The Vision of Autonomic Computing
Computer
Reinforcement Learning in Autonomic Computing: A Manifesto and Case Studies
IEEE Internet Computing
Steps toward self-aware networks
Communications of the ACM - Barbara Liskov: ACM's A.M. Turing Award Winner
Coalition formation through learning in autonomic networks
GameNets'09 Proceedings of the First ICST international conference on Game Theory for Networks
IWSOS '09 Proceedings of the 4th IFIP TC 6 International Workshop on Self-Organizing Systems
Policy conflict analysis for diffserv quality of service management
IEEE Transactions on Network and Service Management
Hi-index | 0.00 |
In order to meet the requirements of emerging services, the future Internet will need to be flexible, reactive and adaptive. Network management functionality is essential in providing dynamic reactiveness and adaptability but current network management approaches have limitations and are inadequate to meet the relevant demands. In search for a paradigm shift, recent research efforts have been focusing on self-management principles. The PhD work presented in this paper proposes to investigate how autonomic principles can be extended and applied to fixed networks for quality of service (QoS) and performance management. The paper describes the two main research issues that will be addressed, namely (a) coordinated decision making in distributed environments, and (b) lightweight learning capabilities, and highlights their importance on realistic application scenarios for the emerging Internet.