Cloudlet-based for big data collection in body area networks

Muhannad Quwaider, Y. Jararweh
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引用次数: 51

Abstract

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.
基于云计算的人体区域网络大数据采集
提出了一种基于云数据采集的大规模ban系统。目标是通过使用基于cloudlet的系统动态选择数据收集到云来最小化端到端数据包成本。目标是以可靠的方式将ban的监测数据提供给最终用户或服务提供者。在减少数据包到云能量的同时,所提出的工作还试图通过动态选择邻居云来使端到端数据包延迟最小化,从而使总体延迟最小化。然后,它将导致监控数据实时存储在云中。请注意,在低数据速率ban中没有网络拥塞的情况下,由于数据收集方式引起的存储延迟通常比拥塞延迟大得多。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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