1 research outputs found
Improving Resource Location with Locally Precomputed Partial Random Walks
Random walks can be used to search complex networks for a desired resource.
To reduce search lengths, we propose a mechanism based on building random walks
connecting together partial walks (PW) previously computed at each network
node. Resources found in each PW are registered. Searches can then jump over
PWs where the resource is not located. However, we assume that perfect
recording of resources may be costly, and hence, probabilistic structures like
Bloom filters are used. Then, unnecessary hops may come from false positives at
the Bloom filters. Two variations of this mechanism have been considered,
depending on whether we first choose a PW in the current node and then check it
for the resource, or we first check all PWs and then choose one. In addition,
PWs can be either simple random walks or self-avoiding random walks. Analytical
models are provided to predict expected search lengths and other magnitudes of
the resulting four mechanisms. Simulation experiments validate these
predictions and allow us to compare these techniques with simple random walk
searches, finding very large reductions of expected search lengths.Comment: 25 pages, 15 figures. arXiv admin note: substantial text overlap with
arXiv:1107.466