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Cloudlet-based for big data collection in body area networks

机译:基于Cloudlet的体积网络大数据收集

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This paper presents a large scale BANs system in the presence of cloudlet-based data collection. The objective is to minimize end-to-end packet cost by dynamically choosing data collection to the cloud using cloudlet based system. The goal is to have the monitored data of BANs to be available to the end user or to the service provider in reliable manner. While reducing packet-to-cloud energy, the proposed work also attempts to minimize the end-to-end packet delay by choosing dynamically a neighbor cloudlet, so that the overall delay is minimized. Then, it will lead to have the monitored data in the cloud in real time manner. Note that, in the absence of network congestions in low data-rate BANs, the storage delays due to data collection manner are usually much larger compared to the congestion delay.
机译:本文在基于Cloudlet的数据收集存在下提出了大规模的禁令系统。目的是使用基于Cloudlet的系统动态地选择数据收集来最小化端到端分组成本。目标是使禁止的监视数据以可靠的方式可用于最终用户或服务提供商。在减少分组到云的能量时,所提出的工作还尝试通过动态地选择邻居Cloudlet来最小化端到端的数据包延迟,从而最小化整体延迟。然后,它将导致在云中实时监视数据。注意,在没有低数据速率禁止的网络拥塞的情况下,与数据收集方式引起的存储延迟通常比拥塞延迟相比大得多。

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