托普西斯
计算机科学
层次分析法
理想溶液
垂直移交
数据挖掘
选择(遗传算法)
趋同(经济学)
移交
模糊逻辑
背景(考古学)
无线网络
运筹学
人工智能
异构网络
无线
计算机网络
工程类
热力学
生物
物理
电信
古生物学
经济
经济增长
作者
Zhengli Zhao,Xiaobin Li
出处
期刊:Lecture notes on data engineering and communications technologies
日期:2021-01-01
卷期号:: 1670-1678
标识
DOI:10.1007/978-3-030-70665-4_181
摘要
The convergence of wireless heterogeneous networks has led the goal of “Always Best Connected” as the primary challenge for next-generation network selection. In order to improve the overall performances of the system, various criteria corresponding to user preferences and network conditions as well as QoS parameters are supposed to be considered comprehensively. Hence, network selection is a typical multi-attribute decision making issue. In this context, the analytic hierarchy process (AHP) and technique for order preference by similarity to an ideal solution (TOPSIS) are exhaustedly used as representative multi-attribute decision methods (MADM). However, various traffic types have different demands for network. AHP can only calculate the weight of one traffic type at a time. Therefore, different traffic types need to be analyzed separately. Moreover, these two methods are susceptible to subjective influences and are not suitable for handling contradictory and vague information, so they are prone to frequent handover, easily resulting in ping-pong effects. Thus, this paper provides a network selection algorithm which combines AHP, TOPSIS and fuzzy logic. Four traffic types and key indicators are evaluated respectively. Simulation results show that the implemented algorithm can significantly compensate for the above defects and make efficient decisions for all traffic types.
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