Research Article
Exploring Intelligent Service Migration in Vehicular Networks
@INPROCEEDINGS{10.1007/978-3-030-12971-2_3, author={Onyekachukwu Ezenwigbo and Vishnu Paranthaman and Glenford Mapp and Ramona Trestian}, title={Exploring Intelligent Service Migration in Vehicular Networks}, proceedings={Testbeds and Research Infrastructures for the Development of Networks and Communications. 13th EAI International Conference, TridentCom 2018, Shanghai, China, December 1-3, 2018, Proceedings}, proceedings_a={TRIDENTCOM}, year={2019}, month={2}, keywords={Edge Computing Service migration Vehicular Ad-hoc Network Quality of Service}, doi={10.1007/978-3-030-12971-2_3} }- Onyekachukwu Ezenwigbo
Vishnu Paranthaman
Glenford Mapp
Ramona Trestian
Year: 2019
Exploring Intelligent Service Migration in Vehicular Networks
TRIDENTCOM
Springer
DOI: 10.1007/978-3-030-12971-2_3
Abstract
Mobile edge clouds have great potential to address the challenges in vehicular networks by transferring storage and computing functions to the cloud. This brings many advantages of the cloud closer to the mobile user, by installing small cloud infrastructures at the network edge. However, it is still a challenge to efficiently utilize heterogeneous communication and edge computing architectures. In this paper, we investigate the impact of live service migration within a Vehicular Ad-hoc Network environment by making use of the results collected from a real experimental test-bed. A new proactive service migration model which considers both the mobility of the user and the service migration time for different services is introduced. Results collected from a real experimental test-bed of connected vehicles show that there is a need to explore proactive service migration based on the mobility of users. This can result in better resource usage and better Quality of Service for the mobile user. Additionally, a study on the performance of the transport protocol and its impact in the context of live service migration for highly mobile environments is presented with results in terms of latency, bandwidth, and burst and their potential effect on the time it takes to migrate services.
