The Variable-Weight MADM Algorithm for Wireless Network

Abstract

In wireless scenarios, the multi-attribute decision-making (MADM) algorithm has been widely used. It can address the multi-objective decision-making issues effectively. However, considering the data flow in wireless network is high-dynamic, continuous, and large-scale, the traditional MADM algorithms are not accurate anymore and the computational complexity is extremely high. To address this problem, in this paper, we propose the variable-weight MADM (vw-MADM) algorithm, which is simple but more effective than previous works. In vw-MADM, when one of the parameters changes, different from the traditional MADM algorithm, only the utility of this parameter needs to be recalculated, the utilities of other candidates are not affected. Based on this innovation, the accuracy is improved while the computational complexity is reduced. Moreover, we also prove the correctness of vw-MADM algorithm, i.e., it is reasonable and effective. Finally, we analyze the computational complexity of both vw-MADM algorithm and traditional MADM algorithm. All the conclusions demonstrate that the proposed vw-MADM algorithm has better performance than the traditional MADM algorithm on accuracy and complexity.