Energy efficient network function virtualization in 5G networks

Abstract

A Number of merits could be brought by network function virtualization (NFV) such as scalability, on demand allocation of resources, and the efficient utilization of network resources. In this paper, we introduce a framework for designing an energy efficient architecture for 5G mobile network function virtualization. In the proposed architecture, the main functionalities of the mobile core network which include the packet gateway (P-GW), serving gateway (S-GW), mobility management entity (MME), policy control and charging role function, and the home subscriber server (HSS) functions are virtualized and provisioned on demand. We also virtualize the functions of the base band unit (BBU) of the evolved node B (eNB) and offload them from the mobile radio side. We leverage the capabilities of gigabit passive optical networks (GPON) as the radio access technology to connect the remote radio head (RRH) to new virtualized BBUs. We consider the IP/WDM backbone network and the GPON based access network as the hosts of virtual machines (VMs) where network functions will be implemented. Two cases were investigated; in the first case, we considered virtualization in the IP/WDM network only (since the core network is typically the location that supports virtualization) and in the second case we considered virtualization in both the IP/WDM and GPON access network. Our results indicate that we can achieve energy savings of 22% on average with virtualization in both the IP/WDM network and GPON access network compared to the case where virtualization is only done in the IP/WDM network. INTRODUCTIONThe current mobile system has evolved from circuit-switched based analogue voice network to a formidable system supporting hundreds of thousands of various applications and a very huge number of users. We are just at the dawn of the conversion to ubiquitous high data rate network that connects anything to anything anytime and anywhere. Therefore, the next generation mobile network will not only connect people, but anything that needs the use of its resources. Various devices will join this network such as medical devices, meteorological equipment, traffic and security cameras, household appliances, etc. As a result, the next generation mobile network will affect many spheres of human life and the growth in traffic will continue during the 5G era beyond 2020 [1,2]. Mobile operators and service providers will have to deal with a 1000 fold increase in traffic compared to the levels in 2010 [3] and they have to properly address a number of challenges due to this huge amount of traffic such as bandwidth requirements and power consumption. In order to address the power consumption challenges, in [4] we have proposed an energy efficient virtual network embedding (EEVNE) approach for cloud computing networks. In [5] we have introduced a framework for energy efficient cloud computing over IP/WDM networks. We have examined energy efficient future HDTV in [6] and investigated the role of physical topology optimization on energy efficiency ...

On Maximizing Energy and Spectral Efficiencies Using Small Cells in 5G and Beyond Networks

“…From (16) and (17), it can be found that capacity and hence SE is a linearly increasing function of L, whereas (18) and (19) indicate that the value of EE is relatively high when L is small and is low when L is large, resulting in EE a decreasing function of L. Hence, at a certain value of L = L * , EE and SE curves must intersect each other. Since any value of L greater than L * causes improvement in both SE and EE performances, an optimal value of EE, as well as SE, can be defined by considering a value of L higher than the value of L=L * at the point of intersection and can be derived as follows:…”

“…However, recently, environmental protection and energy-saving have also become potential issues raised by global communities, resulting in asking researchers for shifting focus towards energy-efficient network design approaches [13]. Consequently, numerous research studies, e.g., [13][14][15][16][17][18][19][20], have already addressed the issue of EE in mobile networks. Hence, due to increasing the energy consumption from large-scale deployment of small cells [21], in addition to SE, EE has also been considered as one of the key performance metrics for the design of future fifth-generation (5G) and beyond mobile systems [22][23][24].…”

“…Note that, even though transceiver 1 operates at the reused spectrum of the macrocell of MNO 1 itself, this spectrum is considered in estimating SE. This is because we consider evaluating the system-level performance of MNO 1, not the performance of in-building SBSs only, which takes into account both the licensed macrocell spectrum as well as the spectrum of in-building SBSs of MNO 1 as given by (17).…”

Softwarization and Optimization for Sustainable Future Mobile Networks: A Survey

“…They emphasize on the need for transparency among virtual BSs of the same physical infrastructure. An architecture for virtualizing both RAN and core network functions with NFV is proposed in [46]. Here RRHs are directly connected to the core of the network and all BBU and core network functions are executed on Virtual Machines (VMs) on demand basis.…”

A framework for energy efficient NFV in 5G networks

“…They argued the current framework and wireless access infrastructure and their capabilities to meet the 5G energy efficiency. In this paper we extend the virtualization architecture that was introduced in our previous work in [8], by investigating a large range of virtual machine workloads with the presence of inter Ð traffic communication between the virtual machines. Beside that, we investigate a wide range of traffic reduction factors which are caused by base band virtual machines (BBUVM) and their effect on the power consumption.…”