In the context of future Cloud Radio Access Net- works (CRAN), optical networks will play an important role to provide the required transport capacity between cell-sites and processing pools, especially for future 5G scenarios. For instance, using CPRI fronthaul technologies a single antenna element can generate data up to 24.3Gbps even with current configurations of radio transmissions, and it is expected to generate up to Tbps with the advance of technology. So, the transport segment of a 5G network needs to be accurately planned to accommodate all the generated traffic. In this work, we propose the use of a Passive Optical Network (PON) jointly with the emergent paradigms of Fog Computing and Network Function Virtualization (NFV) to energy-efficiently support the high traffic transported in emergent mobile networks in an hybrid architecture called Cloud/Fog RAN (CF-RAN) that allows local and remote baseband processing. We introduce an Integer Linear Programming (ILP) model to schedule the processing of CPRI demands among the processing nodes of the network and turn on or off processing functions on demand. Our approach is able to accommodate demands on the nodes of the network in the most energy efficient way. We compare our results with CRAN and distributed architectures (DRAN) and show that an energy efficient planning can achieve considerable gains in power consumption.