Abstract: Certain exemplary embodiments comprise a method comprising: for selected traffic that enters a backbone network via a predetermined ingress point and is addressed to a predetermined destination, via a dynamic tunnel, automatically diverting the selected traffic from the predetermined ingress point to a processing complex; and automatically forwarding the selected traffic from the processing complex toward the predetermined destination.

Abstract: Certain exemplary embodiments comprise a method comprising: for selected traffic that enters a backbone network via a predetermined ingress point and is addressed to a predetermined destination, via a dynamic tunnel, automatically diverting the selected traffic from the predetermined ingress point to a processing complex; and automatically forwarding the selected traffic from the processing complex toward the predetermined destination.

Abstract: Certain exemplary embodiments comprise a method comprising: for selected traffic that enters a backbone network via a predetermined ingress point and is addressed to a predetermined destination, via a dynamic tunnel, automatically diverting the selected traffic from the predetermined ingress point to a processing complex; and automatically forwarding the selected traffic from the processing complex toward the predetermined destination.

Abstract: A signature-based traffic classification method maps traffic into preselected classes of service (CoS). By analyzing a known corpus of data that clearly belongs to identified ones of the preselected classes of service, in a training session the method develops statistics about a chosen set of traffic features. In an analysis session, relative to traffic of the network where QoS treatments are desired (target network), the method obtains statistical information relative to the same chosen set of features for values of one or more predetermined traffic attributes that are associated with connections that are analyzed in the analysis session, yielding a statistical features signature of each of the values of the one or more attributes. A classification process then establishes a mapping between values of the one or more predetermined traffic attributes and the preselected classes of service, leading to the establishment of QoS treatment rules.

Abstract: Two regularized estimators that avoid the pathologies associated with variance estimation are disclosed. The regularized variance estimator adds a contribution to estimated variance representing the likely error, and hence ameliorates the pathologies of estimating small variances while at the same time allowing more reliable estimates to be balanced in the convex combination estimator. The bounded variance estimator employs an upper bound to the variance which avoids estimation pathologies when sampling probabilities are very small.

Abstract: A method is disclosed for implementing and reporting network measurements between a source of probe packets and an element, such as a router. The invention exploits commonly implemented features on commercial elements. By exploiting these features, the expense of deploying special purpose measurement devices can be avoided. In one aspect of the invention, a plurality of probe packets is transmitted in a packet network with each of the probe packets having the same key and the same aggregation characteristic. A report is then received from an instructionless element regarding the plurality of probe packets, thereby enabling measurement of a parameter of the packet network.

Abstract: A signature-based traffic classification method maps traffic into preselected classes of service (CoS). By analyzing a known corpus of data that clearly belongs to identified ones of the preselected classes of service, in a training session the method develops statistics about a chosen set of traffic features. In an analysis session, relative to traffic of the network where QoS treatments are desired (target network), the method obtains statistical information relative to the same chosen set of features for values of one or more predetermined traffic attributes that are associated with connections that are analyzed in the analysis session, yielding a statistical features signature of each of the values of the one ore more attributes. A classification process then establishes a mapping between values of the one or more predetermined traffic attributes and the preselected classes of service, leading to the establishment of QoS treatment rules.

Abstract: A signature-based traffic classification method maps traffic into preselected classes of service (CoS). By analyzing a known corpus of data that clearly belongs to identified ones of the preselected classes of service, in a training session the method develops statistics about a chosen set of traffic features. In an analysis session, relative to traffic of the network where QoS treatments are desired (target network), the method obtains statistical information relative to the same chosen set of features for values of one or more predetermined traffic attributes that are associated with connections that are analyzed in the analysis session, yielding a statistical features signature of each of the values of the one or more attributes. A classification process then establishes a mapping between values of the one or more predetermined traffic attributes and the preselected classes of service, leading to the establishment of QoS treatment rules.

Abstract: A method and apparatus for the estimation of traffic matrices in a network are disclosed.

Abstract: Two regularized estimators that avoid the pathologies associated with variance estimation are disclosed. The regularized variance estimator adds a contribution to estimated variance representing the likely error, and hence ameliorates the pathologies of estimating small variances while at the same time allowing more reliable estimates to be balanced in the convex combination estimator. The bounded variance estimator employs an upper bound to the variance which avoids estimation pathologies when sampling probabilities are very small.

Abstract: Two regularized estimators that avoid the pathologies associated with variance estimation are disclosed. The regularized variance estimator adds a contribution to estimated variance representing the likely error, and hence ameliorates the pathologies of estimating small variances while at the same time allowing more reliable estimates to be balanced in the convex combination estimator. The bounded variance estimator employs an upper bound to the variance which avoids estimation pathologies when sampling probabilities are very small.

Abstract: Traffic measurement should make it possible to obtain the spatial flow of traffic through the domain, i.e., the paths or trajectories followed by packets between any ingress and egress point of the domain. A method of sampling packet trajectories in a packet switching network allows the direct inference of traffic flows through a measurement domain by observing the trajectories of a subset of all packets traversing the network. A method which assumes that the measurement domain does not change comprises the steps of selecting packets for sampling in accordance with a sampling function of the packet content and generating a practically unique label for each sampled packet. The method does not rely on routing state, its implementation cost is small, and the measurement reporting traffic is modest and can be controlled precisely. Using the same hash function will yield the same sample set of packets in the entire domain, and enables us to reconstruct packet trajectories.

Abstract: A method is disclosed for implementing and reporting network measurements between a source of probe packets and an element, such as a router. The invention exploits commonly implemented features on commercial elements. By exploiting these features, the expense of deploying special purpose measurement devices can be avoided. In one aspect of the invention, a plurality of probe packets is transmitted in a packet network with each of the probe packets having the same key and the same aggregation characteristic. A report is then received from an instructionless element regarding the plurality of probe packets, thereby enabling measurement of a parameter of the packet network.

Abstract: The present invention provides apparatus for sampling data flows in a data network in order to estimate a total data volume in the network. Sampling the data flows in the data network reduces the network resources that must be expended by the network to support the associated activity. The present invention enables the service provider of the data network to control sampled volumes in relation to the desired accuracy. The control can be either static or can be dynamic for cases in which the data volumes are changing as a function of time.

Abstract: A method and apparatus for the estimation of traffic matrices in a network are disclosed. Mechanisms are disclosed for measuring traffic volume from a plurality of ingress points to a plurality of egress points in a large scanl network, such as an IP backbone network. The traffic matrix is advantageously inferred from widely available link load measurements such as SNMP data.

Abstract: The invention provides apparatus and methods for a Virtual Private Network (VPN) in a network that offers a simple user interface for efficient utilization of network resources. The VPN is defined for a specified set of endpoints each of which is associated with a single “hose.” A hose provides access to the VPN through an access point which may be a node of the network, for example. The hose is a single interface to the VPN for communication to all other endpoints of the VPN. The VPN achieves network resource allocation efficiency by exploiting resource sharing possibilities via multiplexing routing paths between endpoints and dynamic resource allocation techniques that permit real time resource allocation resizing. When a VPN is established with a VPN service provider, the routing paths between the endpoints of the VPN is optimized for multiplexing opportunities so that resource allocations between nodes along routing paths within the IP network is reduced to a minimum.

Abstract: The present invention provides a method and apparatus for sampling data flows in a data network in order to estimate a total data volume in the network. Sampling the data flows In the data network reduces the network resources that must be expended by the network to support the associated activity. The present Invention enables the service provider of the data network to control sampled volumes in relation to the desired accuracy. The control can be either static or can be dynamic for cases in which the data volumes are changing as a function of time.

Abstract: The invention provides apparatus and methods for a Virtual Private Network (VPN) in a network that offers a simple user interface for efficient utilization of network resources. The VPN is defined for a specified set of endpoints each of which is associated with a single “hose.” A hose provides access to the VPN through an access point which may be a node of the network, for example. The hose is a single interface to the VPN for communication to all other endpoints of the VPN. The VPN achieves network resource allocation efficiency by exploiting resource sharing possibilities via multiplexing routing paths between endpoints and dynamic resource allocation techniques that permit real time resource allocation resizing. When a VPN is established with a VPN service provider, the routing paths between the endpoints of the VPN is optimized for multiplexing opportunities so that resource allocations between nodes along routing paths within the IP network is reduced to a minimum.

Abstract: Traffic measurement should make it possible to obtain the spatial flow of traffic through the domain, i.e., the paths or trajectories followed by packets between any ingress and egress point of the domain. A method of sampling packet trajectories in a packet switching network allows the direct inference of traffic flows through a measurement domain by observing the trajectories of a subset of all packets traversing the network. A method which assumes that the measurement domain does not change comprises the steps of selecting packets for sampling in accordance with a sampling function of the packet content and generating a practically unique label for each sampled packet. The method does not rely on routing state, its implementation cost is small, and the measurement reporting traffic is modest and can be controlled precisely. Using the same hash function will yield the same sample set of packets in the entire domain, and enables us to reconstruct packet trajectories.

Abstract: The present invention provides a method for sampling data flows in a data network in order to estimate a total data volume in the network. Sampling the data flows in the data network reduces the network resources that must be expended by the network to support the associated activity. The present invention enables the service provider of the data network to control sampled volumes in relation to the desired accuracy. The control can be either static or can be dynamic for cases in which the data volumes are changing as a function of time.