US 6,665,271 B1Granted

System for real-time prediction of quality for internet-based multimedia communications

AssigneeTransNexus, Inc.

InventorsStephen A. Thomas, David B. Decker, Rui J. P. de Figueiredo, John V. Martinez, James P. G. Dalton, Jr.

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Abstract

Predicting the quality of a communication carried via a distributed computer network, such as the global Internet, before the initiation of that communication between a pair of endpoints. A prediction system comprises software-implemented processes that can be implemented within an Internet gateway or in an external system that provides prediction results to an Internet gateway. A first process accepts historical data and current environment data and, in response, generates a prediction of objective performance characteristics. A second process accepts the objective performance characteristics and, in response, generates an estimate of the expected quality of communications with an end user. This user quality estimate can be used to support a determination of whether to proceed with the communication or to rely upon an alternative to computer-network supported communications.

Claims15

Dependent claims

A system for generating a prediction result for quality of a multimedia communication for a distributed computer network comprising:

an objective performance prediction module, responsive to historical communication data and current communication environment data, said historical and current data being passively measured, for generating a prediction of objective performance characteristics, wherein the objective prediction module comprises:
a genetic program module, responsive to the historical communication data and the current communication environment data, for performing a feature selection by selecting relevant portions of the historical communication data, wherein the genetic program module is tuned to select the relevant portions of the historical communication data based on selection criteria comprising similarity of network communication paths, the module being also tuned to identify endpoints for the communication and time and date information for the communication;
and
a neural network, responsive to the current communication environment data and the relevant portions of the historical communication data, for generating the prediction of objective performance characteristics for the communication, wherein the neural network comprises an optimal interpolative neural network that generates the prediction of the objective performance characteristics, the neural network comprising:
an input layer comprising inputs β(n−1);
an epoch layer comprising neurons, each having a synaptic weight represented by the vector component of a vector j(n−1) and responsive to the inputs β(n−1) for generating a neuron output;
and
an output variable layer comprising a linear neuron for generating a predicted value of u(n)=M4(n) in response to the output of each neuron on the epoch layer;
and
an estimation module, responsive to the prediction of objective performance characteristics, for generating an estimate of expected quality of the communication.

7 more elements

A computer-implemented process for generating a prediction result for quality of a communication carried over a distributed computer network, comprising the steps:

in response to historical communication data, selecting relevant portions of the historical data based on selection criteria comprising similarity of network communication paths, identity of endpoints for the communication, and time and date information for the communication using a genetic program module;
in response to the relevant portions of historical communication data and current communication environment data, passively generating a prediction of objective performance characteristics using an optimal interpolative neural network, the neural network comprising:
an input layer comprising inputs β(n−1);
an epoch layer comprising neurons, each having a synaptic weight represented by the vector component of a vector j(n−1) and responsive to the inputs β(n−1) for generating a neuron output;
and
an output variable layer comprising a linear neuron for generating a predicted value of u(n)=M4(n) in response to the output of each neuron on the epoch layer;
and
in response to the prediction of objective performance characteristics, generating an estimate of expected quality of the communication.

5 more elements

Dependencies are inferred from the claim text.