Name
Abstract | ||
|---|---|---|
In this paper, one proposes an approach to optimize the computational resource utilization of baseband unit pools in a Cloud Radio Access Network. The problem of resource allocation is formulated and solved as a constrained nonlinear optimization one, based on the concept of bargaining in cooperative game theory. The goal is to minimize resource usage by on-demand resource allocation, per instantaneous requirements of base stations, whilst taking Quality of Service into account. In the event of a shortage of resources, implying that not all demand can be served at the same time, baseband units are prioritized with a weighting policy. Real-time requirements and the priority of services being run on a baseband unit are the two contributors in calculating the weight in a timeslot. Lower prior baseband units, however, are always guaranteed to receive a minimum of resources to prevent them from crashes. Simulation results in a heterogeneous services environment show a minimum 83% improvement in allocation efficiency, compared to a fixed resource allocation scheme based on peak-hour traffic demands. Results also confirm that, in case of a resource shortage, 100% of the resources are fairly distributed among baseband units, fairness being governed by the weight of the baseband units in the pool. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/WCNC45663.2020.9120606 | 2020 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC) |
Keywords | DocType | ISSN |
Wireless Communications, Cloud-RAN, Computational Resource Utilization, Resource Allocation Efficiency, Nonlinear Optimization | Conference | 1525-3511 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mojgan Barahman | 1 | 0 | 0.34 |
| Luis M. Correia | 2 | 284 | 55.53 |
| Lúcio S. Ferreira | 3 | 0 | 0.34 |