Abstract: Method and apparatus for network-level anomaly inference in a network is described. In one example, link load measurements are obtained for multiple time intervals. Routing data for the network is obtained. Link level anomalies are extracted using temporal analysis on the link load measurements over the multiple time intervals. Network-level anomalies are inferred from the link-level anomalies.

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 for balancing traffic across paths connecting a network to the Internet using a fractional allocation strategy for distributing the traffic from a congested selected path. The strategy includes: (a) associating the paths j with a counter i; (b) calculating the total initial selected path overload; (c) calculating the selected path load, wherein the load is equal to the initial selected path overload less the sum of the low capacity boundary for i path(s); (d) calculating the portion of the traffic on the selected path to be distributed using a bi-sectional search strategy; (e) distributing a portion of the traffic on the selected path to the other paths; and (f) stopping if there are no more paths (i=j), otherwise increasing the numerical value of the counter by one (1) and go to step (c).

Abstract: A computer-readable storage medium includes operational instructions, that when executed by a processor, cause the processor to receive network configuration data representing a network having a plurality of routers and to identify at least one of the plurality of routers as having a predicted oscillatory behavior based at least partially on the network configuration data.

Abstract: The present invention utilizes a “small-world” network architecture, in which a relatively small number of random cross-links of nodes or vertices in a network can result in small characteristic path lengths, for the transfer of messages between modes or vertices in a telecommunications/computer network regardless of their location. The “small world” principle is usually considered to apply to many biological and social networks, as these systems generally exhibit properties that are not completely regular or completely random but somewhere in between. The present invention applies this small world principle to telecommunications/computer networks.

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: A method for balancing traffic across paths connecting a network to the Internet using a fractional allocation strategy for distributing the traffic from a congested selected path. The strategy includes: (a) associating the paths j with a counter i; (b) calculating the total initial selected path overload; (c) calculating the selected path load, wherein the load is equal to the initial selected path overload less the sum of the low capacity boundary for i path(s); (d) calculating the portion of the traffic on the selected path to be distributed using a bi-sectional search strategy; (e) distributing a portion of the traffic on the selected path to the other paths; and (f) stopping if there are no more paths (i=j), otherwise increasing the numerical value of the counter by one (1) and go to step (c).

Abstract: A method for balancing traffic across paths connecting a network to the Internet using a fractional allocation strategy for distributing the traffic from a congested selected path. The strategy includes: (a) associating the paths j with a counter i; (b) calculating the total initial selected path overload; (c) calculating the selected path load, wherein the load is equal to the initial selected path overload less the sum of the low capacity boundary for i path(s); (d) calculating the portion of the traffic on the selected path to be distributed using a bi-sectional search strategy; (e) distributing a portion of the traffic on the selected path to the other paths; and (f) stopping if there are no more paths (i=j), otherwise increasing the numerical value of the counter by one (1) and go to step (c).

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: A method for balancing traffic across paths connecting a network to the Internet using a fractional allocation strategy for distributing the traffic from a congested selected path. The strategy includes: (a) associating the paths j with a counter i; (b) calculating the total initial selected path overload; (c) calculating the selected path load, wherein the load is equal to the initial selected path overload less the sum of the low capacity boundary for i path(s); (d) calculating the portion of the traffic on the selected path to be distributed using a bi-sectional search strategy; (e) distributing a portion of the traffic on the selected path to the other paths; and (f) stopping if there are no more paths (i=j), otherwise increasing the numerical value of the counter by one (1) and go to step (c).