Assessment and event based analysis of dynamic wireless networks

The last decade has seen an increasing interest for wireless communications. With the current use of smart-phones and tablets, together with the rise of the Internet of Things, the number of mobile nodes in networks is significantly changing the way they are managed. Indeed, these wireless networks are highly dynamic, mainly, regarding topology and traffic matrices. The high dynamism of mobile nodes can for instance impact the connectivity of the network, or the role of the nodes in the routing graph. Given this increasing complexity, network's service management requires to be as autonomous as possible. However, autonomy can not be achieved unless the network is able to assess and understand its own behavior. In this paper, we propose an assessment index (SA) based on nodes' satisfaction and its self-estimation algorithm for wireless mobile networks.We then provide events' collection and distributed mining methods allowing nodes to analyze the evolution of this index.We illustrate our framework and characterize the estimation error for various network properties under NS3 simulations.