Abstract: A telemetry manager receives, from a network server, global data collection information about network components in an optical network device. The global data collection information includes identifiers for network nodes in the network components from which telemetry data are to be collected, and reporting frequency and encoding format for sending collected telemetry data to the network server. The telemetry manager identifies, from the global data collection information, local data collection information specified for a network component, and sends this information to a telemetry agent in the network component. The telemetry manager receives telemetry data generated by a network node of the network component, where the data is provided according to instructions in the local data collection information. The telemetry manager converts the telemetry data from its native format to an encoding format specified by the global data collection information, and sends the encoded telemetry data to the network server.

Abstract: In accordance with the teachings described herein, systems and methods are provided for optimizing distribution of advertisement information. In one example, call tracking data may be generated from a plurality of telephone calls made to a business entity, where the call tracking data includes geographical information to identify locations from which the plurality of telephone calls originated. A call distribution may be determined from the call tracking data, where the call distribution groups the call tracking data based at least in part on distances between the business entity and the locations from which the plurality of telephone calls originated.

Abstract: In accordance with the teachings described herein, systems and methods are provided for optimizing distribution of advertisement information. In one example, call tracking data may be generated from a plurality of telephone calls made to a business entity, where the call tracking data includes geographical information to identify locations from which the plurality of telephone calls originated. A call distribution may be determined from the call tracking data, where the call distribution groups the call tracking data based at least in part on distances between the business entity and the locations from which the plurality of telephone calls originated.

Abstract: In accordance with the teachings described herein, systems and methods are provided for optimizing distribution of advertisement information. In one example, call tracking data may be generated from a plurality of telephone calls made to a business entity, where the call tracking data includes geographical information to identify locations from which the plurality of telephone calls originated. A call distribution may be determined from the call tracking data, where the call distribution groups the call tracking data based at least in part on distances between the business entity and the locations from which the plurality of telephone calls originated. A probability density function may be generated from the call distribution and used in the generation of the advertisement distribution plan.

Abstract: In accordance with the teachings described herein, systems and methods are provided for optimizing distribution of advertisement information. In one example, call tracking data may be generated from a plurality of telephone calls made to a business entity, where the call tracking data includes geographical information to identify locations from which the plurality of telephone calls originated. A call distribution may be determined from the call tracking data, where the call distribution groups the call tracking data based at least in part on distances between the business entity and the locations from which the plurality of telephone calls originated. A probability density function may be generated from the call distribution and used in the generation of the advertisement distribution plan.

Abstract: Computer-implemented systems and methods are provided for determining an action item from a global set of action items for a plurality of customers based on an objective function, a plurality of individual constraints, and a plurality of aggregate constraints. A plurality of offer sets is generated for each customer. An approximate highest reduced adjusted objective for each of the offer sets for each customer is calculated, and the customers are bucketed based on the highest adjusted objective value associated with each customer. The buckets are collapsed into a single bucket record containing a plurality of aggregate offer set columns, and an aggregate offer set column is selected from each bucket record for each bucket. Each bucket associated with a selected offer set is disaggregated, and the action item included in the selected offer set is stored in a computer-readable memory.

Abstract: Computer-implemented systems and methods are provided for determining an action item from a global set of action items for a plurality of customers based on an objective function, a plurality of individual constraints, and a plurality of aggregate constraints. A plurality of offer sets is generated for each customer. An approximate highest reduced adjusted objective for each of the offer sets for each customer is calculated, and the customers are bucketed based on the highest adjusted objective value associated with each customer. The buckets are collapsed into a single bucket record containing a plurality of aggregate offer set columns, and an aggregate offer set column is selected from each bucket record for each bucket. Each bucket associated with a selected offer set is disaggregated, and the action item included in the selected offer set is stored in a computer-readable memory.