A Hybrid Task Scheduling Scheme for Heterogeneous Vehicular Edge Systems

Enhanced wireless communication improves the connectivity of vehicular networks in which vehicles are utilized as infrastructures for communication and computation. Thus, a new concept "Vehicular Edge Computing (VEC)" is formed. As VEC utilizes a collaborative multitude of near-user edge r...

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Veröffentlicht in:	IEEE access Jg. 7; S. 1
Hauptverfasser:	Chen, Xiao, Thomas, Nigel, Zhan, Tianming, Ding, Jie
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.01.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Ad hoc networks Algorithms Computational fluid dynamics Dynamic scheduling Edge Computing Fluid flow Formal Modelling Heuristic algorithms Internet of Vehicles Performance evaluation Queues Schedules Scheduling Scheduling Algorithm Scheduling algorithms Servers Task analysis Task scheduling Vehicles Wireless communications
ISSN:	2169-3536, 2169-3536
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Abstract	Enhanced wireless communication improves the connectivity of vehicular networks in which vehicles are utilized as infrastructures for communication and computation. Thus, a new concept "Vehicular Edge Computing (VEC)" is formed. As VEC utilizes a collaborative multitude of near-user edge resources (i.e. vehicles) in the Internet of Vehicles, the capability of these joint resources becomes heterogeneous especially in their movements. Therefore, one critical problem is how to efficiently schedule each task under such mobile environments. For the reason, we propose a hybrid dynamic scheduling scheme (HDSS) that has the ability to optimize the task scheduling dynamically based on the changeable system environments. HDSS provides a decision function (DF) to select a better-performed scheduling algorithm from two provided candidates: the queue-based dynamic scheduling (QDS) algorithm and the time-based dynamic scheduling (TDS). QDS coincides with the Join-the-Shortest Queue scheme, which decides the scheduling by sorting out a server with the shortest queue-length; nevertheless, TDS is novel scheme that is designed to implement task allocation by estimating the waiting time of each server in order to select a server with the fastest response. Finally, this research generates formal models of each scheduling algorithm and the hybrid scheduling scheme to conduct performance evaluation with a fluid flow approximation technique. The analysis results in a superior performance of HDSS in the unstable VEC environments.
AbstractList	Enhanced wireless communication improves the connectivity of vehicular networks in which vehicles are utilized as infrastructures for communication and computation. Thus, a new concept "Vehicular Edge Computing (VEC)" is formed. As VEC utilizes a collaborative multitude of near-user edge resources (i.e. vehicles) in the Internet of Vehicles, the capability of these joint resources becomes heterogeneous especially in their movements. Therefore, one critical problem is how to efficiently schedule each task under such mobile environments. For the reason, we propose a hybrid dynamic scheduling scheme (HDSS) that has the ability to optimize the task scheduling dynamically based on the changeable system environments. HDSS provides a decision function (DF) to select a better-performed scheduling algorithm from two provided candidates: the queue-based dynamic scheduling (QDS) algorithm and the time-based dynamic scheduling (TDS). QDS coincides with the Join-the-Shortest Queue scheme, which decides the scheduling by sorting out a server with the shortest queue-length; nevertheless, TDS is novel scheme that is designed to implement task allocation by estimating the waiting time of each server in order to select a server with the fastest response. Finally, this research generates formal models of each scheduling algorithm and the hybrid scheduling scheme to conduct performance evaluation with a fluid flow approximation technique. The analysis results in a superior performance of HDSS in the unstable VEC environments.
Author	Ding, Jie Chen, Xiao Zhan, Tianming Thomas, Nigel
Author_xml	– sequence: 1 givenname: Xiao surname: Chen fullname: Chen, Xiao organization: State Key Laboratory of Software Development Environment at Beihang University, Beijing, China and School of Informatics, University of Edinburgh, Edinburgh, UK, EH8 9AB – sequence: 2 givenname: Nigel surname: Thomas fullname: Thomas, Nigel organization: School of Computing Science, Newcastle University, Newcastle Upon Tyne, UK – sequence: 3 givenname: Tianming surname: Zhan fullname: Zhan, Tianming organization: School of Information Engineering, Nanjing Audit University, Nanjing, 211815, China – sequence: 4 givenname: Jie surname: Ding fullname: Ding, Jie organization: China Institute of FTZ Supply Chain, Shanghai Maritime University, Shanghai, China
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SubjectTerms	Ad hoc networks Algorithms Computational fluid dynamics Dynamic scheduling Edge Computing Fluid flow Formal Modelling Heuristic algorithms Internet of Vehicles Performance evaluation Queues Schedules Scheduling Scheduling Algorithm Scheduling algorithms Servers Task analysis Task scheduling Vehicles Wireless communications
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Title	A Hybrid Task Scheduling Scheme for Heterogeneous Vehicular Edge Systems
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