LAUSR

This paper presents an algorithm/architecture and Hardware/Software co-designs for implementing a digital edge computing layer on a Zynq platform in the context of the Internet of Multimedia Things (IoMT). Traditional cloud computing is no longer suitable for applications that require image processing due to cloud latency and privacy concerns. With edge computing, data are processed, analyzed, and encrypted very close to the device, which enable the ability to secure data and act rapidly on connected things. The proposed edge computing system is composed of a reconfigurable module to simultaneously compress and encrypt multiple images, along with wireless image transmission and display functionalities. A lightweight implementation of the proposed design is obtained by approximate computing of the discrete cosine transform (DCT) and by using a simple chaotic generator which greatly enhances the encryption efficiency. The deployed solution includes four configurations based on HW/SW partitioning in order to handle the compromise between execution time, area, and energy consumption. It was found with the experimental setup that by moving more components to hardware execution, a timing speedup of more than nine times could be achieved with a negligible amount of energy consumption. The power efficiency was then enhanced by a ratio of 7.7 times.