uture processing, storage and communication services will be highly pervasive: people, smart objects, machines and the surrounding space (all embedding devices such as with sensors, RFID tags etc.) will define a highly decentralized cyber environment of resources interconnected by dynamic networks of networks. As communications will extend to cover any combination of ’people, machines and things’, future networks will be increasingly complex and heterogeneous, yet always endorsed with the challenging task of ensuring end-to-end QoS. This paper proposes the groundwork for an advanced cognitive networking paradigm exploitable in future wired and wireless infrastructures: a decentralized cognitive plane to allow for cross-layer, cross-node and cross-network domain self-management, self-control and self-optimization, while being compatible with legacy management and control systems.
Self-optimized Cognitive Network of Networks / A., Manzalini; P. H., Deussen; S., Nechifor; Mamei, Marco; R., Minerva; C., Moiso; A., Salden; T., Wauters; Zambonelli, Franco. - In: THE COMPUTER JOURNAL. - ISSN 0748-9331. - STAMPA. - 54:2(2011), pp. 189-196. [10.1093/comjnl/bxq032]
Self-optimized Cognitive Network of Networks
MAMEI, Marco;ZAMBONELLI, Franco
2011
Abstract
uture processing, storage and communication services will be highly pervasive: people, smart objects, machines and the surrounding space (all embedding devices such as with sensors, RFID tags etc.) will define a highly decentralized cyber environment of resources interconnected by dynamic networks of networks. As communications will extend to cover any combination of ’people, machines and things’, future networks will be increasingly complex and heterogeneous, yet always endorsed with the challenging task of ensuring end-to-end QoS. This paper proposes the groundwork for an advanced cognitive networking paradigm exploitable in future wired and wireless infrastructures: a decentralized cognitive plane to allow for cross-layer, cross-node and cross-network domain self-management, self-control and self-optimization, while being compatible with legacy management and control systems.
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