Maximizing multiple influences and fair seed allocation on multilayer social networks

Fair Allocation in Evolving Networks

We consider networks evolving over time within an inÞnite-horizon dynamic setting. Transitions from one network to another are given by a stationary transition probability matrix. We study the problem of fairly and efficiently allocating the value of a network at any point in time among its participants, assuming that agents discount the future by some common discount factor δ. An allocation ru...

Maximizing Diffusion on Dynamic Social Networks

The influence maximization problem is an important one in social network analysis, with applications from marketing to epidemiology. The task is to select some subset of the nodes in the network which, when activated, will spread the activation to the greatest portion of the rest of the network as quickly as possible. Since exact solutions are computationally intractable greedy approximation al...

Resource Allocation Problems on Networks - Maximizing Social Welfare using an Agent-based Approach

Numerous applications can be formulated as an instance of resource allocation problems. Different kinds of solving techniques have been investigated, but the theoretical results cannot always be applied in practice due to inappropriate assumptions. Indeed, in these studies, agents are most of the time omniscient and/or have complete communication abilities. These hypotheses are not satisfied re...

Fair resource allocation in active networks

On Fair Bandwidth Allocation in Connection-less Networks

We introduce a transport-independent mechanism for network-wide fair bandwidth allocation in the Internet based on a natural hierarchy of authorities. With our proposed approach, routers identify a dynamic set of so-called fluxes derived form descriptors (ranks) disseminated in the network in a hierarchical fashion. The scheme assumes no particular implementation of the sessions contributing to...