Virtualization of devices operating in Internet of Things (IoTs) networks allows them to host functions or tasks from different users; these devices can thus execute multiple on demand sensing and data processing services concurrently. Devices, however, have limited energy and operational lifetime. To this end, this paper considers supporting Virtual Network Functions (VNFs) in a Radio Frequency (RF)-charging network with a Hybrid Access Point (HAP). Our aim is to minimize the energy used by the HAP to power devices in order to support deployed VNFs. It outlines a Mixed-Integer Linear Program (MILP) to jointly optimize VNFs placement, routing and link scheduling, and also the HAP’s charging duration. Further, it proposes a heuristic, called Decoupled Greedy Algorithm (DGA), that first assigns VNFs onto devices with the highest energy level before optimizing the HAP’s charging, routing and link schedule. Our results show that DGA has a probability higher than 0.95 to successfully serve a service request. Further, DGA consumes up to 36.43% less energy than competing methods.