5GPy: A SimPy-based simulator for performance evaluations in 5G hybrid Cloud-Fog RAN architectures

Abstract

The joint cooperation of cloud and fog computing emerges as a new architectural pattern for future 5G networks in order to cope with the increasingly number of mobile elements presented in such networks. Through the use of the cloud, power efficiency can be achieved through centralization of processing. On the other hand, the use of fog processing nodes increases power consumption but helps to decrease the latency of delay-sensitive applications and to increase the coverage of the network. As the use of cloud and fog presents conflicting characteristics, it is important to accurately study their behaviour in order to define the best way to use such a hybrid architecture. In this work we present a three-fold contribution to the study of joint cloud and fog computing architectures. First, we present a hybrid architecture called Cloud-Fog RAN (CF-RAN) that focus on dynamic activation and deactivation of both network and processing resources in order to maintain a balanced operation between the cloud and the fog. Second, we present a performance evaluation model used to analyse the performance of different metrics of CF-RAN. Third, as it is very difficult and costly to build cloud and fog real scenarios, we introduce 5GPy, a SimPy event-driven simulator, publicly available, used to perform small and large scale simulations on architectures such as CF-RAN. We present the architectural details of 5GPy and, by using Integer Linear Program (ILP) and graph-based heuristics to allocate resources in 5G networks, we performed simulations of CF-RAN operation in a small network and in a large network based on a Brazilian city. The results show interesting aspects and trade-offs between cloud and fog computing that were possible to be found with the proposed performance evaluation model and with the 5GPy simulator.