Affiliations: Multimedia Systems Group, IT Department of Research Institute for ICT (ITRC), Tehran, Iran
Note: [] Corresponding author. Pejman Goudarzi, Multimedia Systems Group, IT Department of Research Institute for ICT (ITRC), Tehran-Iran. E-mail: pgoudarzi@itrc.ac.ir
Abstract: Many difficult engineering problems have found natural solutions which have been inspired from biological behaviors of the living kinds. Some important examples include neural networks, Genetic Algorithm (GA), DNA computing, artificial immune systems etc. Fair resource allocation strategies which are developed by many researchers are based on solving a form of constrained optimization problem. However, they are not necessarily lead to high-speed and stable solutions. There are plenty of high-speed fair rate allocation methods in the literature, some of them are based on fuzzy controllers for improving the convergence speed and are not necessarily optimal. Hence, in the current research, the GA has been adopted for finding the optimum membership functions which must be used in the fuzzy controller. Stability analysis is presented to guarantee the convergence property of the algorithm. After simulating, the results show that using the hybrid fuzzy-genetic approach improves the conventional methods in convergence speed and results in fewer oscillations in allocated rates.
