This paper focuses on improving network management by exploiting the potential of “doing” of the Active Networks technology, together with the potential of “planning,” which is typical of the artificial intelligent systems. We propose a distributed multiagent architecture for Active Network management, which exploits the dynamic reasoning capabilities of the Situation Calculus in order to emulate the reactive behavior of a human expert to fault situations. The information related to network events is generated by programmable sensors deployed across the network. A logical entity collects this information, in order to merge it with general domain knowledge, with a view to identifying the root causes of faults, and to deciding on reparative actions. The logical inference system has been devised to carry out automated isolation, diagnosis, and even repair of network anomalies, thus enhancing the reliability, performance, and security of the network. Experimental results illustrate the Reasoner capability of correctly recognizing fault situations and undertaking management actions.
Gaglio, S., Gatani, L., Lo Re, G., Urso, A. (2006). A Logical Architecture for Active Network Management. JOURNAL OF NETWORK AND SYSTEMS MANAGEMENT, 14, 127-146 [10.1007/s10922-005-9012-7].
A Logical Architecture for Active Network Management
GAGLIO, Salvatore;GATANI, Luca;LO RE, Giuseppe;URSO, Alfonso
2006-01-01
Abstract
This paper focuses on improving network management by exploiting the potential of “doing” of the Active Networks technology, together with the potential of “planning,” which is typical of the artificial intelligent systems. We propose a distributed multiagent architecture for Active Network management, which exploits the dynamic reasoning capabilities of the Situation Calculus in order to emulate the reactive behavior of a human expert to fault situations. The information related to network events is generated by programmable sensors deployed across the network. A logical entity collects this information, in order to merge it with general domain knowledge, with a view to identifying the root causes of faults, and to deciding on reparative actions. The logical inference system has been devised to carry out automated isolation, diagnosis, and even repair of network anomalies, thus enhancing the reliability, performance, and security of the network. Experimental results illustrate the Reasoner capability of correctly recognizing fault situations and undertaking management actions.File | Dimensione | Formato | |
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