High-Quality Learning Resource Dissemination Based on Opportunistic Networks in Campus Collaborative Learning Context
In the campus scenario, a basic community of collaborative teams is formed among the nodes participating in the collaborative learning interaction in the mobile opportunistic network. Due to the existing research does not consider the weak connection, node influence and the contact characteristics between nodes. In this paper, a routing method using a collaborative group as a communication unit is proposed. The route mainly counts the contact characteristics among the groups according to the characteristics of the node movement and predicts the subsequent contact situation. Combined with the weak connection relationship and the node’s influence, the optimal node to be transmitted is selected. It has been experimentally verified that the routing method can greatly improve the speed of message dissemination and avoid unnecessary message redundancy and waste of contact opportunities.
KeywordsOpportunistic networks Collaborative learning Weak connection Community influence
This work was supported by the National Natural Science Foundation of China (No. 61877037) and the National Natural Science Foundation of China (No. 61977044).
- 1.Fall, K.: A delay-tolerant network architecture for challenged internets. In: Proceedings of the 2003 Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications, p. 27. ACM, Karlsruhe (2003)Google Scholar
- 2.Vahdat, A., Becker, D.: Epidemic Routing for Partially-Connected Ad Hoc Networks. Handbook of Systemic Autoimmune Diseases (2000)Google Scholar
- 4.Spyropoulos, T., Psounis, K., Raghavendra, C.S.: Spray and wait: an efficient routing scheme for intermittently connected mobile networks. In: ACM SIGCOMM Workshop on Delay-tolerant Networking, pp. 252–259. ACM, New York (2005)Google Scholar
- 5.Sushant, J., Kevin, R., Rabin, K.: Routing in a delay tolerant network. In: Technologies, Architectures, and Protocols for Computer Communication, pp. 145–158. ACM, Portland (2004)Google Scholar
- 10.Petroczi, A., Bazsó, F., et al.: Measuring tie-strength in virtual social networks. Connections 91(1), 39–52 (2006)Google Scholar
- 14.Kristiansson, S.: Enriching and simplifying communication by social prioritization. In: International Conference on Advances in Social Networks Analysis and Mining, Odense, Denmark, pp. 336–340 (2010)Google Scholar
- 15.Haythornthwaite, W.C., Garton, L.: Studying online social networks. J. Comput.-Mediated Commun. 3(1), 1–5 (1997)Google Scholar