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Evaluating the Scalability of a Big Data IoT Cloud Solution

机译:评估大数据IoT云解决方案的可扩展性

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This paper explores the performance benefits of using a specific cloud computing platform for scalable big data solution for IoT sensors. In particular, the Microsoft Azure platform was used for conducting the experiments, measuring the processing speed of the available hardware for variable size of streamed data packets.We have set two research questions. First, to determine what is the effect of the packet size on the performance, and second, if scalability can improve the performance. Our experiments show that if the packets arrive in multiple machines that operate independently, one will benefit with saving a great amount of processing time. Even though the performance dropped with the increase of the packet size, it was not as critical as if using a single machine to process the great amount of streamed data.
机译:本文探讨了使用特定的云计算平台为物联网传感器提供可扩展的大数据解决方案的性能优势。特别是,使用Microsoft Azure平台进行实验,测量可变大小的流数据包时可用硬件的处理速度。我们提出了两个研究问题。首先,确定数据包大小对性能的影响是什么,其次,可伸缩性是否可以改善性能。我们的实验表明,如果数据包到达多台独立运行的机器中,则可以节省大量处理时间,这将使您受益匪浅。尽管性能随着数据包大小的增加而下降,但它并不像使用一台机器来处理大量流数据那样关键。

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