FOGHORN: Fog-aided wireless networks for communication, caching and computing
Osvaldo Simeone
Professor at NJIT and IEEE fellow
DEIB - Conference Room
January 11th, 2017
11.00 am
Contact:
Mario Martinelli
Umberto Spagnolini
Research Line:
Signal processing for multimedia and telecommunications
Professor at NJIT and IEEE fellow
DEIB - Conference Room
January 11th, 2017
11.00 am
Contact:
Mario Martinelli
Umberto Spagnolini
Research Line:
Signal processing for multimedia and telecommunications
Abstract
On January 11th, 2017 a conference about FOGHORN will be held at DEIB by Osvaldo Simeone.
Fog-aided wireless networks are an emerging class of wireless systems that leverage the synergy and complementarity of cloudifi cation and edge processing, two key technologies in the evolution towards 5G systems and beyond. The operation of fog-aided wireless networks poses novel fundamental research problems pertaining to the optimal management of the communication, caching and computing resources at the cloud and at the edge, as well as to the transmission on the fronthaul network connecting cloud and edge. The solution of these problems challenges the theoretical principles and engineering insights which have underpinned the design of existing networks. In this talk, it will be argued via specific examples that network information theory provides a principled framework to develop fundamental theoretical insights and algorithmic principles on the optimal design of fog-aided networks. Furthermore, signal processing, (non-convex) optimization, queuing and learning aspects will be highlighted.
FOGHORN is ERC Consolidator grant 2017-2022.
Fog-aided wireless networks are an emerging class of wireless systems that leverage the synergy and complementarity of cloudifi cation and edge processing, two key technologies in the evolution towards 5G systems and beyond. The operation of fog-aided wireless networks poses novel fundamental research problems pertaining to the optimal management of the communication, caching and computing resources at the cloud and at the edge, as well as to the transmission on the fronthaul network connecting cloud and edge. The solution of these problems challenges the theoretical principles and engineering insights which have underpinned the design of existing networks. In this talk, it will be argued via specific examples that network information theory provides a principled framework to develop fundamental theoretical insights and algorithmic principles on the optimal design of fog-aided networks. Furthermore, signal processing, (non-convex) optimization, queuing and learning aspects will be highlighted.
FOGHORN is ERC Consolidator grant 2017-2022.
