Optimization-Based Resource Management Algorithms with Considerations of Client Satisfaction and High Availability in Elastic 5G Network Slices

Abstract

A combined edge and core cloud computing environment is a novel solution in 5G network slices. The clients’ high availability requirement is a challenge because it limits the possible admission control in front of the edge cloud. This work proposes an orchestrator with a mathematical programming model in a global viewpoint to solve resource management problems and satisfying the clients’ high availability requirements. The proposed Lagrangian relaxation-based approach is adopted to solve the problems at a near-optimal level for increasing the system revenue. A promising and straightforward resource management approach and several experimental cases are used to evaluate the efficiency and effectiveness. Preliminary results are presented as performance evaluations to verify the proposed approach’s suitability for edge and core cloud computing environments. The proposed orchestrator significantly enables the network slicing services and efficiently enhances the clients’ satisfaction of high availability.

An Optimization-Based Orchestrator for Resource Access and Operation Management in Sliced 5G Core Networks

“…A mathematical model is formulated to solve network operational problems with elastic access control, scheduling, and migration mechanisms. The motivation and objective are extended from the previous work [ 20 ] dealing with a network operation problem, not only from a resource planning perspective. The operation is divided into slices with many time slots in the evaluation period—additionally, the available hosts scheduling with migration to adjust into active hosts or servers.…”

“…The extra migration effort and active hosts are calculated as a problem to migrate resources or shutdown hosts for power saving. Accordingly, the problem formulation is extended from previous work [ 20 ]. The unbalanced supply and demand inspire this study during peak traffic hours.…”

“…At the beginning, the idea is to relax complicated constraints into the primal problem and extend feasible solution regions to simplify the primal problem. The primal problem is transformed into an LR problem which is associated with Lagrangian multipliers [ 20 ]. Then, the LR problem can be divided into several independent sub-problems using decomposition methods associated with their decision variables and constraints.…”

“…However, the extra migration effort and active hosts are calculated as a problem to migrate resources or shutdown hosts for power saving in limited resources. Accordingly, the problem formulation is extended from previous work [ 20 ]. The objective function includes access control variables for task assignment, host on-off variables, and migration variables to maximize system revenue with the proposed scheduling heuristics among allocated time slots.…”

“…This work is to concentrate on the detailed operation for practical evaluation. The main contributions of this work compared briefly to the previous work [ 20 ] include.…”