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Face recognition applications for airport security and surveillance can benefit from the collaborative coupling of mobile and cloud computing as they become widely available today. This paper discusses the authors' work with the design and implementation of face recognition applications using their mobile-cloudlet-cloud architecture named MOCHA and its initial performance results. The challenge lies with how to perform task partitioning from mobile devices to cloud and distribute compute load among cloud servers (cloudlet) to minimize the response time given diverse communication latencies and server compute powers. Their preliminary simulation results show that optimal task partitioning algorithms significantly affect response time with heterogeneous latencies and compute powers.
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