A novel approach to study realistic navigations on networks

We consider navigation or search schemes on networks which are realistic in the sense that not all search chains can be completed. We show that the quantity $\mu = \rho/s_d$, where $s_d$ is the average dynamic shortest distance and $\rho$ the success rate of completion of a search, is a consistent measure for the quality of a search strategy. Taking the example of realistic searches on scale-free networks, we find that $\mu$ scales with the system size $N$ as $N^{-\delta}$, where $\delta$ decreases as the searching strategy is improved. This measure is also shown to be sensitive to the distintinguishing characteristics of networks. In this new approach, a dynamic small world (DSW) effect is said to exist when $\delta \approx 0$. We show that such a DSW indeed exists in social networks in which the linking probability is dependent on social distances.Comment: Text revised, references added; accepted version in Journal of Statistical Mechanic

The Potential of Restarts for ProbSAT

This work analyses the potential of restarts for probSAT, a quite successful algorithm for k-SAT, by estimating its runtime distributions on random 3-SAT instances that are close to the phase transition. We estimate an optimal restart time from empirical data, reaching a potential speedup factor of 1.39. Calculating restart times from fitted probability distributions reduces this factor to a maximum of 1.30. A spin-off result is that the Weibull distribution approximates the runtime distribution for over 93% of the used instances well. A machine learning pipeline is presented to compute a restart time for a fixed-cutoff strategy to exploit this potential. The main components of the pipeline are a random forest for determining the distribution type and a neural network for the distribution's parameters. ProbSAT performs statistically significantly better than Luby's restart strategy and the policy without restarts when using the presented approach. The structure is particularly advantageous on hard problems.Comment: Eurocast 201

Can filesharers be triggered by economic incentives? Results of an experiment

Illegal filesharing on the internet leads to considerable financial losses for artists and copyright owners as well as producers and sellers of music. Thus far, measures to contain this phenomenon have been rather restrictive. However, there are still a considerable number of illegal systems, and users are able to decide quite freely between legal and illegal downloads because the latter are still difficult to sanction. Recent economic approaches account for the improved bargaining position of users. They are based on the idea of revenue-splitting between professional sellers and peers. In order to test such an innovative business model, the study reported in this article carried out an experiment with 100 undergraduate students, forming five small peer-to-peer networks.The networks were confronted with different economic conditions.The results indicate that even experienced filesharers hold favourable attitudes towards revenue-splitting.They seem to be willing to adjust their behaviour to different economic conditions

Information Horizons in Networks

We investigate and quantify the interplay between topology and ability to send specific signals in complex networks. We find that in a majority of investigated real-world networks the ability to communicate is favored by the network topology on small distances, but disfavored at larger distances. We further discuss how the ability to locate specific nodes can be improved if information associated to the overall traffic in the network is available.Comment: Submitted top PR