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HCRCaaS: A Handwritten Character Recognition Container as a Service Based on QoS Guarantee Algorithm

机译:HCRCaaS:一种基于QoS保证算法的手写字符识别容器即服务

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摘要

Handwritten character recognition (HCR) is a mainstream mobile device input method that has attracted significant research interest. Although previous studies have delivered reasonable recognition accuracy, it remains difficult to directly embed the advanced HCR service into mobile device software and obtain excellent but fast results. Cloud computing is a relatively new online computational resource provider which can satisfy the elastic resource requirements of the advanced HCR service with high-recognition accuracy. However, owing to the delay sensitivity of the character recognition service, the performance loss in the traditional cloud virtualization technology (e.g., kernel-based virtual machine (KVM)) may impair the performance. In addition, the improper computational resource scheduling in cloud computing impairs not only the performance but also the resource utilization. Thus, the HCR online service is required to guarantee the performance and improve the resource utilization of the HCR service in cloud computing. To address these problems, in this paper, we propose an HCR container as a service (HCRCaaS) in cloud computing. We address several key contributions (1) designing an HCR engine on the basis of deep convolution neutral networks as a demo for an advanced HCR engine with better recognition accuracy, (2) providing an isolated lightweight runtime environment for high performance and easy expansion, and (3) designing a greedy resource scheduling algorithm based on the performance evaluation to optimize the resource utilization under a quality of service (QoS) guaranteeing. Experimental results show that our system not only reduces the performance loss compared with traditional cloud computing under the advanced HCR algorithm but also improves the resource utilization appropriately under the QoS guaranteeing. This study also provides a valuable reference for other related studies.
机译:手写字符识别(HCR)是一种主流的移动设备输入方法,已引起了广泛的研究兴趣。尽管先前的研究已经提供了合理的识别精度,但是仍然难以直接将高级HCR服务嵌入到移动设备软件中并获得出色而快速的结果。云计算是一个相对较新的在线计算资源提供者,可以以较高的识别精度满足高级HCR服务的弹性资源需求。然而,由于字符识别服务的延迟敏感性,传统的云虚拟化技术(例如,基于内核的虚拟机(KVM))的性能损失可能损害性能。另外,云计算中不正确的计算资源调度不仅损害性能,而且损害资源利用率。因此,需要HCR在线服务来保证性能并提高HCR服务在云计算中的资源利用率。为了解决这些问题,本文提出了一种在云计算中使用HCR容器即服务(HCRCaaS)的方法。我们解决了几个关键问题(1)在深度卷积中性网络的基础上设计HCR引擎,作为具有更高识别精度的高级HCR引擎的演示;(2)提供隔离的轻量级运行时环境以实现高性能和易于扩展;以及(3)设计基于性能评估的贪婪资源调度算法,以在保证服务质量(QoS)的情况下优化资源利用率。实验结果表明,在先进的HCR算法下,我们的系统不仅比传统的云计算减少了性能损失,而且在QoS保证下适当地提高了资源利用率。该研究也为其他相关研究提供了有价值的参考。

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