10 research outputs found
Diffusive capture processes for information search
We show how effectively the diffusive capture processes (DCP) on complex
networks can be applied to information search in the networks. Numerical
simulations show that our method generates only 2% of traffic compared with the
most popular flooding-based query-packet-forwarding (FB) algorithm. We find
that the average searching time, , of the our model is more scalable than
another well known $n$-random walker model and comparable to the FB algorithm
both on real Gnutella network and scale-free networks with $\gamma =2.4$. We
also discuss the possible relationship between and , the second
moment of the degree distribution of the networks