Biologically inspired self-governance and self-organisation for autonomic networks
Proceedings of the 1st international conference on Bio inspired models of network, information and computing systems
BiRSM: bio-inspired resource self-management for all IP-networks
IEEE Network: The Magazine of Global Internetworking - Special issue on biologically inspired networking
Applying blood glucose homeostatic model towards self-management of IP qos provisioned networks
IPOM'06 Proceedings of the 6th IEEE international conference on IP Operations and Management
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This paper presents a scalable and self-optimizing architecture for Quality-of-Service (QoS) provisioning in the Differentiated Services (DiffServ) framework. The proposed architecture includesadaptive components that model the network as a Semi-MarkovDecision Process (SMDP).Specifically, an ingress node adaptively performs connection admission and flow classification, whileeach core router performs joint bandwidth allocation and buffermanagement for the network classes. The main objective is to maximize average long term network revenue, and at the same time, effectively minimize average long term QoS violations. We use a model-free Reinforcement Learning (RL) technique to find the optimal policy for each DiffServ component. Simulation results show that our proposed solution not only performs well in terms of average long term reward, but is ableto adapt, self-optimize, and self-heal to network changes.