Abstract
In this paper, network function virtualization (NVF) is identified as a promising key technology that can contribute to energy-efficiency improvement in 5G networks. An optical network supported architecture is proposed and investigated in this work to provide the wired infrastructure needed in 5G networks and to support NFV towards an energy efficient 5G network. In this architecture the mobile core network functions as well as baseband function are virtualized and provided as VMs. The impact of the total number of active users in the network, backhaul/fronthaul configurations and VM inter-traffic are investigated. A mixed integer linear programming (MILP) optimization model is developed with the objective of minimizing the total power consumption by optimizing the VMs location and VMs servers’ utilization. The MILP model results show that virtualization can result in up to 38% (average 34%) energy saving. The results also reveal how the total number of active users affects the baseband virtual machines (BBUVMs) optimal distribution whilst the core network virtual machines (CNVMs) distribution is affected mainly by the inter-traffic between the VMs. For real-time implementation, two heuristics are developed, an Energy Efficient NFV without CNVMs inter-traffic (EENFVnoITr) heuristic and an Energy Efficient NFV with CNVMs inter-traffic (EENFVwithITr) heuristic, both produce comparable results to the optimal MILP results. Finally, a Genetic algorithm is developed for further verification of the results.
Highlights
According to Cisco Visual Networking Index, mobile data traffic will witness seven pleats between 2016 and 2021 and will grow at a Compound Annual Growth Rate (CAGR) of 46% reaching 48.3 exabytes per month by 2021 [2]
Constraints (26) and (27) determine the location of core network virtual machines (CNVMs) by setting the binary variable σpE to 1 if there is a CNVM hosted at node p, where η is equal to 10−9 which is small enough to ensure that the value of σpE is equal to 1 when h∈H λBp,h> 0 and ensure σpE = 0 when h∈H λBp,h= 0
The mixed integer linear programming (MILP) model tends to accommodate baseband unit (BBU) virtual machine’’ (BBUVM) and CNVMs at the IP over WDM network during times of the day when there is a small number of active users
Summary
According to Cisco Visual Networking Index, mobile data traffic will witness seven pleats between 2016 and 2021 and will grow at a Compound Annual Growth Rate (CAGR) of 46% reaching 48.3 exabytes per month by 2021 [2]. Applications, and devices of different kinds and purposes need to send and access data from distributed and centralized servers and databases using public and/or private networks and clouds To support these requirements, 5G mobile networks have to possess intelligence, flexible traffic management, adaptive bandwidth assignment, and at the forefront of these traits is energy efficiency. The work in this paper extends our work in [25], [26] to include a number of factors such as the total number of active users in the network during the day, the backhaul and fronthaul configuration and the required workload for baseband processing It introduces an optical-based framework for energy efficient NFV deployment in 5G networks and provides full MILP details and associated heuristics. Where: wl: is the baseband workload in (GOPS) needed to process one user traffic, A: number of antennas used, M : modulation bits, C: the code rate, L: number of MIMO layers, R: number of physical resource blocks allocated for the user
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