Content-Centric Wireless Networks

  • Principal investigator: Suhas Diggavi (UCLA)
  • Sponsor: National Science Foundation (NSF)
  • Project timeline: 2014-2017

Project synopsis

This project seeks to advance our fundamental understanding of content-centric wireless networks. Communication networks are traditionally connection-centric, i.e., establish a reliable data connection between end-nodes. Recently, there has been a significant shift in network usage, where the users’ intent is to access some specific (broadband and video) content rather than connect to a specific node. While there have been significant advances in enabling higher data rates in connection-centric wireless networks, the strategic use of storage along with jointly designed data delivery has received less attention in wireless networks. The goal of this project is to develop an information-theoretic framework for a content-centric approach to wireless, that enables a strategic positioning and use of storage jointly optimized with wireless information flow. This framework will be based on a content-distribution capacity region, which will characterize the region of transmission size versus cache storage, for different wireless network topologies, with user demands following from non-uniform content popularity profiles. We will develop both a theory and explicit strategies for content-centric wireless networks using a broad set of tools ranging from Shannon theory, network algorithms and coding as well as ideas from content-distribution network system design. The project also promotes the training of research engineers: we will integrate the research results into curricula by creating novel courses combining the underlying concepts in wireless network information flow, storage and wireless content-delivery systems.

The research in this project, if successful, will contribute to the fundamental sciences of information flow and storage in wireless networks. Given the exponentially rising demand for wireless data, driven by media content, the results will serve as an enabler for wireless broadband content distribution that leverages dimensions beyond brute spectrum allocation.