Enhancement of the Adaptive Routing Tensor Model in the Info-communication Network With Providing Quality of Experience by the R-Factor

Abstract

The object of research is the routing processes and ensuring the quality of experience in the infocommunication network. To conduct research an improvement of the adaptive routing tensor model in an infocommunication network with quality of experience by the R-factor is proposed. The basis was a floe-based routing model that took into account possible packet losses caused by congestion of network elements and was represented by the conditions for implementing a multipath routing strategy, conditions of the flow conservation and conditions for preventing overload of communication links. To obtain in an analytical form the conditions for ensuring the quality of experience in terms of the R-factor, a tensor description of the infocommunication network is carried out. This allowed obtaining of analytical expressions for calculating the average end-to-end delay and the probability of packet loss, which were used to formulate the QoE conditions in terms of the R-factor.

In the framework of the proposed model, solving the technological problem of adaptive routing solutions are reduced to solving the optimization problem of nonlinear programming for calculating route variables. The introduced optimality criterion allowed it possible to ensure the adaptive nature of route decisions, when an increase in QoE requirements led to an increase in the amount of network resource used. To solve the problem, methods of mathematical programming were used, which are implemented in the MatLab package.

A study on a fragment of the infocommunication network made it possible to evaluate the adequacy and effectiveness of the proposed model. Using the obtained research results, it was possible to ensure the fulfillment of the specified QoE requirements in terms of the R-factor for the services provided to end users. Using the proposed model is characterized by high efficiency on load balancing across multiple routes in the infocommunication network. This was evidenced by the fact that at a given value of the R-factor, with an increase in the intensity of traffic entering the infocommunication network, there was a gradual increase in the number of routes involved. In other words, the network resource was distributed evenly and efficiently by 7–10 % relative to known analogues, which, when solving the same problem, immediately use all possible routes.