Bypass-based star aggregation using link attributes for improving the information accuracy

In this study, we present an approach for reducing the information inaccuracy of existing star aggregation based on bypass links when there are multi-constraint QoS parameters in asymmetric networks. In our approach, bypass links with low similarity are selected. Links that are not chosen as bypass links are included in each group depending on the star's link characteristics. Moreover, each link group is aggregated differently according to the similarity of the links that make up the group. The selection of a bypass link by using link similarity reduces the existing time complexity of O(N
³
) to O(N) by virtue of the simplification of the selection process. In addition, the adaptive integration according to the characteristics of the links in each group is designed to reduce the information inaccuracy caused by static aggregation. Simulation results show that the proposed method maintains low information distortion; specifically, it is 3.8 times lower than that of the existing method, even when the number of nodes in a network increases.