QoS4IVSaaS: a QoS management framework for intelligent video surveillance as a service

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• 作者：Weishan Zhang ; Pengcheng Duan ; Xiaodan Xie ; Feng Xia…
• 关键词：Anomaly detection ; Stream processing ; QoS ; CPU ; GPU collaboration
• 刊名：Personal and Ubiquitous Computing
• 出版年：2016
• 出版时间：October 2016
• 年：2016
• 卷：20
• 期：5
• 页码：795-808
• 全文大小：2,212 KB
• 刊物类别：Computer Science
• 刊物主题：User Interfaces and Human Computer Interaction
  
• 出版者：Springer London
• ISSN：1617-4917
• 卷排序：20

文摘

Quality of service (QoS) is critical for real-time intelligent video surveillance as a service (IVSaaS) platform, which is both computation intensive and data intensive by nature. However, there is scarce work on a QoS framework for IVSaaS platform. In this paper, we propose QoS for intelligent video surveillance as a service, a QoS framework to make computing resources highly available. In the framework, multiple metrics such as throughput, loads of CPU/GPU, memory and IO are taken into account with different time series models to enhance the adaptivity of different video services. A model selection algorithm is proposed to choose the model that achieves the best performance under various error indicators. At the same time, a resource abnormality detection algorithm is designed to detect anomalies when a service is underperformed. Evaluation results show that the proposed QoS framework can successfully ensure QoS by dynamically scheduling computing resources.