Collaborative Data Dissemination in Opportunistic Vehicular Networks

Future opportunistic vehicular networks offers viable means for collaborative data dissemination by high-capacity device-to-device communication. This is a highly challenging problem because a) mobile data items are heterogeneous in size and lifetime; b) mobile users have different interests to different data; and c) dissemination participants have limited storages. We study collaborative data dissemination under these realistic opportunistic vehicular network conditions and formulate the optimal data dissemination as a submodular function maximisation problem with multiple linear storage constraints. We then propose a heuristic algorithm to solve this challenging problem, and provide its theoretical performance bound. The effectiveness of our approach is demonstrated through simulation using real vehicular traces. https://www.researchgate.net/profile/Zhaocheng_Wang/publication/265973727_Collaborative_Data_Dissemination_in_Opportunistic_Vehicular_Networks/links/54ba14770cf253b50e2aa214/Collaborative-Data-Dissemination-in-Opportunistic-Vehicular-Networks.pdf