López Millán, Víctor M. and Cholvi, Vicent and López, Luis and Fernández Anta, Antonio (2012) A Model of SelfAvoiding Random Walks for Searching Complex Networks. [Journal Articles]

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Abstract
Random walks have been proven useful in several applications in networks. Some variants of the basic random walk have been devised pursuing a suitable tradeoff between better performance and limited cost. A selfavoiding random walk (SAW) is one that tries not to revisit nodes, therefore covering the network faster than a random walk. Suggested as a network search mechanism, the performance of the SAW has been analyzed using essentially empirical studies. A strict analytical approach is hard since, unlike the random walk, the SAW is not a Markovian stochastic process. We propose an analytical model to estimate the average search length of a SAW when used to locate a resource in a network. The model considers single or multiple in stances of the resource sought and the possible availability of onehop replication in the network (nodes know about resources held by their neighbors). The model characterize networks by their size and degree distribution, without assuming a particular topology. It is, therefore, a meanfield model, whose applicability to real networks is validated by simulation. Experiments with sets of randomly built regular networks, Erd ̋s–R ́nyi networks, and scalefree networks of several of several sizes and degree averages, with and without onehop replication, show that model predictions are very close to simulation results, and allow us to draw conclusions about the applicability of SAWs to network search.
Item Type:  Journal Articles 

Uncontrolled Keywords:  selfavoiding random walk, random walk, network search, resource location, onehop replication, average search length 
Subjects:  Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering 
Divisions:  Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science 
Depositing User:  Systems Ad Systems Administrator 
Date Deposited:  17 May 2012 10:59 
Last Modified:  03 Oct 2013 10:29 
URI:  http://eprints.networks.imdea.org/id/eprint/262 
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