Abstract: A device may receive historical data and real-time data associated with a troubleshooting service, identify, using a machine learning model, an optimal resolution based on the historical data and the real-time data, and identify, using a graph analytics model, an optimal path of actions based on the optimal resolution. The machine learning model may be trained to identify one of the set of historical issues associated with the unresolved issue, and identify the optimal resolution based on one of the set of historical resolutions associated with the one of the set of historical issues. The graph analytics model may be trained to generate a set of paths of actions based on the historical data, and identify the optimal path based on respective numbers of actions associated with the set of paths. The device may identify optimal action based on the optimal path and the prior action.

Abstract: A device may receive historical data and real-time data associated with a troubleshooting service, identify, using a machine learning model, an optimal resolution based on the historical data and the real-time data, and identify, using a graph analytics model, an optimal path of actions based on the optimal resolution. The machine learning model may be trained to identify one of the set of historical issues associated with the unresolved issue, and identify the optimal resolution based on one of the set of historical resolutions associated with the one of the set of historical issues. The graph analytics model may be trained to generate a set of paths of actions based on the historical data, and identify the optimal path based on respective numbers of actions associated with the set of paths. The device may identify optimal action based on the optimal path and the prior action.

Abstract: A device may receive historical data and real-time data associated with a troubleshooting service, identify, using a machine learning model, an optimal resolution based on the historical data and the real-time data, and identify, using a graph analytics model, an optimal path of actions based on the optimal resolution. The machine learning model may be trained to identify one of the set of historical issues associated with the unresolved issue, and identify the optimal resolution based on one of the set of historical resolutions associated with the one of the set of historical issues. The graph analytics model may be trained to generate a set of paths of actions based on the historical data, and identify the optimal path based on respective numbers of actions associated with the set of paths. The device may identify optimal action based on the optimal path and the prior action.

Abstract: A device may receive historical data and real-time data associated with a troubleshooting service, identify, using a machine learning model, an optimal resolution based on the historical data and the real-time data, and identify, using a graph analytics model, an optimal path of actions based on the optimal resolution. The machine learning model may be trained to identify one of the set of historical issues associated with the unresolved issue, and identify the optimal resolution based on one of the set of historical resolutions associated with the one of the set of historical issues. The graph analytics model may be trained to generate a set of paths of actions based on the historical data, and identify the optimal path based on respective numbers of actions associated with the set of paths. The device may identify optimal action based on the optimal path and the prior action.

Abstract: A system includes an application server that hosts a plurality of enterprise applications and stores enterprise data associated with each of the enterprise applications. A client device executes a client application that can provide access to each of the enterprise applications. The client application includes a memory protection engine that allocates a first memory location for the enterprise data transmitted to the client device so the enterprise data is accessible to each of the plurality of enterprise applications through the client application. A second allocated memory location is allocated for non-enterprise data. A mobile enterprise server transmits the enterprise data to the client device.

Abstract: A system includes an application server that hosts a plurality of enterprise applications and stores enterprise data associated with each of the enterprise applications. A client device executes a client application that can provide access to each of the enterprise applications. The client application includes a memory protection engine that allocates a first memory location for the enterprise data transmitted to the client device so the enterprise data is accessible to each of the plurality of enterprise applications through the client application. A second allocated memory location is allocated for non-enterprise data. A mobile enterprise server transmits the enterprise data to the client device.

Abstract: An approach is provided for monitoring traffic over a network link that is used to provide one or more services to one or more customers. A determination is made regarding whether a failure mode of the network link has occurred by comparing the monitored traffic to predetermined bandwidth criteria. A corrective action to be taken in response to the failure mode is selected, where selection of the corrective action to be taken is determined based on the failure mode. Further corrective actions selected iteratively from a predetermined list of successive actions are applied until the failure modes are addressed.

Abstract: Various embodiments of the present invention are directed to a method for creating a DWDM optical fiber network topology based on a set of demands associated with a region of interest. The demands may be placed on one or more rings in a DWDM optical fiber network based on several Evaluation Function (EF) parameters, which may include Ring COI calculations. EF parameters may include without limitation: (1) a preference for a ring topology solution or partial solution that considers (e.g., routed or skipped) as many demands as possible; (2) a preference for a ring topology solution or partial solution that skips the fewest number of demands; (3) a preference for a ring topology solution or partial solution that produces the highest Ring COI value; and/or (4) a preference for a ring topology solution or partial solution that provides, on average, the fewest number of node hops, i.e., the fewest number of intermediate nodes along various paths between endpoints.

Abstract: An approach is provided for forecasting usage of network links. The method includes determining traffic data values for traffic over a network link that is used to provide one or more services to one or more customers, where the traffic data values are taken at intervals for a predetermined range of time. A historical data set of peak traffic data values is compiled from the traffic data values. A mathematical confidence factor is applied to the peak traffic data values to achieve modified data values, and a time-based weighting factor is applied to the modified data values to achieve further modified data values. And, a forecast trend curve of traffic over the network is calculated using the further modified data values.

Abstract: An approach is provided for network resource growth management. Utilization of a network resource that is hierarchically associated with one or more other network resources is determined. If the utilization exceeds a first predetermined threshold, a growth notification is triggered. The growth notification specifies additional network resources required to modify the utilization of the network resource according to a second predetermined threshold.

Abstract: Various embodiments of the present invention are directed to a method for creating and optimizing a DWDM optical fiber network that is configured to service a set of demands associated with a region of interest.

Abstract: An approach is provided for monitoring traffic over a network link that is used to provide one or more services to one or more customers. A determination is made regarding whether a failure mode of the network link has occurred by comparing the monitored traffic to predetermined bandwidth criteria. A corrective action to be taken in response to the failure mode is selected, where selection of the corrective action to be taken is determined based on the failure mode. Further corrective actions selected iteratively from a predetermined list of successive actions are applied until the failure modes are addressed.

Abstract: An approach is provided for forecasting usage of network links. The method includes determining traffic data values for traffic over a network link that is used to provide one or more services to one or more customers, where the traffic data values are taken at intervals for a predetermined range of time. A historical data set of peak traffic data values is compiled from the traffic data values. A mathematical confidence factor is applied to the peak traffic data values to achieve modified data values, and a time-based weighting factor is applied to the modified data values to achieve further modified data values. And, a forecast trend curve of traffic over the network is calculated using the further modified data values.

Abstract: Various embodiments of the present invention are directed to a method for creating a DWDM optical fiber network topology based on a set of demands associated with a region of interest. The demands may be placed on one or more rings in a DWDM optical fiber network based on several Evaluation Function (EF) parameters, which may include Ring COI calculations. EF parameters may include without limitation: (1) a preference for a ring topology solution or partial solution that considers (e.g., routed or skipped) as many demands as possible; (2) a preference for a ring topology solution or partial solution that skips the fewest number of demands; (3) a preference for a ring topology solution or partial solution that produces the highest Ring COI value; and/or (4) a preference for a ring topology solution or partial solution that provides, on average, the fewest number of node hops, i.e., the fewest number of intermediate nodes along various paths between endpoints.

Abstract: Various embodiments of the present invention are directed to a method for creating and optimizing a DWDM optical fiber network that is configured to service a set of demands associated with a region of interest.