The rise of robotics applications demands new cloud architectures that deliver high throughput and low latency. Bin Fan and Shaoshan Liu explain how PerceptIn designed and implemented a cloud architecture to support video streaming and online object recognition tasks and demonstrate how Alluxio supports these emerging cloud architectures.
Bin and Shaoshan also offer an overview of in-home surveillance robots, which require the following features from the cloud: online object detection, video streaming, storage, search, and video playback. These requirements necessitate a storage layer that can handle enormous amount of incoming data, which may end up in different storage systems (including S3, GCS, Swift, HDFS, OSS, GlusterFS, and NFS). ANd when writing and retrieving video feeds, the storage layer must provide high throughout and low latency. To fulfill these requirements, PerceptIn designed and implemented a cloud architecture consisting of the following components:
Alluxio provides two key features that are critical to the success of this architecture. First, it provides high throughput and low latency to support fast retrieval of video feeds. Second, it provides a unified namespace to support many popular storage systems, including S3, GCS, Swift, HDFS, OSS, GlusterFS, and NFS. Alluxio enables more than 650 MB/s throughput, whereas the native filesystem only achieves 120 MB/s (a 5x increase). This throughput is critical as it determines how fast you can write a video feed to storage. If the throughput is too low, then the storage layer may become the bottleneck of the whole multimedia data pipeline.
Alluxio also supports fast retrieval: with Alluxio, you can retrieve a video within 500 milliseconds. However, when the video is stored in remote machines, the latency can be as high as 20 seconds. Using Alluxio to buffer “hot” video data could reduce retrieval latencies by as many as 40 folds. In addition, different users demand different persistent storage underlying Alluxio: some may use HDFS; others may use S3. Without Alluxio, PerceptIn would have to manage multiple interfaces, one for each persistent storage. With Alluxio’s unified namespace, PerceptIn only has to maintain one major interface while supporting many different underlying storage systems.
Bin Fan is a software engineer at Alluxio and a PMC member of the Alluxio project. Previously, Bin worked at Google building next-generation storage infrastructure, where he won Google’s Technical Infrastructure award. He holds a PhD in computer science from Carnegie Mellon University.
Shaoshan Liu is the cofounder and president of PerceptIn, a company working on developing a next-generation robotics platform. Previously, he worked on autonomous driving and deep learning infrastructure at Baidu USA. Shaoshan holds a PhD in computer engineering from the University of California, Irvine.
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