Data Compression with a Time Limit

In this paper, we explore a framework to identify an optimal choice of compression algorithms that enables the best allocation of computing resources in a large-scale data storage environment: our goal is to maximize the efficiency of data compression given a time limit that must be observed by the compression process. We tested this approach with lossless compression of one-dimensional data (text) and two-dimensional data (images) and the experimental results demonstrate its effectiveness. We also extended this technique to lossy compression and successfully applied it to the lossy compression of two-dimensional data.