CStorage: An efficient classification-based image storage system in cloud datacenters

Image storage systems are designed to support images sharing and retrieving applications, especially for smartphone and other mobile devices. Existing image storage systems store images in random data servers without considering their similarities. When a front-end server sends out an image query, it receives similar images from a large number of data servers, causing possible network incast congestion and long query latency. To solve this problem, we propose CStorage, an efficient classification-based image storage system. In CStorage, similar images are stored in the same data server. Thus, a front-end server receives query results from a single data server, which reduces the occurrence of incast congestion as well as the image retrieval latency. CStorage also leverages the deep learning technique to cluster images and provides a high precision and recall rates. Experimental results show the effectiveness of CStorage in reducing image retrieval latency and improving precision and recall rates of searching results.