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Microservice Based Video Cloud Platform with Performance-Aware Service Path Selection

机译:具有性能感知服务路径选择的基于微服务的视频云平台

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Microservice based cloud architecture becomes a promising solution to deal with the challenges of large-scale intelligent video applications. However, the current service selection methods usually do not consider both the fine-grained online service capability and the features of video tasks, and this will result in the degradation of the overall efficiency of the service composition. In this paper, we propose a novel Performance-aware Service PAth Selection (PSPAS) approach for the microservice based video cloud computing platform. Firstly, we establish a fine-grained time estimation model which synthetically considers the processing capability of microservice instances, the characteristics of video processing tasks, and the data transfer conditions between microservice instances. Then, based on the proposed performance model, we search and update the optimal microservice path by using the shortest path algorithm. Finally, the experiment evaluation results demonstrate the effectiveness of our method.
机译:基于微服务的云架构成为解决大规模智能视频应用挑战的有前途的解决方案。然而,当前的服务选择方法通常既不考虑细粒度的在线服务能力也不考虑视频任务的特征,这将导致服务组合的整体效率下降。在本文中,我们为基于微服务的视频云计算平台提出了一种新颖的性能感知服务速率选择(PSPAS)方法。首先,我们建立了一个细粒度的时间估计模型,该模型综合考虑了微服务实例的处理能力,视频处理任务的特征以及微服务实例之间的数据传输条件。然后,基于提出的性能模型,我们使用最短路径算法搜索和更新最佳微服务路径。最后,实验评估结果证明了该方法的有效性。

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