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Information centric networks (ICNs) allow content objects to be cached within the network, so as to provide efficient data delivery. Existing works on in-network caches mainly focus on minimizing the redundancy of caches to improve the cache hit ratio, which may not lead to significant bandwidth saving. On the other hand, it could result in too frequent caching operations, i.e., cache placement and...
Efficient marketing or awareness-raising campaigns seek to recruit a small number, w, of influential individuals — where w is the campaign budget — that are able to cover the largest possible target audience through their social connections. In this paper we assume that the topology is gradually discovered thanks to recruited individuals disclosing their social connections. We analyze the performance...
We propose a model for network optimization in a non-cooperative game setting with specific reference to the Internet connectivity. We refer to the general model shown in internal report [1], where Autonomous Systems (AS) decisions on link creation and traffic routing are strategically based on realistic interconnection costs, keeping into account the peering/transit dichotomy. Equilibria existence...
Viral marketing campaigns seek to recruit the most influential individuals to cover the largest target audience. This can be modeled as the well-studied maximum coverage problem. Another related problem, called the maximum connected cover, is when recruited nodes have to be connected. This problem ensures a strong coordination among the influential nodes which are the backbone of the marketing campaign...
Cliques are defined as complete graphs or subgraphs; they are the strongest form of cohesive subgroup, and are of interest in both social science and engineering contexts. In this paper we show how to efficiently estimate the distribution of clique sizes from a probability sample of nodes obtained from a graph (e.g., by independence or link-trace sampling). We introduce two types of unbiased estimators,...
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