Decision Algorithm for Heterogenous Internet of Vehicles

DOI

10.2991/cnci-19.2019.91How to use a DOI?

Keywords

Heterogeneous Internet of Vehicles (IoV), vertical handover, fuzzy analytic hierarchy process (FAHP), decision algorithm.

Abstract

In the fast-moving Internet of Vehicles (IoV), the handovers may fail frequently and the network throughput may decline due to the excessive speed of vehicles and the uneven distribution of terminals. To solve these problems, this paper puts forward a vertical handover decision algorithm based on the fuzzy analytic hierarchy process (FAHP). Firstly, the candidate networks were screened against the network load at the moment of handover, eliminating those with load beyond the pre-set threshold. In this way, the network load of all candidate networks is controlled within a certain limit and the algorithm is made less complex. Secondly, the weights of all four decision attributes was determined by the FAHP, including the signal-to-interference-plus-noise ratio (SINR), handover delay, available bandwidth and communication cost. Finally, the technique for order preference by similarity to ideal solution (TOPSIS) algorithm was introduced to make decisions, yielding the optimal network for handover. The simulation results show that our algorithm can reduce the handover failure rate, lower the handover delay and enhance the network throughput under different number of vehicle terminals.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Qiong Wu
AU  - Xinmiao Lu
AU  - Ya Wang
PY  - 2019/05
DA  - 2019/05
TI  - Decision Algorithm for Heterogenous Internet of Vehicles
BT  - Proceedings of the 2019 International Conference on Computer, Network, Communication and Information Systems (CNCI 2019)
PB  - Atlantis Press
SP  - 655
EP  - 663
SN  - 2352-538X
UR  - https://doi.org/10.2991/cnci-19.2019.91
DO  - 10.2991/cnci-19.2019.91
ID  - Wu2019/05
ER  -