Abstract: A system and method for network planning with certain guarantees is disclosed. The system receives data characterizing various aspects of a backbone network, such as the nodes of the backbone network, how the nodes are connected by network links, the maximum available capacities of the network assets, network costs, and network asset reliability information. The system also receives data characterizing the requirements of different data communications, or flows, within the backbone network. For example, the backbone network may need to provide a flow a minimum amount of bandwidth or throughput, and the flow may have a minimum required uptime or availability. Based on the network data and flow data, the system generates a network plan that describes how capacity should be provided by different components of the network in a manner that guarantees satisfying flow requirements while balancing other considerations, such as network costs.

Abstract: A system and method for network planning with certain guarantees is disclosed. The system receives data characterizing various aspects of a backbone network, such as the nodes of the backbone network, how the nodes are connected by network links, the maximum available capacities of the network assets, network costs, and network asset reliability information. The system also receives data characterizing the requirements of different data communications, or flows, within the backbone network. For example, the backbone network may need to provide a flow a minimum amount of bandwidth or throughput, and the flow may have a minimum required uptime or availability. Based on the network data and flow data, the system generates a network plan that describes how capacity should be provided by different components of the network in a manner that guarantees satisfying flow requirements while balancing other considerations, such as network costs.

Abstract: The disclosure is directed to a network planning tool for planning a topology of a computer network, e.g., for provisioning network capacity. The network planning tool evaluates various factors, e.g., demand projections between a pair of nodes, existing network topology, existing circuits, failure scenarios, and other constraints, and generates a set of circuits that satisfies various demand projections. The set of circuits is robust under failure scenarios and minimizes latency, costs and/or power consumption involved in satisfying the demand projections. The tool assigns each of the circuits to a spectral resource of a physical communication link, e.g., a wavelength of a fiber optic cable, using which it can propagate data traffic between the pair of nodes.

Abstract: A system and method for network planning with certain guarantees is disclosed. The system receives data characterizing various aspects of a backbone network, such as the nodes of the backbone network, how the nodes are connected by network links, the maximum available capacities of the network assets, network costs, and network asset reliability information. The system also receives data characterizing the requirements of different data communications, or flows, within the backbone network. For example, the backbone network may need to provide a flow a minimum amount of bandwidth or throughput, and the flow may have a minimum required uptime or availability. Based on the network data and flow data, the system generates a network plan that describes how capacity should be provided by different components of the network in a manner that guarantees satisfying flow requirements while balancing other considerations, such as network costs.

Abstract: The disclosure is directed to a network planning tool for planning a topology of a computer network, e.g., for provisioning network capacity. The network planning tool evaluates various factors, e.g., demand projections between a pair of nodes, existing network topology, existing circuits, failure scenarios, and other constraints, and generates a set of circuits that satisfies various demand projections. The set of circuits is robust under failure scenarios and minimizes latency, costs and/or power consumption involved in satisfying the demand projections. The tool assigns each of the circuits to a spectral resource of a physical communication link, e.g., a wavelength of a fiber optic cable, using which it can propagate data traffic between the pair of nodes.

Abstract: Described herein are techniques and systems for online ad campaign tuning using proportional-integral-derivative (PID) controllers, such as proportional (P) controllers and proportional-integral (PI) controllers. Also, described herein are techniques and systems for shortening a learning/tuning phase of a PID controller used for optimizing an online ad campaign.