Load balancing and resource management in distributed B5G networks

Abstract

The traffic explosion and the rising of diverse requirements lead to many challenges for the mobile networks on flexibility, scalability, and deployability. To meet the challenges, end-to-end network slicing and mobile edge computing (MEC) are introduced into beyond fifth-generation (B5G) mobile communication networks. However, the edge servers are limited by computing and data processing capabilities, how to implement efficient load balancing and resource management in data center are still challenges for B5G network slices. In this paper, we first propose a model of load balancing for B5G network slices and formulate a total cost minimization problem, considering the energy cost, processing delay, backhaul bandwidth cost, and revenue loss associated with the backhaul delay. Then, a distributed algorithm based on Proximal Jacobian Alternating Direction Method of Multipliers (PJ-ADMM) is proposed to solve the formulated problem. Simulations are conducted to show that the proposed algorithm are effective in terms of reducing network operating cost.