Minimizing Energy Consumption for End-to-End Slicing in 5G Wireless Networks and Beyond

TL;DR

This paper proposes a joint optimization algorithm for end-to-end network slicing in 5G that significantly reduces energy consumption by coordinating RAN and core network resources.

Contribution

It introduces a novel joint power control, server, and link allocation algorithm for E2E slicing that outperforms separate slicing schemes in energy efficiency.

Findings

Achieves 30% energy savings over disjoint schemes

Effectively balances resource sharing between RAN and core networks

Provides a practical solution for energy-efficient 5G slicing

Abstract

End-to-End (E2E) network slicing enables wireless networks to provide diverse services on a common infrastructure. Each E2E slice, including resources of radio access network (RAN) and core network, is rented to mobile virtual network operators (MVNOs) to provide a specific service to end-users. RAN slicing, which is realized through wireless network virtualization, involves sharing the frequency spectrum and base station antennas in RAN. Similarly, in core slicing, which is achieved by network function virtualization, data center resources such as commodity servers and physical links are shared between users of different MVNOs. In this paper, we study E2E slicing with the aim of minimizing the total energy consumption. The stated optimization problem is non-convex that is solved by a sub-optimal algorithm proposed here. The simulation results show that our proposed joint power control, server and link allocation (JPSLA) algorithm achieves 30% improvement compared to the disjoint scheme, where RAN and core are sliced separately.