EdgeBOL: Automating Energy-savings for Mobile Edge AI

Jose A. Ayala-Romero, Andres Garcia-Saavedra, Xavier Costa-Perez & George Iosifidis
Supporting Edge AI services is one of the most exciting features of future mobile networks. These services involve the collection and processing of voluminous data streams, right at the network edge, so as to offer real-time and accurate inferences to users. However, their widespread deployment is hampered by the energy cost they induce to the network. To overcome this obstacle, we propose a Bayesian learning framework for jointly configuring the service and the Radio Access...
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