Abstract: Systems and methods may use a math programming model for designing an edge cloud network. The edge cloud network design may depend on various factors, including the number of edge cloud nodes, edge cloud node location, or traffic coverage, among other things.

Abstract: Systems and methods may use a math programming model for designing an edge cloud network. The edge cloud network design may depend on various factors, including the number of edge cloud nodes, edge cloud node location, or traffic coverage, among other things.

Abstract: Systems and methods may use a math programming model for designing an edge cloud network. The edge cloud network design may depend on various factors, including the number of edge cloud nodes, edge cloud node location, or traffic coverage, among other things.

Abstract: Systems and methods may use a math programming model for designing an edge cloud network. The edge cloud network design may depend on various factors, including the number of edge cloud nodes, edge cloud node location, or traffic coverage, among other things.

Abstract: Systems and methods may use a math programming model for designing an edge cloud network. The edge cloud network design may depend on various factors, including the number of edge cloud nodes, edge cloud node location, or traffic coverage, among other things.

Abstract: Systems and methods may use a math programming model for designing an edge cloud network. The edge cloud network design may depend on various factors, including the number of edge cloud nodes, edge cloud node location, or traffic coverage, among other things.

Abstract: Systems and methods may use a math programming model for designing an edge cloud network. The edge cloud network design may depend on various factors, including the number of edge cloud nodes, edge cloud node location, or traffic coverage, among other things.

Abstract: A method and apparatus for resizing a trunk in a network are disclosed. For example, the method sets one or more target utilization levels for one or more trunks, and gathers trunk load data from one or more switches in the network in accordance with a pre-determined time period. The method evaluates the trunk load data in accordance with one or more trigger points for resizing the one or more trunks, wherein the one or more trigger points is based on the one or more target utilization levels. The method then resizes the one or more trunks if the one or more trigger points are reached or exceeded.

Abstract: A method of capacity planning in a network includes assigning a class of service to each packet of data on the network. Each class of service is also assigned a grade of service for different network conditions. A class bandwidth is calculated for each class of service under each network condition by multiplying an expected load for each class of service by the associated grade of service under each of the network conditions. A network condition bandwidth is calculated for each network condition by adding together the class bandwidths for all classes. A network capacity is predicted based upon the largest network condition bandwidth. A network management apparatus can perform the method.

Abstract: A method of capacity planning in a network includes assigning a class of service to each packet of data on the network. Each class of service is also assigned a grade of service for different network conditions. A class bandwidth is calculated for each class of service under each network condition by multiplying an expected load for each class of service by the associated grade of service under each of the network conditions. A network condition bandwidth is calculated for each network condition by adding together the class bandwidths for all classes. A network capacity is predicted based upon the largest network condition bandwidth. A network management apparatus can perform the method.

Abstract: A method and apparatus for resizing a trunk in a network are disclosed. For example, the method sets one or more target utilization levels for one or more trunks, and gathers trunk load data from one or more switches in the network in accordance with a pre-determined time period. The method evaluates the trunk load data in accordance with one or more trigger points for resizing the one or more trunks, wherein the one or more trigger points is based on the one or more target utilization levels. The method then resizes the one or more trunks if the one or more trigger points are reached or exceeded.

Abstract: A network includes a space chattering mechanism for maximizing server throughput under overload conditions. The server provides control messages to various network traffic sources, which can require differing control instructions.

Abstract: A network includes a space chattering mechanism for maximizing server throughput under overload conditions. The server provides control messages to various network traffic sources, which can require differing control instructions.

Abstract: A network includes a space chattering mechanism for maximizing server throughput under overload conditions. The server provides control messages to various network traffic sources, which can require differing control instructions.

Abstract: A network includes a space chattering mechanism for maximizing server throughput under overload conditions. The server provides control messages to various network traffic sources, which can require differing control instructions.

Abstract: A method is provided for designing a hierarchical architecture for a synchronous optical network (SONET) given a plurality of demand nodes at which communications traffic originates and at least one destination node at which the communications traffic is collected for transmission to a switch.

Abstract: This invention relates to a method and apparatus for throttling request messages to an overloaded database and for throttling overload traffic to a particular destination. The database sends a gap value to the sources of messages or traffic; following any message or call to the destination, no messages will be sent or calls to the destination completed for one gap interval. In a departure from the prior art, the gap interval, a function of the number of request messages flushed or overload calls to the destination is not recurrently calculated anew, but is instead recurrently adjusted from its previous value. Advantageously, this arrangement permits a relatively stable value of the gap to be maintained and reduces overhead for preliminary processing of request messages that cannot be handled.