Abstract:
A method, computer-readable storage device, and an apparatus for determining a localized service quality in a wireless network are disclosed. For example, the method constructs a tensor comprising a plurality of dimensions to represent data for the localized service quality, receives data for the wireless network that is gathered at a coarse granularity level, populates the tensor in accordance with the data that is gathered, applies an unfolding mechanism to construct a plurality of two dimensional matrices from the tensor, determines for each respective two dimensional matrix of the plurality of two dimensional matrices an approximation for a pre-determined level of accuracy, and populating all entries of each respective two dimensional matrix that are not populated in accordance with the approximation of the respective two dimensional matrix, and determines the localized service quality by applying a folding mechanism across the plurality of two dimensional matrices.
Abstract:
A method includes selecting a study group including a first network element and a second network element of a network, selecting a control group including a third network element, identifying times at which a change is deployed at the first network element and the second network element, time-aligning the change at the first element and the change at the second network element to a common time, performing a statistical analysis that compares the performance of the network before the common time to the performance of the network after the common time, detecting an impact of the change on a performance of the network based on the statistical analysis, and initiating a remedial action when the impact comprises a degradation to the performance.
Abstract:
A new scalable approach to conflict-free deployment of changes across networks. The conflict rules or constraints may be modeled using policies and algorithms to determine an optimized schedule for change deployment.
Abstract:
A method includes selecting a study group including a first network element and a second network element of a network, selecting a control group including a third network element, identifying times at which a change is deployed at the first network element and the second network element, time-aligning the change at the first element and the change at the second network element to a common time, performing a statistical analysis that compares the performance of the network before the common time to the performance of the network after the common time, detecting an impact of the change on a performance of the network based on the statistical analysis, and initiating a remedial action when the impact comprises a degradation to the performance.
Abstract:
A method includes selecting a study group including a first network element and a second network element of a network, selecting a control group including a third network element, identifying times at which a change is deployed at the first network element and the second network element, time-aligning the change at the first element and the change at the second network element to a common time, performing a statistical analysis that compares the performance of the network before the common time to the performance of the network after the common time, detecting an impact of the change on a performance of the network based on the statistical analysis, and initiating a remedial action when the impact comprises a degradation to the performance.
Abstract:
A new scalable approach to conflict-free deployment of changes across networks. The conflict rules or constraints may be modeled using policies and algorithms to determine an optimized schedule for change deployment.
Abstract:
A method of migrating traffic in a network includes receiving, via an API, a request to migrate traffic. The request identifies a target around which the traffic is to be migrated and a peer to which the traffic is to be migrated. The method also includes discovering at least one anchor point based on at least a topology of the network, the target, and the peer. The method includes, based on an identity of the at least one anchor point and the target, identifying a migration mechanism. The method also includes requesting, in accordance with the migration mechanism, that the at least one anchor point facilitate migration of the traffic. The method includes responding, through the API, to the request indicating whether the migration was successful.
Abstract:
A method and apparatus for determining the impact of a software upgrade on a service performance are disclosed. The method obtains call detail records associated with a plurality of mobile user endpoint devices, aggregates each mobile user endpoint device into at least one group, maps each mobile user endpoint device to at least one first aggregate, wherein each aggregate of the at least one first aggregate comprises at least one of: a group established based on the type of each of the mobile user endpoint devices, a group established based on the make of each of the mobile user endpoint devices, or a group established based on the model of each of the mobile user endpoint devices, and identifies a nearest co-occurring software upgrade when a change in a service performance in the communications network is detected based on the at least one first aggregate.
Abstract:
A new scalable approach to conflict-free deployment of changes across networks. The conflict rules or constraints may be modeled using policies and algorithms to determine an optimized schedule for change deployment.
Abstract:
A device detects and diagnoses correlated anomalies of a network. The device includes an anomaly detection module receiving a first data stream including an event-series related to the network. The anomaly detection module executes at least one algorithm to detect a potential anomaly in the event-series. The device further includes a correlating module receiving a second data stream including other event-series related to the network. The correlating module determines whether the potential anomaly is false and determines whether the potential anomaly is a true anomaly.