A Novel High-Speed Algorithm for Achieving Proportional Fairness in Data Networks

Proportional fairness criterion which has been proposed the first time by F.P.Kelly and his colleagues has a number of properties in allocating users’ rates. For example, it resembles the Jacobson’s AIMD method in rate allocation to users and there exists a well-established stability analysis in Kelly’s work relating to stability of rate allocation algorithm. Another outstanding feature is that Kelly et al. try to solve the optimization problem of maximizing the aggregate utility of users in a distributed manner by decomposing the overall system problem into two subproblems that can be solved by network and individual users by introducing a pricing scheme. The users try to maximize the individual net utility which is the utility minus the amount they pay and the network adjusts the prices by solving its corresponding subproblem. In this paper, we have proposed a novel high-speed technique which tries to increase the convergence-speed of the Kelly’s algorithm. Our simulations justify our algorithm.

Keywords:

Proportional fairness , Elastic traffic , Backbone , Scalability , Penalty function