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Random walks can be used to search a complex networks for a desired resource.To reduce the number of hops necessary to find the resource, we propose asearch mechanism based on building random walks connecting together partialwalks that have been precomputed at each network node in an initial stage. Theresources found in each partial walk are registered in its associated Bloomfilter. Searches can then jump over partial nodes in which the resource is notlocated, significantly reducing search length. However, additional unnecessaryhops come from false positives at the Bloom filters. The analytic modelprovided predicts the expected search length of this mechanism, the optimalsize of the partial walks and the corresponding optimal (shortest) expectedsearch length. Simulation experiments are used to validate these predictionsand to assess the impact of the number of partial walks precomputed in eachnode.

Reducing Search Lengths with Locally Precomputed Partial Random Walks