The Cloudlet Accelerator: Bringing Mobile-Cloud Face Recognition into Real-Time

Abstract

A mobile-cloud architecture provides a practical platform for performing face recognition on a mobile device. However, using a mobile-cloud architecture to perform real-time face recognition presents several challenges including resource limitations and long network delays. In this paper, we determine three approaches for accelerating the execution of the face recognition application by utilizing an intermediate device called a cloudlet. We study in detail one of these approaches, using the cloudlet to perform pre-processing, and quantify the maximum attainable acceleration. Our experimental results show up to a 128x improvement in response time when appropriate cloudlet hardware is used.