Introduction to the issue on signal processing for big data

Abstract

With the Internet, social media, wireless mobile devices, and pervasive sensors continuously collecting massive amounts of data, we undoubtedly live in an era of “data deluge.” Learning from such huge volumes of data however, promises ground-breaking advances in science and engineering along with consequent improvements in quality of life. Indeed, mining information from big data could limit the spread of epidemics and diseases, identify trends in financial and e-markets, unveil topologies and dynamics of emergent social-computational systems, accelerate brain imaging, neuroscience and systems biology models, and also protect critical infrastructure including the power grid and the Internet's backbone network. While Big Data can be definitely perceived as a big blessing, big challenges also arise with large-scale datasets. Given these challenges, ample signal processing opportunities arise. The articles in this special section explore novel modeling approaches, algorithmic advances along with their performance analysis, as well as representative applications of Big Data analytics to address practical challenges, while revealing fundamental limits and insights on the analytical trade-offs involved.