Research And Simulated Implementation On Microeconomics-Based Fuzzy QoS Routing Algorithm

During the early period of Internet, network applications mainly focus on traditional applications such as E-mail and FTP. These traditional applications are not sensitive to QoS (Quality of Service) . With the rapid development of various kinds of technologies, some new mobile businesses appear continuously, thus, the next generation Internet should be composed of wire transmission and wireless transmission. The service provided mainly by IP network should also be provided by mobile wireless Internet. Furthermore, the mobile wireless Internet should provide QoS gurantee for users.For the fee limitation of Internet, when users access to the mobile wireless Internet, they always prefer to get the best services with the least cost. However, the network providers always pursue the most profits. Hence, it's very necessary to study QoS routing algorithms that apply to the mobile wireless Internet and can benefit both Internet providers and users.In this paper, the Microeconomics-based fuzzy QoS routing algorithms that apply to the mobile wireless Internet are proposed. In the algorithms, the utilities of both network providers and users are considered simultaneously. Especially under the condition that the wireless network resources are limited, according to users' pays and the QoS class of users, assigns the limited resources to users reasonably and improve the utilization of network resources as much as possible; at the same time, the algorithms guides the users to utilize the network resources reasonably and improve the users' QoS satisfaction degree and makes the utilities of network providers and users reach or near to the Pareto optimum of Nash equilibrium at the best. In the algorithms, link judgment is done based on fuzzy theory, game analysis of network providers and users is done by using microeconomics theory, in the following, compute the heuristic cost and based on heuristic stepwise algorithms to determine next hop.To verify the feasibility and evaluate the performance of the proposed algorithms, the simulation is implemented in NS2 simulating platform. The results of the simulation are analyzed, showing that the proposed algorithms are effective.