Search in power-law node degree networks

Graphs in which decentralized algorithms can find short paths efficiently by considering only local information are known as Searchable Networks [4], [5]. Jon Kleinberg studied decentralized search in a subtle variant of the Watts-Strogatz model [3] and showed that the structure of searchable networks has to meet some strict requirements [5]. The aim of this paper is to investigate how it would be decentralized search in small-world models which combine wide variation in node degrees with some kind of spatial embedding. Through simulations, we evaluate the performance of a decentralized greedy algorithm and compare its efficiency versus Kleinberg´s results. Our results indicates that networks with wide variation in node degrees can allow decentralized algorithms to achieve better average delivery times than the ones obtained by Kleinberg in [4].