Ribbon Communications Operating Company, Inc.

Movik Networks

Nizar K Purayil

Charles W Boyle

Surya Kumar Kovvali

Vsevolod V Ostapenko

Christopher Leary

Sreenivas Nvr Kaki

Ronald Mark Parker

Sandeep Agarwal

Ramji Raghavan

Krishnan Ramakrishnan

John Hutchins

Mythili Vutukuru

Ankush Gupta

Surya Kumar Kowali

Mahesh Kumaravel

A method performed by a computing system includes collecting information on transactions in a telecommunication system, using the information on transactions to create a plurality of event objects, each of the event objects associated with a telecommunication event, associating each of the event objects with a Key Performance Indicator (KPI), applying the event objects to a plurality of inference functions, each inference functions using the set of parameters as inputs and the KPIs of the event objects as outputs to create a model that infers a relationship between the set of parameters and the KPIs, and analyzing metadata from each of the inference functions to determine which of the set of parameters was used to predict an outcome leading to the KPI.

Most probable cause determination for telecommunication events

A method includes: receiving protocol event data from a plurality of probes within the telecommunication system; determining a most probable cause of a call event from the protocol event data; applying the most probable cause to a trained machine learning algorithm that includes the most probable cause as its input and a telecommunication system score as its output; and in response to an output score from the trained machine learning algorithm, performing a corrective action for a plurality of network users that are expected to be affected by the most probable cause.

Predictive scoring based on key performance indicators in telecommunications system

A method performed by a computing system that collects information on transactions in a telecommunication system includes receiving an event object. The event object includes parameters associated with a telecommunication event. The method further includes classifying the event object, using a classification mechanism, as one of a plurality of Key Performance Indicators (KPIs) by using the parameters, including considering events from multiple protocols for classifying event objects. The method further includes, after classifying the event object, inferring relationships between a set of inputs and a set of outputs, the set of inputs including information types from the event object and the set of outputs including KPIs.

Telecommunication event object classification based on information from multiple protocols

Methods for estimating Subscriber quality of experience (QOE) for mobile users accessing networks for different services from observed data in control and user planes in mobile wireless networks and then summarizing inferences per user, per service, per sector, group of sectors and other aggregate points, and exporting this information for reducing user churn, network planning and network tuning, application adaptation to improve QOE are disclosed. Methods for improving subscriber QOE metrics for certain applications, services and web-sites for improved monetization methods are also presented. The methods facilitate quantifying network goodness from the user application point of view, and exporting triggers to other network elements, such as SON Server, OSS and PCRF, when QOE anomalies are detected. Additionally, this exported information could also trigger content adaptation, delivery optimizations and other actions. Finally, client, server and intermediary enhancements to improve QOE of certain applications in delay/capacity varying networks are presented.

System and methods for estimation and improvement of user, service and network QOE metrics

A network device, capable of understanding communications between an end user and the core network on a RAN network is disclosed. In some embodiments, the device is able to decode the control plane and the user plane. As such, it is able to determine when the end user has requested multimedia content. Once this is known, the device can optimize the delivery of that content in several ways. In one embodiment, the device requests the content from the content server (located in the core network) and transmits this content in a just-in-time manner to the end user. In another embodiment, the device automatically changes the encoding and resolution of the content, based on overall monitored network traffic. In another embodiment, the device automatically selects or modifies the format and resolution options based on overall bandwidth limitations, independent of the end user.

Adaptive chunked and content-aware pacing of multi-media delivery over HTTP transport and network controlled bit rate selection

A packet scheduling method and apparatus with the knowledge of application behavior, anticipated usage/behavior based on the type of content, and underlying transport conditions during the time of delivery, is disclosed. This type of scheduling is applicable to a content server or a transit network device in wireless (e.g., 3G, WIMAX, LTE, WIFI) or wire-line networks. Methods for identifying or estimating rendering times of multi-media objects, segmenting a large media content, and automatically pausing or delaying delivery are disclosed. The scheduling reduces transit network bandwidth wastage, and facilitates optimal sharing of network resources such as in a wireless network.

Growing community of inventors

Bengaluru, India

Nizar K Purayil