Weighting Approach in Zigbee Network Performance Index Based on Correlation

Abstract

In Zigbee network performance evaluation, there is artificiality to determine weights of Multi-dimensional indexes, and the indexes could not be completely independent. We combine the entropy method and correlation between indexes, and build multi-evaluation index weight decision analysis model to get more objective and realistic evaluation of indexes. Using opnet network simulation software, we collect different network performance parameters by changing the node size. The data analysis shows that the entropy can objectively and accurately reflect the size of information provided by each index, and this method can reflect the relative importance of each index more objectively and accurately.