Online Cloud Offloading Using Heterogeneous Enhanced Remote Radio Heads

Abstract

This paper studies the cloud offloading gains of using heterogeneous enhanced remote radio heads (eRRHs) and dual-interface clients in fog radio access networks (F-RANs). First, the cloud offloading problem is formulated as a collection of independent sets selection problem over a network coding graph, and its NP-hardness is shown. Therefore, a computationally simple online heuristic algorithm is proposed, that maximizes cloud offloading by finding an efficient schedule of coded file transmissions from the eRRHs and the cloud base station (CBS). Furthermore, a lower bound on the average number of required CBS channels to serve all clients is derived. Simulation results show that our proposed framework that uses both network coding and a heterogeneous F-RAN setting enhances cloud offloading as compared to conventional homogeneous F-RANs with network coding.