AVE: Autonomous Vehicular Edge Computing Framework with ACO-Based Scheduling

With the emergence of in-vehicle applications, providing the required computational capabilities is becoming a crucial problem. This paper proposes a framework named autonomous vehicular edge (AVE) for edge computing on the road, with the aim of increasing the computational capabilities of vehicles...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology Vol. 66; no. 12; pp. 10660 - 10675
Main Authors: Feng, Jingyun, Liu, Zhi, Wu, Celimuge, Ji, Yusheng
Format: Journal Article
Language:English
Published: New York IEEE 01.12.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Ant colony optimization
Caching
Cloud computing
Computer simulation
Edge computing
Idling
job scheduling
Operations research
Scheduling
Scheduling algorithms
Vehicles
vehicular network
Workflow
ISSN:0018-9545, 1939-9359
Online Access:Get full text
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Summary:With the emergence of in-vehicle applications, providing the required computational capabilities is becoming a crucial problem. This paper proposes a framework named autonomous vehicular edge (AVE) for edge computing on the road, with the aim of increasing the computational capabilities of vehicles in a decentralized manner. By managing the idle computational resources on vehicles and using them efficiently, the proposed AVE framework can provide computation services in dynamic vehicular environments without requiring particular infrastructures to be deployed. Specifically, this paper introduces a workflow to support the autonomous organization of vehicular edges. Efficient job caching is proposed to better schedule jobs based on the information collected on neighboring vehicles, including GPS information. A scheduling algorithm based on ant colony optimization is designed to solve this job assignment problem. Extensive simulations are conducted, and the simulation results demonstrate the superiority of this approach over competing schemes in typical urban and highway scenarios.
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ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2017.2714704