Abstract
Currently, VANETs are becoming more and more popular and have been applied in many different applications. However, because the feature of VANETs’ topologies is relatively stable, the routing protocol designed for VANET can be more efficient from a macro perspective. Specifically, the concept of incompletely predictable networks (IPNs), where nodes travel around the basic positions, can be used to model stable VANETs, as the ones related to taxis during our daily lives. In this paper, we propose a new protocol, named Greedy Probability-based Routing Protocol, for rather stable VANETs. A new concept named “anti-pheromone” is put forward to achieve high energy efficiency. Simulation results illustrate that GPRP has proper utilization ratio of nodes to achieve energy efficiency and has a stable performance when network size changes.
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Acknowledgments
This work is supported by the National Science Foundation of China under Grant No. 61300237, No. U1536206, No. U1405254, No. 61232016 and No. 61402234, the National Basic Research Program 973 under Grant No. 2011CB311808, the Natural Science Foundation of Jiangsu province under Grant No. BK2012461, the research fund from Jiangsu Technology & Engineering Center of Meteorological Sensor Network in NUIST under Grant No. KDXG1301, the research fund from Jiangsu Engineering Center of Network Monitoring in NUIST under Grant No. KJR1302, the research fund from Nanjing University of Information Science and Technology under Grant No. S8113003001, the 2013 Nanjing Project of Science and Technology Activities for Returning from Overseas, the 2015 Project of six personnel in Jiangsu Province under Grant No. R2015L06, the CICAEET fund, and the PAPD fund.
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Shen, J., Wang, C., Castiglione, A., Liu, D., Esposito, C. (2016). Greedy Probability-Based Routing Protocol for Incompletely Predictable Vehicular Ad-hoc Network. In: Wang, G., Ray, I., Alcaraz Calero, J., Thampi, S. (eds) Security, Privacy and Anonymity in Computation, Communication and Storage. SpaCCS 2016. Lecture Notes in Computer Science(), vol 10067. Springer, Cham. https://doi.org/10.1007/978-3-319-49145-5_21
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DOI: https://doi.org/10.1007/978-3-319-49145-5_21
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