  In the wireless network applications, such as routing decision, network
selection, etc., the Multi-Attribute Decision Making (MADM) has been widely
used. The MADM approach can address the multi-objective decision making issues
effectively.However, when the parameters vary greatly, the traditionalMADM
algorithm is not effective anymore. To solve this problem,in this paper, we
propose the pairwise-based MADM algorithm.In the PMADM, only two nodes
utilities are calculated and compared each time. The PMADM algorithm is much
more accurate than the traditional MADM algorithm. Moreover, we also prove that
our PMADM algorithm is sensitive to the parameters which vary seriously and
in-sensitive to the parameters which change slightly. This property is better
than that of the traditional MADM algorithm. Additionally, the PMADM algorithm
is more stable than the traditional MADM algorithm. For reducing the
computational complexity of the PMADM algorithm, we propose the low-complexity
PMADM algorithm. For analyzing the computational complexity of the lPMADM
algorithm, we propose the tree-based decomposing algorithm in this paper. The
lPMADM algorithm has the same properties and performances as that of the PMADM
algorithm; however, it is simpler than the PMADM algorithm. The simulation
results show that the PMADM and lPMADM algorithms are much more effective than
the traditional MADM algorithm.
