A Novel Access Network Selection Algorithm for Heterogeneous Wireless Environment Based on Multiple Attributes

摘要

In the field of access selection algorithm in heterogeneous wireless networks, bandwidth, packet loss, delay and other performances of various access networks are different. The proposed algorithm such as TOPSIS considered the effect of multiple attributes on network access selection, but the recommended network tended to be the one whose value of one attribute is too large, that makes it not to be the closest one to the optimal scheme. This paper proposes a network selection algorithm named Multiple Attributes Close to the Optimal (MACO), in which multiple attributes are close to the optimal solution. The core idea of this algorithm is evaluating the similarity measure between multiple network attribute and the optimal solution, so the recommended network is the closest one to the optimal scheme. We built an heterogeneous wireless environment to verify the algorithm. Experimental results show that when one attribute of network changes greatly, the traditional algorithm TOPSIS can be affected seriously and will change the recommended network, but MACO can keep the recommendation result in which multiple attributes are close to the optimal solution. The stability of MACO increases 30% than that of TOPSIS.