Abstract
This paper introduces an evolutionary approach to enhance the process of finding central nodes in mobile networks. This can provide essential information and important applications in mobile and social networks. This evolutionary approach considers the dynamics of the network and takes into consideration the central nodes from previous time slots. We also study the applicability of maximal cliques algorithms in mobile social networks and how it can be used to find the central nodes based on the discovered maximal cliques. The experimental results are promising and show a significant enhancement in finding the central nodes.
Highlights
Centrality in social networks is an important measure of the influence of the node in the network [1,2,3,4,5,6]
We focus on the design and analysis of evolutionary centrality algorithms that can be used effectively to analyze the dynamics of mobile networks to find central nodes
This paper focused on the problem of centrality and maximal cliques in mobile social networks
Summary
Centrality in social networks is an important measure of the influence of the node in the network [1,2,3,4,5,6]. Finding these central nodes that have important effects on other nodes will have many important applications in network science. There is a need to understand the behavior of mobile networks and to find central nodes dynamically This can enhance the provided services and introduce new applications that meet the need of communities in mobile networks. The goal of this research is to develop algorithms that can be used for evolutionary centrality in mobile social networks by utilizing mobility data that represents the dynamic behavior of the mobile networks
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