Modeling a datacenter state through a novel weight corrected AHP algorithm

Abstract

Analytic Hierarchy Process (AHP) is an effective algorithm for determining the weight of each module of a model. It is generally used in the process of multi-indicator decision making. But, when using AHP for evaluation, it is inevitable to introduce the evaluator’s subjectivity. In this paper, an algorithm based on Bayes’ formula is proposed for correcting the weights determined by the analytic hierarchy process. This algorithm can reduce the subjectivity of the evaluator introduced during the evaluation process. At the same time, the common operational indicators of a data center are summarized and classified. I chose some relatively important indicators and established an evaluation model for the operational status of the data center. The weight of the modules of the established model is corrected using this improved algorithm.