Abstract
Cognitive vehicular ad-hoc networks (CVANETs) are expected to improve spectrum utilization efficiently and offer both infotainment and safety services for vehicles. In this paper, the joint route selection and resource allocation problem is considered for CVANETs. Taking into account the lifetime of transmission links, we first propose a candidate link selection method which selects the transmission links satisfying the link lifetime constraint. Then stressing the importance of transmission delay, we formulate the joint route selection and resource allocation problem as an end-to-end transmission delay minimization problem. As the formulated optimization problem is a complicated integer nonlinear problem, which cannot be solved conveniently, we equivalently transform the original problem into two subproblems, i.e., resource allocation subproblem for candidate links and route selection subproblem. Solving the two optimization subproblems by applying the K shortest path algorithm and the Dijkstra algorithm, respectively, we can obtain the joint route selection and resource allocation strategy. Simulation results demonstrate the effectiveness of the proposed algorithm.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Jiang, C., Chen, Y., Liu, K.R.: Data-driven optimal throughput analysis for route selection in cognitive vehicular networks. IEEE J. Sel. Areas Commun. 32, 2149–2162 (2014)
Miao, P., Li, P., Fang, Y.: Cooperative diversity in wireless networks: efficient protocols and outage behavior. IEEE J. Sel. Areas Commun. 30, 760–768 (2012)
Ghafoor, H., Koo, I.: CR-SDVN: a cognitive routing protocol for software-defined vehicular networks. IEEE Sens. J. 18(4), 1761–1772 (2018)
Wang, C., Zhang, L., Li, Z., Jiang, C.: SDCoR: software defined cognitive routing for Internet of vehicles. IEEE Internet Things J. 5, 3513–3520 (2018)
Kim, W., Oh, S.Y., Gerla, M., Lee, K.C.: CoRoute: a new cognitive anypath vehicular routing protocol. Wirel. Commun. Mob. Comput. 11(12), 1588–1602 (2011)
Chu, J.H., Feng, K.T., Lin, J.S.: Prioritized optimal channel allocation schemes for multi-channel vehicular networks. IEEE Trans. Mob. Comput. 14(7), 1463–1474 (2015)
Cordeschi, N., Amendola, D., Baccarelli, E.: Reliable adaptive resource management for cognitive cloud vehicular networks. IEEE Trans. Veh. Technol. 64(6), 2528–2537 (2015)
He, H., Shan, H., Huang, A., Sun, L.: Resource allocation for video streaming in heterogeneous cognitive vehicular networks. IEEE Trans. Veh. Technol. 65(10), 7917–7930 (2016)
Qian, J., Jing, T., Huo, Y., Zhou, W., Li, Z.: A next-hop selection scheme providing long path life-time in VANETs. In: IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), pp. 1929–1933 (2015)
Liu, H., Jin, C., Yang, B., Zhou, A.: Finding top-K shortest paths with diversity. IEEE Trans. Knowl. Data Eng. 30(3), 488–502 (2018)
Cormen, T.H., Leiserson, C.E., Ronald, R.L., Stein, C.: Introduction to Algorithms, 2nd edn, pp. 595–601. MIT Press and McGraw-Hill, London and New York (2001). Section 24.3: Dijkstra’s Algorithm
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Liu, C., Chai, R., Peng, S., Chen, Q. (2020). Delay Optimization-Based Joint Route Selection and Resource Allocation Algorithm for Cognitive Vehicular Ad Hoc Networks (Workshop). In: Gao, H., Feng, Z., Yu, J., Wu, J. (eds) Communications and Networking. ChinaCom 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 313. Springer, Cham. https://doi.org/10.1007/978-3-030-41117-6_28
Download citation
DOI: https://doi.org/10.1007/978-3-030-41117-6_28
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-41116-9
Online ISBN: 978-3-030-41117-6
eBook Packages: Computer ScienceComputer Science (R0)