Title: Turbo:Improving Image Building for Docker Containers
With the increasing use of Docker, customized Docker images are becoming more and more common, but unfortunately, building an image is very slow. We pull 137 different images in Docker Hub that are downloaded more than one hundred thousand times to evaluate the building time overheads. We use these Docker images to analyze the building process in detail, studying the time and storage space overheads. We find that duplicated data almost reaches 60% of different Docker images. The size of downloaded data for updating an image is up to 12.7 times the real changes between the different versions of one image. According to these findings, we propose an approach to improve the utilization of duplicate data for speeding up the image building and design a generic system named Turbo. Our experimental results show that Turbo speeds up the image building by 3.1x and saves
the space overheads by up to 41.89%.
Song Jiang received the Ph.D in Computer Science, College of William and Mary in June 2004. He currently is an associate professor at The University of Texas at Arlington.His many research results have been adopted by well-known open source communies. Token-Ordered LRU algorithm has been officily adopted in the Linux Kernel since version 2.6. Linux that is the most popular open-source operating system. The Clock-pro replacement algorithm has been officially adopted in the NetBSD kernel. The LIRS replacement algorithm has been officially adopted in MySQL. MySQL is the world's most popular open source database software used by Google and Wikipedia. Dr.Song Jiang is engaged in System infrastructure for big data, in particular, data management systems, file and storage systems, and I/O performance in high-performance computing, and has published more than 70 papers in international conferences and journals. His research was funded by the National Natural Science Foundation of the United States and the Argonne National Laboratory.