QQA : Quantitative Quality Assesment (or pseudo-subjective quality)

in @rmor’s evaluation,22-23 october 2003 QQA: QuantitativeQuality Assesment(or pseudo-subjective quality)

Global view • QQA: Quantitative Quality Assessment(or pseudo-subjective quality assessment) • Quantitative evaluation of quality • as perceived by the observer, • automatically, and, if necessary, in real time. • Idea: to use specific learning tools (particular open queuing networks) capturing the way human react, taking measurable quantities as inputs. • Objective reached. Tested on: video and audio separately. Applications under analysis: control; monitoring. Extensions under analysis:to pricing, to diffserv architectures, to traffic prediction and bandwidth negotiation, to control issues in radio access networks, to home networking. @rmor – INRIA Rennes

The method • Use a particularly performant statistical learning tool:a product form queueing network with positive and negative customers (a G-network, or RNN) • to learn how humans react face to a multimedia stream • after having passed through a packet network. • Key points: • identify appropriate input variables (loss rate, source bit rate, …) • a configuration = a set of values for the input variables • with each configuration associate a quality value given by a set of real observers under controlled conditions • find a G-network with the mapping: • input variables = external arrival rates (of positive customers) • only one queue sends customers outside, and the quality is mapped to the load of this node • for each configuration, the load of the exit node is (very) close to the quality given by the human observers @rmor – INRIA Rennes

stream of voice, music, video, multimedia, … Source Receiver Example of implementation for video IP network RNN asking the source for BR, FR, RA measuring LR, CLP @rmor – INRIA Rennes

G. Rubino, DR INRIA S. Mohamed,PhD (January 2003),now temporary engineer M. Varela, PhD student(starting his 2nd year) F. Cervantes, J. Incera, prof. at ITAM, Mexico, for dynamic bandwidth negotiation For the remaining extensions: B. Tuffin, CR INRIA,Y. Hezel, PhD student,for pricing issues J.-M. Bonnin, MdC ENST B,for mobile applications D. Ros, MdC ENST B,J. Orozco, PhD student,for control in diffserv L. Toutain, MdC ENST B,S. Ben Hamida, PhD student,for control in home networking(conditional to STREP accepted) People @rmor – INRIA Rennes

G. Rubino, DR INRIA S. Mohamed,PhD (January 2003),now temporary engineer M. Varela, PhD student(starting his 2nd year) F. Cervantes, J. Incera, prof. at ITAM, Mexico, for dynamic bandwidth negotiation For the remaining extensions: B. Tuffin, CR INRIA,Y. Hayel, PhD student,for pricing issues J.-M. Bonnin, MdC ENST B,for mobile applications D. Ros, MdC ENST B,J. Orozco, PhD student,for control in diffserv L. Toutain, MdC ENST B,S. Ben Hamida, PhD student,for control in home networking(conditional to STREP accepted) People @rmor – INRIA Rennes

Publications • “A Study of Real--time Packet Video Quality Using Random Neural Networks”.S. Mohamed and G. Rubino. IEEE Transactions On Circuits and Systems for Video Technology, Vol. 12, No. 12, December 2002. • “Performance evaluation of real-time speech through a packet network: a Random Neural Networks based approach”.S. Mohamed, G. Rubino and M. Varela.To appear in Performance Evaluation. • Other publications in • Infocom 2001 • ICOIN’15, 2001 • PDPTA’2001 @rmor – INRIA Rennes

Next future • develop a video-conference tool with automatic quality control based on QQA • transform the approach into an industrial product • Phillips? France Telecom? • extend the approach in couplingtraffic predictionwithdynamic negotiation of bandwidth • idea: put a dynamic bandwidth negotiator at the edge of the core • use QQA and traffic prediction (+ a pricing scheme) to allow the user to negotiate with the provider • apply QQA to control in • a diffeserv architecture • a home network (together with reservation techniques, network calculus tools and IPv6 facilities) • in pricing(to build virtual user profiles); • to explore the interest of the same tools in risk evaluation, and in compression techniques @rmor – INRIA Rennes

Next future: on the tool • improve the mathematical analysis in the case of recurrent networks • and then, apply it to the WAN design area • improve the numerical algorithms used to analyze the networks • basically, by adapting to G-networks specific techniques that have proven to be efficient with ANN @rmor – INRIA Rennes

QQA : Quantitative Quality Assesment (or pseudo-subjective quality)