Abstract: A method performed by a processor in a network function virtualization infrastructure includes determining an amount of resources consumed by a virtual network function subsequent to a scaling of the amount of resources in response to an occurrence of a predefined trigger event, determining an amount of time elapsed between the predefined trigger event and a completion of the scaling, determining a key performance indicator value for the virtual network function subsequent to completion of the scaling, evaluating an efficiency of the predefined trigger event that triggers the scaling, based on the amount of resources consumed by the virtual network function subsequent to the scaling, the amount of time elapsed between the detection of the predefined trigger event and completion of the scaling, and the key performance indicator for the virtual network function subsequent to completion of the scaling, and adjusting the predefined trigger event based on the evaluating.

Abstract: A method performed by a processor in a network function virtualization infrastructure includes determining an amount of resources consumed by a virtual network function subsequent to a scaling of the amount of resources in response to an occurrence of a predefined trigger event, determining an amount of time elapsed between the predefined trigger event and a completion of the scaling, determining a key performance indicator value for the virtual network function subsequent to completion of the scaling, evaluating an efficiency of the predefined trigger event that triggers the scaling, based on the amount of resources consumed by the virtual network function subsequent to the scaling, the amount of time elapsed between the detection of the predefined trigger event and completion of the scaling, and the key performance indicator for the virtual network function subsequent to completion of the scaling, and adjusting the predefined trigger event based on the evaluating.

Abstract: In one example, a processing system may support capacity management in a virtualization environment based on hierarchical capacity management. The processing system may maintain a policy for a first capacity agent at a first hierarchical layer. The policy may include a set of key capacity indicators, a capacity limit, and an algorithm. The processing system may obtain, based on the set of key capacity indicators, a set of key capacity indicator information. The processing system may monitor, based on the capacity limit, for a detection of a capacity limit event. The processing system may determine, based on the algorithm, a predicted capacity exhaustion point. The processing system may send, toward a second capacity agent at a second hierarchical layer that is above the first hierarchical layer, the set of key capacity indicator information and the predicted capacity exhaustion point.

Abstract: A method performed by a processor in a network function virtualization infrastructure includes determining an amount of resources consumed by a virtual network function subsequent to a scaling of the amount of resources in response to an occurrence of a predefined trigger event, determining an amount of time elapsed between the predefined trigger event and a completion of the scaling, determining a key performance indicator value for the virtual network function subsequent to completion of the scaling, evaluating an efficiency of the predefined trigger event that triggers the scaling, based on the amount of resources consumed by the virtual network function subsequent to the scaling, the amount of time elapsed between the detection of the predefined trigger event and completion of the scaling, and the key performance indicator for the virtual network function subsequent to completion of the scaling, and adjusting the predefined trigger event based on the evaluating.

Abstract: In one example, a processing system may support capacity management in a virtualization environment based on hierarchical capacity management. The processing system may maintain a policy for a first capacity agent at a first hierarchical layer. The policy may include a set of key capacity indicators, a capacity limit, and an algorithm. The processing system may obtain, based on the set of key capacity indicators, a set of key capacity indicator information. The processing system may monitor, based on the capacity limit, for a detection of a capacity limit event. The processing system may determine, based on the algorithm, a predicted capacity exhaustion point. The processing system may send, toward a second capacity agent at a second hierarchical layer that is above the first hierarchical layer, the set of key capacity indicator information and the predicted capacity exhaustion point.

Abstract: A method performed by a processor in a network function virtualization infrastructure includes determining an amount of resources consumed by a virtual network function subsequent to a scaling of the amount of resources in response to an occurrence of a predefined trigger event, determining an amount of time elapsed between the predefined trigger event and a completion of the scaling, determining a key performance indicator value for the virtual network function subsequent to completion of the scaling, evaluating an efficiency of the predefined trigger event that triggers the scaling, based on the amount of resources consumed by the virtual network function subsequent to the scaling, the amount of time elapsed between the detection of the predefined trigger event and completion of the scaling, and the key performance indicator for the virtual network function subsequent to completion of the scaling, and adjusting the predefined trigger event based on the evaluating.

Abstract: A method performed by a processor in a network function virtualization infrastructure includes determining an amount of resources consumed by a virtual network function subsequent to a scaling of the amount of resources in response to an occurrence of a predefined trigger event, determining an amount of time elapsed between the predefined trigger event and a completion of the scaling, determining a key performance indicator value for the virtual network function subsequent to completion of the scaling, evaluating an efficiency of the predefined trigger event that triggers the scaling, based on the amount of resources consumed by the virtual network function subsequent to the scaling, the amount of time elapsed between the detection of the predefined trigger event and completion of the scaling, and the key performance indicator for the virtual network function subsequent to completion of the scaling, and adjusting the predefined trigger event based on the evaluating.

Abstract: A method performed by a processor in a network function virtualization infrastructure includes determining an amount of resources consumed by a virtual network function subsequent to a scaling of the amount of resources in response to an occurrence of a predefined trigger event, determining an amount of time elapsed between the predefined trigger event and a completion of the scaling, determining a key performance indicator value for the virtual network function subsequent to completion of the scaling, evaluating an efficiency of the predefined trigger event that triggers the scaling, based on the amount of resources consumed by the virtual network function subsequent to the scaling, the amount of time elapsed between the detection of the predefined trigger event and completion of the scaling, and the key performance indicator for the virtual network function subsequent to completion of the scaling, and adjusting the predefined trigger event based on the evaluating.

Abstract: A system includes a receiver configured to receive a first set of element management system data from a first element management system. The first set of element management system data includes first network element data associated with a first network element of the first element management system. The receiver also configured to receive a second set of element management system data from a second element management system. The second set of element management system data includes second network element data associated with a second network element of the second element management system. The system also includes a reformatting component configured to reformat the first set and the second set to generate data having a common data format.

Abstract: A system includes a reformatting component configured to generate element management system data having a common data format by reformatting a first set of element management system data and a second set of element management system data. The system also includes a display component configured to use the element management system data to display network performance metrics via a user interface. The user interface includes at least one regional level view including a list of one or more service markets within each of one or more service regions.

Abstract: A user interface for viewing network system data is provided and includes at least one company level view that includes a list of one or more service regions within a company, at least one regional level view that includes a list of one or more service markets within each of the one or more service regions, and at least one market level view that includes a list of one or more wire centers within the one or more service markets.

Abstract: The present invention discusses a computerized method for managing a communication network through processing data used in a Capacity Management System (CMS) associated with the communication network. A configurable grammar, such as an XML grammar with regular expressions, is used to implement various aspects of network management. Data management includes pre-processing data (transferring data, decompressing data, parsing data), loading data into a relational database, and data analysis. Results of data analysis can be used to determine a network condition, and thereby to enable network management.

Abstract: An IP usage pattern of a first computer system is monitored by a second computer system that is remotely located from the first computer system. The second computer system is associated with an ISP. First parasite software may be identified based on an abnormal change in the IP usage pattern. The abnormal change in the IP usage pattern may be detected by comparing the IP usage pattern to a baseline model of IP usage for the first computer system. Anti-parasite software associated with the first parasite software may be forwarded from the ISP to the first computer system.

Abstract: A user interface for viewing network system data is provided and includes at least one company level view that includes a list of one or more service regions within a company, at least one regional level view that includes a list of one or more service markets within each of the one or more service regions, and at least one market level view that includes a list of one or more wire centers within the one or more service markets.

Abstract: An IP usage pattern of a first computer system is monitored by a second computer system that is remotely located from the first computer system. The second computer system is associated with an ISP. First parasite software may be identified based on an abnormal change in the IP usage pattern. The abnormal change in the IP usage pattern may be detected by comparing the IP usage pattern to a baseline model of IP usage for the first computer system. Anti-parasite software associated with the first parasite software may be forwarded from the ISP to the first computer system.

Abstract: A user interface for viewing network system data is provided and includes at least one company level view that includes a list of one or more service regions within a company, at least one regional level view that includes a list of one or more service markets within each of the one or more service regions, and at least one market level view that includes a list of one or more wire centers within the one or more service markets.

Abstract: An Internet Protocol (IP) usage pattern of a first computer system is monitored by a second computer system remotely located from the first computer system. Based on the monitoring, it is determined if the IP usage pattern is abnormal for the first computer system. If the IP usage pattern is abnormal, an alert signal is generated for the first computer system by the second computer system. The alert message indicates a potential presence of parasite software on the first computer system.

Abstract: A system of evaluating automatic message accounting records associated with telephony calls is disclosed. The system includes correlation logic to collect originating AMA records having an originating call code to identify a record of an originating long distance call and further to collect terminating AMA records that correspond to the collected originating automatic message accounting records. The system also includes evaluation logic to determine when a call may be by-passing terminating access charges by identifying calls that have been correlated with an originating AMA record having the originating code and with a terminating AMA record having a local termination code.

Abstract: In accordance with one aspect of the present invention, a method provides a circuit from a first customer location to a second customer location. The method includes selecting a path-starting node from a network of nodes, and selecting a path-ending node from the network of nodes. The path-starting node is connectable to the first customer location, and the path-ending node is connectable to the second customer location. The method also includes selecting at least one subset of files from a database containing a set of files. Each file of the set of files contains segment data pertaining to a segment that connects a pair of nodes within the network. Each of the at least one subset contains data pertaining to a path from the path-starting node to the path-ending node. If more than one subset of files is selected, selecting an optimal path corresponding to an optimal subset of files.

Abstract: An Internet Protocol (IP) usage pattern of a first computer system is monitored by a second computer system remotely located from the first computer system. Based on the monitoring, it is determined if the IP usage pattern is abnormal for the first computer system. If the IP usage pattern is abnormal, an alert signal is generated for the first computer system by the second computer system. The alert message indicates a potential presence of parasite software on the first computer system.