Increasing Data Capacity through Compression
Information consumption is continually on the rise, but telecommunications infrastructure has hit capacity—progress may lie in compression. Global mobile data traffic grew 81 percent in 2013 alone, but efforts to accommodate this growth have mainly been aimed at increasing the capacity of the infrastructure. This includes laying fiber and other technological advances that enable the infrastructure to carry more bits. Yet this approach of simply moving more bits to each person now appears to be facing diminishing returns, and the most cost-effective investments in physical infrastructure have already been made. In contrast, there has been less attention paid to how data compression can reduce the number of bits that must be communicated.
Aaron B. Wagner, Electrical and Computer Engineering, proposes that increases in per-capita information consumption could be driven by improvements in compression. His research examines how to harness these gains in compression, especially network gains. The work focuses on lossy compression—a class of methods for encoding data—for two simple networks that are not well understood. For both problems, Wagner’s lab seeks to determine the information-theoretic rate-distortion tradeoffs for a practically important class of instances. The project also contributes to improved STEM education through the development of adoptable course materials for a graduate-level course on information theory and data compression.