBANS使用的关联协议进一步利用与云连接的关联协议。仿真结果证明了所提出的体系结构在优化端到端延迟,管理干扰,最大化网络容量以及跟踪用户的移动性时的效率。

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