Abstract: A method to determine the maximum number of VPNs assignable to plurality of routers in a VPN network. The first step in the method can be specifying a tolerance which is a probability that consumed router memory will exceed available router memory for each router in a plurality of routers. The second step can be computing the consumed router memory on each router in a plurality of routers by summing a route memory, an interface memory, a VPN memory, and a constant memory. The third step can be computing a number [V] of VPNs assigned to the router to insure that, with the specified probability tolerance, the consumed router memory will not exceed the available router memory for each router in a plurality of routers.

Abstract: A method for forming a communications network using routers. The first step is analyzing a router location to determine if the router location is VPN resource constrained or interface-constrained. The VPN resource constrained router network comprises at least at least two groups of routers and the same number of customer groups. The next step is connecting the first group of customers and routers, and the second group of customers and routers, using a round robin connectivity methodology and saving information in each router's database. The interface-constrained router network, comprises no more routers than the value [Q*], wherein [Q*] represents the number of routers that can be used by a group of customers so that VPN resources will not be exhausted faster than interface resources for the group of routers, then connecting customers to the group of routers using a round robin connectivity methodology and saving information in each router's database.

Abstract: A method to determine the maximum number of VPNs assignable to plurality of routers in a VPN network. The first step in the method can be specifying a tolerance which is a probability that consumed router memory will exceed available router memory for each router in a plurality of routers. The second step can be computing the consumed router memory on each router in a plurality of routers by summing a route memory, an interface memory, a VPN memory, and a constant memory. The third step can be computing a number [V] of VPNs assigned to the router to insure that, with the specified probability tolerance, the consumed router memory will not exceed the available router memory for each router in a plurality of routers.

Abstract: The specification describes techniques for evaluating important network performance parameters, for example, call set-up time, for private network-to-network (PNNI) interfaces. These performance parameters are used to determine the optimum size of the peer groups in the PNNI network. Both flat and multi-level networks may be designed using the methods described.

Abstract: A method and apparatus for providing a flexible virtual forwarding table for packet networks are disclosed. For example, the method receives one or more packets from at least one customer endpoint device, where the one or more packets are destined for a destination node. The method then locates a route for routing the one or more packets by consulting one or more virtual forwarding projection tables, wherein each of the one or more virtual forwarding projection tables contains a subset of the routes that are stored in a virtual route forwarding table. Finally, the method forwards the one or more packets towards said destination node using said route.

Abstract: The number of nodes in a private network-to-network interface may be very large. These nodes can be organized in two or more hierarchical levels. Network performance parameters, for example, call set-up time, may be used to determine the optimum number of hierarchical levels for a given PNNI network. A multi-step algorithm is presented for calculating the optimum number of levels in the network for a given number of nodes.

Abstract: Method and apparatus for hierarchical node partitioning for address planning in networks, e.g., PNNI ATM networks to perform judicious definition of peer groups to create a logical partitioning of the ATM switches that increases PNNI routing efficiency and performance.

Abstract: Method and apparatus for hierarchical node partitioning for address planning in networks, e.g., PNNI ATM networks to perform judicious definition of peer groups to create a logical partitioning of the ATM switches that increases PNNI routing efficiency and performance.

Abstract: A method to determine the maximum number of VPNs assignable to plurality of routers in a VPN network. The first step in the method can be specifying a tolerance which is a probability that consumed router memory will exceed available router memory for each router in a plurality of routers. The second step can be computing the consumed router memory on each router in a plurality of routers by summing a route memory, an interface memory, a VPN memory, and a constant memory. The third step can be computing a number [V] of VPNs assigned to the router to insure that, with the specified probability tolerance, the consumed router memory will not exceed the available router memory for each router in a plurality of routers.

Abstract: A method for forming a communications network using routers. The first step is analyzing a router location to determine if the router location is VPN resource constrained or interface-constrained. The VPN resource constrained router network comprises at least at least two groups of routers and the same number of customer groups. The next step is connecting the first group of customers and routers, and the second group of customers and routers, using a round robin connectivity methodology and saving information in each router's database. The interface-constrained router network, comprises no more routers than the value [Q*], wherein [Q*] represents the number of routers that can be used by a group of customers so that VPN resources will not be exhausted faster than interface resources for the group of routers, then connecting customers to the group of routers using a round robin connectivity methodology and saving information in each router's database.

Abstract: The present invention provides a method called, the “cluster method”, for designing an efficient and low cost network that satisfies certain requirements, and in particular, that satisfies the requirement of having a prescribed number of nodes. The method first computes a provably optimal (or near optimal, in some cases) solution to small network design problems with the three following constraints. First, the network must be immune to the failure of a single link. Second, the network diameter cannot exceed a prescribed value. Third, the maximum node degree cannot exceed a prescribed value. The solutions to the small problems are combined, using an optimization technique called “dynamic programming,” to design large networks subject to the three above constraints. This cluster method is a hierarchical method, since the solutions to small problems are combined to solve a large problem. The resulting large network design meets the given survivability, diameter and maximum node degree constraints.

Abstract: The specification describes techniques for evaluating important network performance parameters, for example, call set-up time, for private network-to-network (PNNI) interfaces. These are used to determine the optimum size of the peer groups in the PNNI network.

Abstract: The specification describes techniques for evaluating important network performance parameters, for example, call set-up time, for different network topologies. These are used to determine the optimum number of hierarchical levels for a given PNNI network.

Abstract: The present invention provides a method called, the “cluster method”, for designing an efficient and low cost network that satisfies certain requirements, and in particular, that satisfies the requirement of having a prescribed number of nodes. The method first computes a provably optimal (or near optimal, in some cases) solution to small network design problems with the three following constraints. First, the network must be immune to the failure of a single link or node. Second, the network diameter cannot exceed a prescribed value. Third, the maximum node degree cannot exceed a prescribed value. The solutions to the small problems are combined, using an optimization technique called “dynamic programming,” to design large networks subject to the three above constraints. This cluster method is a hierarchical method, since the solutions to small problems are combined to solve a large problem.