We propose a scalable Internet system for continuous collection of crowd-sourced video from devices such as Google Glass. Our hybrid cloud architecture, GigaSight, is effectively a Content Delivery Network (CDN) in reverse. It achieves scalability by decentralizing the collection infrastructure using cloudlets based on virtual machines (VMs). Based on time, location, and content, privacy sensitive information is automatically removed from the video. This process, which we refer to as denaturing, is executed in a user-specific VM on the cloudlet. Users can perform content-based searches on the total catalog of denatured videos. Our experiments reveal the bottlenecks for video upload, denaturing, indexing, and contentbased search. They also provide insight on how parameters such as frame rate and resolution impact scalability.
For video applications, a scalable system that allows users to perform content-based searches on continuous collection of crowdsourced video was proposed in REF .
Scalable crowd-sourcing of video from mobile devices
MobiSys '13
Computer Science