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Accelerating smart eHealth services execution at the fog computing infrastructure

机译:在雾计算基础架构上加速智能eHealth服务的执行

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Fog computing improves the execution of computationally intensive services for remote client nodes as part of the data processing is performed close to the location where the results will be delivered. As opposed to other services running on smart cities, a major challenge of eHealth services on the fog is that they typically span multiple computational activities performing big data processing over sensible information that must be protected. Using the capacities of current processors can improve the servicing of remote patient nodes. This paper presents the design and validation of a framework that improves the service time of selected activities at the fog servers; precisely, of those activities requested by remote patients. It exploits the capacities of current processors to parallelize specific activities that can be run on reserved cores, and it relies on the quality of service guarantees of data distribution platforms to improve communication and response times to mobile patients. The proposed approach is validated on a prototype implementation of simulated computationally-intensive eHealth interactions, decreasing the response time by 4x when core reservation is activated.
机译:雾计算改善了远程客户端节点的计算密集型服务的执行,因为数据处理的一部分在靠近要传递结果的位置执行。与运行在智慧城市上的其他服务相反,雾中的eHealth服务的主要挑战在于,它们通常会跨多个计算活动,对必须保护的敏感信息执行大数据处理。利用当前处理器的容量可以改善对远程患者节点的服务。本文提出了一个框架的设计和验证,该框架可以改善雾服务器上选定活动的服务时间。确切地说,是偏远患者要求的那些活动。它利用当前处理器的能力来并行化可以在预留核心上运行的特定活动,并且它依靠数据分发平台的服务质量保证来改善与移动患者的通信和响应时间。该方法在模拟计算密集型eHealth交互的原型实现中得到了验证,当激活核心预留时,响应时间减少了4倍。

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