Name
Abstract | ||
|---|---|---|
Cognitive networks are envisaged to provide optimized resource usage in future. While heterogeneity and resource scarcity draw research attention to the wireless part, the rest of the network (mobile backhaul) is rarely considered for these improvements. The future of next generation wireless networks is probable to be all-IP, where a common flexible infrastructure is looking for dynamic autonomous solutions that cognition may provide. This work proposes a novel solution, where the introduction of reinforcement learning over multiprotocol label switching (MPLS) in a differentiated services (DiffServ) mobile backhaul should provide autonomous network adaptation aiming at enhanced QoS capabilities. The proposed solution enables intelligent traffic routing by means of distributed reinforcement learning agents that base decisions on edge-gained experience. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/VETECS.2009.5073831 | VTC Spring |
Keywords | DocType | ISSN |
DiffServ networks,IP networks,cognitive radio,learning (artificial intelligence),mobile radio,multiprotocol label switching,quality of service,telecommunication network management,telecommunication network routing,DiffServ-MPLS mobile networks,QoS capabilities,all-IP networks,cognitive networks,differentiated service mobile backhaul,load management,multiprotocol label switching,next generation wireless networks,reinforcement learning,traffic routing | Conference | 1550-2252 E-ISBN : 978-1-4244-2517-4 |
ISBN | Citations | PageRank |
978-1-4244-2517-4 | 2 | 0.38 |
References | Authors | |
11 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nemanja Vučević | 1 | 39 | 5.15 |
| Jordi Pérez-Romero | 2 | 18 | 4.13 |
| Oriol Sallent | 3 | 72 | 6.14 |
| R. Agustí | 4 | 53 | 3.57 |