Service Migration for Connected Autonomous Vehicles

Pacheco, Lucas; Oliveira, Helder; Rosário, Denis; Cerqueira, Eduardo; Villas, Leandro; Braun, Torsten (12 October 2020). Service Migration for Connected Autonomous Vehicles. In: 2020 IEEE Symposium on Computers and Communications (ISCC) (pp. 1-6). IEEE 10.1109/ISCC50000.2020.9219592

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In Connected Autonomous Vehicles scenarios or CAV, ubiquitous connectivity will play a significant role in the safety of the vehicles and passengers. The extensive amount of sensors in each car will generate vast amounts of data that cannot be processed promptly by onboard units. Edge and fog computing are emerging solutions for remote data processing for autonomous vehicles, offering higher computing power, as well as the low latency required by autonomous driving. However, due to the highly distributed nature of fog and edge computing servers, CAV mobility may pose a challenge to keep services close to end-users and maintaining QoS. In this paper, we propose MOSAIC, service migration, and resource management algorithm for intra-tier and inter-tier communication in edge and fog computing. The proposed solution performs proactive migration of services based on mobility information, server resources, QoS, and network conditions. Simulation results show the efficiency of the proposed algorithm in terms of latency, migration failures, and network throughput.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

08 Faculty of Science > Institute of Computer Science (INF)
08 Faculty of Science > Institute of Computer Science (INF) > Communication and Distributed Systems (CDS)

UniBE Contributor:

de Sousa Pacheco, Lucas; Cerqueira, Eduardo and Braun, Torsten

Subjects:

000 Computer science, knowledge & systems
500 Science > 510 Mathematics

ISBN:

978-1-7281-8086-1

Publisher:

IEEE

Language:

English

Submitter:

Dimitrios Xenakis

Date Deposited:

19 Nov 2020 17:05

Last Modified:

22 Nov 2020 02:50

Publisher DOI:

10.1109/ISCC50000.2020.9219592

BORIS DOI:

10.7892/boris.148204

URI:

https://boris.unibe.ch/id/eprint/148204

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