We present a semi-Markov model of random walk on complex networks in discrete and continuous-time scenario. In the general setting of the semi-Markov chains, the duration of stay at given node - the sojourn time - is random, and the probability to transition to a neighbor depends on the sojourn time. Analytical formulae for the average sojourn time and the node occupation probability of infinite walk are presented and verified with Monte Carlo simulations for two examples. We propose an application of the semi-Markovian random walk for ranking web pages determined by the fraction of time that infinite random surfer spends on a web page - time rank, as an alternative to the existing PageRank that relies on the fraction of visits - visit rank.
Lasko Basnarkov (Sat,) studied this question.