On efficiency in searching networks

This paper deliberates on various critical aspects in evaluating searching networks. Existing metrics either draw biased conclusions regarding search performance or provide wrong guidelines for algorithm design. We, therefore, define a unified criterion, search efficiency (SE), to objectively address search performance in a comprehensive manner. The goal of SE is to better characterize performance of searching networks than existing metrics do as well as to guide the design of future ones. We first validate the correctness of SE in performance evaluation in an ideal graph, strictly binary tree, by analyzing SE for two typical search methods, breadth first search and random walk. We further show its strength in performance characterization in the real-world topology, power-law random graph, under various network conditions. We finally design an algorithm, dynamic search, based on SE analysis. Its proved outstanding performance demonstrates the strength of SE to provide guidance for the future design of searching networks.