Abstract: A method, a computer readable medium and an apparatus for optimizing a cellular network architecture are disclosed. For example, the method obtains network traffic data for a plurality of different endpoint device types, wherein the network traffic data comprises network traffic data for each of the plurality of different endpoint device types, and predicts a future traffic pattern for one of the plurality of different endpoint device types based on the network traffic data. The method then adjusts a parameter of the cellular network architecture in response to the future traffic pattern predicted for the one of the plurality of different endpoint device types.

Abstract: A method, a computer readable medium and an apparatus for optimizing a cellular network architecture are disclosed. For example, the method obtains network traffic data for a plurality of different endpoint device types, wherein the network traffic data comprises network traffic data for each of the plurality of different endpoint device types, and predicts a future traffic pattern for one of the plurality of different endpoint device types based on the network traffic data. The method then adjusts a parameter of the cellular network architecture in response to the future traffic pattern predicted for the one of the plurality of different endpoint device types.

Abstract: A method, a computer readable medium and an apparatus for optimizing a cellular network architecture are disclosed. For example, the method obtains network traffic data for a plurality of different endpoint device types, wherein the network traffic data comprises network traffic data for each of the plurality of different endpoint device types, and predicts a future traffic pattern for one of the plurality of different endpoint device types based on the network traffic data. The method then adjusts a parameter of the cellular network architecture in response to the future traffic pattern predicted for the one of the plurality of different endpoint device types.

Abstract: A method, a computer readable medium and an apparatus for optimizing a cellular network architecture are disclosed. For example, the method obtains network traffic data for a plurality of different endpoint device types, wherein the network traffic data comprises network traffic data for each of the plurality of different endpoint device types, and predicts a future traffic pattern for one of the plurality of different endpoint device types based on the network traffic data. The method then adjusts a parameter of the cellular network architecture in response to the future traffic pattern predicted for the one of the plurality of different endpoint device types.

Abstract: A method, a computer readable medium and an apparatus for optimizing a cellular network architecture are disclosed. For example, the method obtains network traffic data for a plurality of different endpoint device types, wherein the network traffic data comprises network traffic data for each of the plurality of different endpoint device types, and predicts a future traffic pattern for one of the plurality of different endpoint device types based on the network traffic data. The method then adjusts a parameter of the cellular network architecture in response to the future traffic pattern predicted for the one of the plurality of different endpoint device types.

Abstract: A method is provided for constructing a packet classifier for a computer network system. The method includes: representing a set of rules for packet classification as a directed graph; formulating a plurality of minimization problems from the directed graph, where subgraphs extending from non-terminal nodes in the directed graph represent a minimization problem (i.e., a one-dimensional packet classifier); solving the plurality of minimization problems; combining solutions for the plurality of minimization problems to yield a reduced set of rules which form a reduced packet classifier; and instantiating the reduced packet classifier in a content-addressable memory device.

Abstract: A method, a computer readable medium and an apparatus for optimizing a cellular network architecture are disclosed. For example, the method obtains network traffic data for a plurality of different endpoint device types, wherein the network traffic data comprises network traffic data for each of the plurality of different endpoint device types, and predicts a future traffic pattern for one of the plurality of different endpoint device types based on the network traffic data. The method then adjusts a parameter of the cellular network architecture in response to the future traffic pattern predicted for the one of the plurality of different endpoint device types.

Abstract: A method is provided for constructing a packet classifier for a computer network system. The method includes: representing a set of rules for packet classification as a directed graph; formulating a plurality of minimization problems from the directed graph, where subgraphs extending from non-terminal nodes in the directed graph represent a minimization problem (i.e., a one-dimensional packet classifier); solving the plurality of minimization problems; combining solutions for the plurality of minimization problems to yield a reduced set of rules which form a reduced packet classifier; and instantiating the reduced packet classifier in a content-addressable memory device.