Optimal Target Set Selection via Opinion Dynamics

The solution for handling the issue of mobile data is gaining significance due to the exponential rise in data traffic in recent years. Data traffic offloading becomes a challenging problem, if it is dependent only on infrastructure (femtocells, Bluetooth, WiFi). Opportunistic communications(mobile social networks, Delay tolerant networks) can enhance the offloading efficiently if the target nodes(helper nodes) are chosen optimally. In this paper, we have considered this problem and propose a Target Set Selection algorithm based on Opinion Dynamics. The opinion vector provides a weighed feedback for the community to select the helper nodes. To validate our algorithm, we have compare it with existing algorithm like heuristic approach and greedy approach of target set selection. Our result shows that the number of nodes identified in the Target Set can further be reduced by nearly 13% when compared with degree based greedy approach. Result also shows that our approach is nearly 58% better than the heuristic approach, infrastructure-based approach in terms of traffic forwarding via helper node.