Asymmetric Attribute Aggregation in Hierarchical Networks

Abstract

To achieve scalability and security, large networks are often structured hierarchically as a collection of domains. In hierarchical networks, the topology and QoS parameters of a domain have to be first aggregated before being propagated to other domains. However, topology aggregation may distort useful information. Although spanning tree aggregation can perfectly encode attribute information of symmetric networks, it can not be applied to asymmetric networks directly. In this paper, we propose a spanning tree based attribute aggregation method for asymmetric networks. The time complexity of the proposed method and the space complexity of its resulted aggregated topology are the same with that of the spanning tree aggregation method in symmetric networks. This method can guarantee that the attributes of more than half of the links in the networks are unaltered after aggregation. Simulation results show that the proposed method achieves the best tradeoff between information accuracy and space complexity among the existing asymmetric attribute aggregation methods.