Conclusions

In this Chapter, we have presented a new rate control mechanism that combines an automated real-time subjective multimedia quality assessment with a TCP-Friendly rate controller. It helps in delivering the best multimedia quality and in saving any superfluous bandwidth for a given network situation (by determining the exact sending rate to be used, instead of just giving an upper bound). The controller decides, based on the subjective quality (measured by the trained neural network according to the approach described in Chapter 4) and on the network conditions (TCP-Friendly rate controller suggestions), which parameters should be modified to achieve this task. We used, with our rate controller, the equation-based TCP-Friendly congestion control protocol that has some advantages for real-time multimedia applications. We provided a list of the possible controlling parameters to be used with our proposal. We showed the efficiency of the proposed approach in the cases of speech and video transmission. The perceived quality improved considerably in our experience when using the new controller. By using different parameters, we believe that the quality can be improved. Studying the effects of the other parameters and building a complete controller are some of the future research directions.