马尔科夫模型在异构无线网络选择中的应用

摘要

研究异构无线网络接入选择问题.选择网上最佳资源连接,由于通信过程存在随机性,单一方法难以确定最优接入网络.为满足异构无线网络选择准确性,提出一种马尔科夫的异构无线网络选择算法.首先选择网络性能指标,然后采用层次分析法确定网络性能指标权重,再通过马尔科夫模型计算每一个网络的期望总同报值,并选择回报值最大的网络作为当前最优接入网络进行仿真.仿真结果证明,相对于传统网络选择算法,马尔科夫算法能够根据用户需求选择到最优接入网络,可以有效地减少切换次数,提高有效吞吐量和降低丢包率,提高了异构性网络选择的准确性.%Research heterogeneous wireless network access problem. Heterogeneous wireless network access selection is a multiple attribute decision making problem, and single method is difficult to determine the optimal access network. This paper put forward a network selection algorithm based on Markov. Firstly, the network performance indexes were chosen, and the weights identifying network performance index were calculated by AHP. Finally, the expected total value of network was calculated by Markov model, and the maximum value was chosen for the current optimal access networks. Simulation experiments show that the Markov algorithm can choose optimal access network according to user needs, effectively reduce switching times, enhance the effective throughput, reduce packet loss rate, and improve the accuracy of choice network in the heterogeneous network, compared with the traditional network selection algorithm.