Freshness-Aware Seed Selection for Offloading Cellular Traffic Through Opportunistic Mobile Networks

Abstract

Offloading cellular traffic through Opportunistic Mobile Networks, also known as opportunistic offloading has been proposed as 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 both the optimal number of initial seeds and the maximum overall content utility. To solve the optimization problem, the optimal strategy is first analyzed, and then two seed selection methods: the greedy seed selection method and the decay-based seed selection method are proposed to find the optimal number of initial seeds to maximize the overall content utility. 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, not only in the Infocom 06 trace, but also in the MIT Reality trace.