With rapid growth of producing high-resolution digital contents such as Full HD, 4K, and 8K movies, the demand for low cost and high throughput sharing of content files is increasing at digital content productions. In order to meet this demand, we have proposed DRIP (Distributed chunks Retrieval and Integration Procedure), a storage and retrieval mechanism for large file sharing using forward error correction (FEC) and global dispersed storage. DRIP was confirmed that it contributes to low cost and high throughput sharing. This paper describes the design and implementation of Content Espresso, a distributed large file sharing system for digital content productions using DRIP, and presents performance evaluations. We set up experimental environment using 79 physical machines including 72 inexpensive storage servers, and evaluate file metadata access performance, file storage/retrieval performance, FEC block size, and system availability by emulating global environments. The results confirm that Content Espresso has capability to deal with 15,000 requests per second, achieves 1 Gbps for file storage, and achieves more than 3 Gbps for file retrieval. File storage and retrieval performance are not significantly affected by the network conditions. Thus, we conclude that Content Espresso is capable of a global scale file sharing system for digital content productions.
ASJC Scopus subject areas
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
- Artificial Intelligence