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