Abstract
Message dissemination problem have attracted great attention in vehicular ad hoc networks (VANETs). One important task is to find a set of relay nodes to maximize the number of successful delivery messages. In this paper, we investigate the message dissemination problem and propose a new method that aims at selecting optimal nodes as the collaborative nodes to distribute message. Firstly, we analyze the real vehicle traces and find its sociality by extracting contacts and using community detecting approach. Secondly, we propose community collaboration degree to measure the collaborative possibility of message delivery in the whole community. Moreover, we use Markov chains to infer future community collaboration degree. Thirdly, we design a community collaboration (CC) algorithm for selecting the optimal collaborative nodes. We compare our algorithm with other methods. The simulation results show that our algorithm performance is better than other methods.
Keywords
This work is partially supported by the NSF of China (No. 61502359, 61602351, 61572370, and 61802286), the Hubei Provincial Natural Science Foundation of China (No. 2018CFB424), and the Wuhan University of Science and Technology Innovative Entrepreneurship Training Program (17ZRA118).
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Huang, W. et al. (2019). Exploiting Sociality for Collaborative Message Dissemination in VANETs. In: Gao, H., Wang, X., Yin, Y., Iqbal, M. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 268. Springer, Cham. https://doi.org/10.1007/978-3-030-12981-1_26
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