Method and apparatus for self-learning of VPNS from combination of unidirectional tunnels in MPLS/VPN networks

摘要

A technique is provided for implementing deep-packet inspection (DPI) services in a MPLS/VPN configured computer network. The technique employs a novel self-learning algorithm that analyzes data packets belonging to different unidirectional tunnels in the MPLS/VPN network and determines whether the analyzed data packets transport data in the same VPN. If so, the unidirectional tunnels containing the analyzed data packets are associated with a common layer-2 identification (L2ID) value. Unlike conventional flow-classification procedures, the inventive technique classifies a data packet by first associating the data packet with a L2ID value and then classifying the packet as belonging to a particular data flow based on a novel 6-tuple consisting of a conventional 5-tuple plus the packet's L2ID value. Because unidirectional tunnels corresponding to the same application data flow transport data packets having the same set of 6-tuple values, DPI services can apply application-level policies to classified data packets consistent with their 6-tuple flow classifications.