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

Claim 1

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)=M 4 (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.

Claim 2

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)=M 4 (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.