Coded caching is a technique for reducing congestion in communication networks by prefetching content during idle periods and exploiting multicasting opportunities during periods of heavy traffic. Modern content delivery networks are investing very heavily in profiling their users and predicting their preferences, but most of the research in coded caching has focused on minimizing the worst case (i.e., peak) rate in a broadcast link with multiple identically distributed user requests for files of the same size.
This talk presents the first steps towards characterizing the minimal achievable rate of a coded caching scheme with heterogeneous user profiles and file sizes, which is still unknown in general. First, it will explain the main idea behind coded caching and review some of the existing work in this area. Then, it will analyze the case of two users with distinct but overlapping demand sets, providing a complete characterization of their rate capacity under selfish and uncoded prefetching. Additionally, it will also describe explicit prefetching schemes that achieve those capacities with arbitrary (and not necessarily identical) users’ cache capacities. Finally, the talk will propose several heuristic schemes suitable for scenarios with an arbitrary number of heterogeneous user classes. It will analyze their peak and average rates, comparing their performance for different cache capacities and file demand sets.
About Borja Peleato
Borja Peleato received the B.S. degrees in telecommunications and mathematics from the Universitat Politecnica de Catalunya, Barcelona, Spain, in 2007, and the M.S. and Ph.D. degrees in Electrical Engineering from Stanford University, Stanford, CA, USA, in 2009 and 2013, respectively.
He was a visiting student at the Massachusetts Institute of Technology (MIT) in 2006 and a Senior Flash Channel Architect with Proton Digital Systems in 2013. From 2014 to 2020, he was an Assistant Professor in the Electrical and Computer Engineering Department at Purdue University, West Lafayette, IN, USA. In 2020, he was awarded a CONEX-Marie Curie Fellowship and joined the Signal Theory and Communications group at the Universidad Carlos III de Madrid, Leganes, Spain, where he is still employed. In 2022 he received the Ramón y Cajal and the CAM Atraccion de Talento Fellowships, and accepted the latter.
He is an IEEE Senior member and his research interests include wireless communications, autonomous networks, information theory, and convex optimization.
This event will be conducted in English