Freshness-aware initial seed selection for traffic offloading through opportunistic mobile networks

Offloading traffic through Opportunistic Mobile Networks, also known as opportunistic offloading is a promising way to relieve the overload of cellular networks. The efficiency of such opportunistic offloading is highly determined by the selection of initial seeds. With considering both the freshness of the content and the cost of transmission from the cellular network to the initial seeds, this paper defines a novel freshness-aware seed selection optimization problem to find K initial seeds to maximize the overall content utility. To solve the optimization problem, we propose two seed selection methods: the greedy seed selection method and the decay-based seed selection method. The greedy seed selection method iteratively selects nodes with the maximum Freshness Centrality value as initial seeds. To further improve the performance, the decay-based seed selection method selects initial seeds who are far apart and important in theirs local structure. Extensive real trace-driven simulations are conducted to evaluate the performance of our proposed seed selection methods. The results show that as expected the proposed decay-based seed selection method is superior to the proposed greedy seed selection method and the random seed selection method.