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A Novel Cost-Effective Controller Placement Scheme for Software-Defined Vehicular Networks

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journal contribution
posted on 2021-06-25, 10:27 authored by N Lin, Q Zhao, L Zhao, A Hawbani, L Liu, G Min
Energy costs have dramatically increased in data center networks as an increasing number of large-scale Internet applications are used. In software-defined vehicular networks (SDVN), the communication delay between two vehicles and between vehicles and the controller will dramatically climb up as the number of vehicles increases. This requires more controllers to provide communication service to minimize the latency. More controllers lead to high energy costs. Therefore, the number of controllers and their placement, the so-called controller placement problem (CPP), should be addressed. The appropriate placement of controllers can decrease the energy cost, enabling green communication in SDVN. Although CPP has been studied for static networks, it has not been effectively solved in highly dynamic and complex networks. In this paper, a novel cost-effective CPP scheme for SDVN is proposed. First, our proposed minimum controller selection mechanism (MOSA) can reduce the number of controllers and guarantee the coverage of the area. Besides, an improved multi-objective artificial bee colony algorithm (IMABC) is proposed based on the original artificial bee colony algorithm. The IMABC can judge which controller should be switched on for data transmission based on real-time traffic flow. A route computation mechanism is proposed to evaluate the performance of our CPP scheme. The experimental results confirm that compared to other existing CPP schemes, our scheme can achieve a higher packet delivery ratio while greatly reducing energy consumption and latency.

History

Author affiliation

School of Informatics

Version

  • AM (Accepted Manuscript)

Published in

IEEE Internet of Things Journal

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

eissn

2327-4662

Copyright date

2021

Available date

2021-06-25

Language

en

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