Optimization-based resource management algorithms with considerations of client satisfaction and high availability in elastic 5g network slices
Journal
Sensors
Journal Volume
21
Journal Issue
5
Pages
1-22
Date Issued
2021
Author(s)
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. ? 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Subjects
Admission control
High availability
Lagrangian relaxation (LR)
Load balancing
Network slicing
Resource allocation
Cloud computing
Mathematical programming
Natural resources management
Queueing networks
Client satisfaction
Cloud computing environments
LaGrangian relaxation
Mathematical programming models
Resource management
Resource management algorithms
Resource management problems
5G mobile communication systems
article
cloud computing
human
leisure
preliminary data
resource allocation
satisfaction
Type
journal article