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Self- Management of Cognitive Future Internet Elements (Self-NET)
Start date: 01 May 2008, End date: 31 Dec 2010 PROJECT  FINISHED 

Self-NET aims to introduce, design and validate an innovative paradigm for cognitive self-managed elements of the Future Internet. The present Internet model is based on clear separation of concerns between protocol layers, with intelligence moved to the edges, and with the existent protocol pool targeting user and control plane operations with less emphasis on management tasks.Self-NET shall engineer the Future Internet based on cognitive behaviour with a high degree of autonomy, by proposing the operation of self-managed Future Internet elements around a novel feedback-control cycle. The Self-NET proposed Distributed Cognitive Cycle of System Management shall facilitate promotion of distributed management over a hierarchical distribution of management and (re)configuration cognitive cycles, breaking down the execution and decision making levels to (autonomic) network elements, network domain types and up to the service provider realm. Moreover, Self-NET shall study integrated solutions for knowledge management within autonomic elements, including knowledge distribution among the various autonomic elements, as well as a coordination scheme for the cooperation among different network domains. Self-NET shall propose a framework for the transition of traditional monolithic approaches for management actions and protocol stack design to more flexible and dynamic schemes, by introducing autonomic models for localised management decisions. Furthermore, Self-NET shall provide a peer-to-peer style distribution of responsibilities among self-governed elements of the Future Internet, therefore overcoming the barrier of current client-server in the operation of mobility management, broadcast/multicast, and quality of service mechanisms.The consortium shall develop a prototyping environment to test the applicability and robustness of Self-NET solutions. In parallel, simulation campaigns shall verify the scalability and performance sustainability of Self-NET artefacts.
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