Firework: Data Processing and Sharing for Hybrid Cloud-Edge Analytics
Firework: Data Processing and Sharing for Hybrid Cloud-Edge Analytics
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DOI：
10.1109/tpds.2018.2812177
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发表时间：
2018-09
影响因子：
5.3
通讯作者：
Quan Zhang;Qingyang Zhang;Weisong Shi;Hong Zhong
中科院分区：
文献类型：
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作者：
Quan Zhang;Qingyang Zhang;Weisong Shi;Hong Zhong
现在，我们正在进入万物互联（IoE）时代，数十亿个传感器和执行器连接到网络。作为最复杂的万物互联应用之一，实时视频分析有望显著改善公共安全、商业智能、医疗保健和生命科学等。然而，以云为中心的视频分析要求所有视频数据必须预加载到集中式群集或云，考虑到IoE设备生成的视频数据的规模，这会遭受高响应延迟和高数据传输成本。此外，由于各种问题，视频数据很少在多个利益相关者之间共享，这限制了利用许多数据源做出明智决策的视频分析的实际部署。此外，没有高效的编程接口供开发人员和用户跨地理上分布的计算资源轻松编程和部署IoE应用。在本文中，我们提出了一个新的计算框架，烟花，它有助于分布式数据处理和共享的万物互联应用程序通过虚拟共享数据视图和服务组合。我们为Firework设计了一个易于使用的编程接口，允许开发人员在Firework上编程。本文介绍了Firework的系统设计、实现和编程接口。视频分析应用程序的实验结果表明，与以云为中心的解决方案相比，Firework减少了高达19.52%的响应延迟和至少72.77%的网络带宽成本。
Now we are entering the era of the Internet of Everything (IoE) and billions of sensors and actuators are connected to the network. As one of the most sophisticated IoE applications, real-time video analytics is promising to significantly improve public safety, business intelligence, and healthcare & life science, among others. However, cloud-centric video analytics requires that all video data must be preloaded to a centralized cluster or the cloud, which suffers from high response latency and high cost of data transmission, given the scale of zettabytes of video data generated by IoE devices. Moreover, video data is rarely shared among multiple stakeholders due to various concerns, which restricts the practical deployment of video analytics that takes advantages of many data sources to make smart decisions. Furthermore, there is no efficient programming interface for developers and users to easily program and deploy IoE applications across geographically distributed computation resources. In this paper, we present a new computing framework, Firework, which facilitates distributed data processing and sharing for IoE applications via a virtual shared data view and service composition. We designed an easy-to-use programming interface for Firework to allow developers to program on Firework. This paper describes the system design, implementation, and programming interface of Firework. The experimental results of a video analytics application demonstrate that Firework reduces up to 19.52 percent of response latency and at least 72.77 percent of network bandwidth cost, compared to a cloud-centric solution.