PROJECT TITLE :

Mobile Conductance in Sparse Networks and Mobility-Connectivity Tradeoff - 2016

ABSTRACT:

An necessary application for modern giant-scale networks is to spread the information efficiently to the most important audience. To better perceive the theoretical underpinnings, a novel graph metric named mobile conductance was proposed in our previous work to guage the information spreading time of a connected mobile network. By capturing the details of each network structure and mobility pattern, this metric essentially determines the network bottleneck for conducting information flow under general network mobility. Despite major relaxation on node mobility, solely slight relaxation on network connectivity was created in our previous work. In this paper, we have a tendency to make another major relaxation on the network connectivity by extending the mobile-conductance based analytical model to the sparse setting, hence giving a unified read. Interestingly, a penalty issue is identified for info spreading in sparse networks as compared to the connected state of affairs, that is then intuitively interpreted and verified by simulations. By jointly considering mobility and connectivity, we tend to derive the mobile conductance for numerous mobility models with general connectivity. Using these analytical results, the mobility-connectivity tradeoff is quantitatively analyzed to work out how a lot of mobility might be exploited to make amends for network connectivity deficiency.