Folo: Latency and Quality Optimized Task Allocation in Vehicular Fog Computing

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Zhu, Chao
dc.contributor.author Tao, Jin
dc.contributor.author Pastor Figueroa, Giancarlo
dc.contributor.author Xiao, Yu
dc.contributor.author Ji, Yusheng
dc.contributor.author Zhou, Quan
dc.contributor.author Li, Yong
dc.contributor.author Ylä-Jääski, Antti
dc.date.accessioned 2018-10-24T09:40:08Z
dc.date.available 2018-10-24T09:40:08Z
dc.date.issued 2019-06
dc.identifier.citation Zhu , C , Tao , J , Pastor Figueroa , G , Xiao , Y , Ji , Y , Zhou , Q , Li , Y & Ylä-Jääski , A 2018 , ' Folo: Latency and Quality Optimized Task Allocation in Vehicular Fog Computing ' IEEE Internet of Things Journal . DOI: 10.1109/JIOT.2018.2875520 en
dc.identifier.issn 2327-4662
dc.identifier.other PURE UUID: 79cdeb37-0ef9-4532-812c-63c568ddd48b
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/folo-latency-and-quality-optimized-task-allocation-in-vehicular-fog-computing(79cdeb37-0ef9-4532-812c-63c568ddd48b).html
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/36100736/AALTO_Folo_Latency_and_Quality_Optimized_Task_Allocation_in_Vehicular_Fog_Computing.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/34467
dc.description | openaire: EC/H2020/815191/EU//PriMO-5G
dc.description.abstract With the emerging vehicular applications such as real-time situational awareness and cooperative lane change, there exist huge demands for sufficient computing resources at the edge to conduct time-critical and data-intensive tasks. This paper proposes Folo, a novel solution for latency and quality optimized task allocation in Vehicular Fog Computing (VFC). Folo is designed to support the mobility of vehicles, including vehicles that generate tasks and the others that serve as fog nodes. Considering constraints on service latency, quality loss, and fog capacity, the process of task allocation across stationary and mobile fog nodes is formulated into a joint optimization problem. This task allocation in VFC is known as a non-deterministic polynomial-time hard (NP-hard) problem. In this paper, we present the task allocation to fog nodes as a bi-objective minimization problem, where a trade-off is maintained between the service latency and quality loss. Specifically, we propose an event-triggered dynamic task allocation (DTA) framework using Linear Programming based Optimization (LBO) and Binary Particle Swarm Optimization (BPSO). To assess the effectiveness of Folo, we simulated the mobility of fog nodes at different times of a day based on real-world taxi traces and implemented two representative tasks, including video streaming and real-time object recognition. Simulation results show that the task allocation provided by Folo can be adjusted according to actual requirements of the service latency and quality, and achieves higher performance compared with naive and random fog node selection. To be more specific, Folo shortens the average service latency by up to 27% while reducing the quality loss by up to 56%. en
dc.format.extent 12
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation info:eu-repo/grantAgreement/EC/H2020/815191/EU//PriMO-5G
dc.relation.ispartofseries IEEE Internet of Things Journal en
dc.rights openAccess en
dc.subject.other 113 Computer and information sciences en
dc.title Folo: Latency and Quality Optimized Task Allocation in Vehicular Fog Computing en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Department of Computer Science
dc.contributor.department Department of Electrical Engineering and Automation
dc.contributor.department Department of Communications and Networking
dc.contributor.department National Institute of Informatics
dc.contributor.department Tsinghua University
dc.contributor.department Helsinki Institute for Information Technology HIIT
dc.subject.keyword Computing Offloading
dc.subject.keyword Vehicular Fog Computing (VFC)
dc.subject.keyword Dynamic Task Allocation
dc.subject.keyword Linear programming (LP)
dc.subject.keyword Binary Particle Swarm Optimization (BPSO)
dc.subject.keyword 113 Computer and information sciences
dc.identifier.urn URN:NBN:fi:aalto-201810245529
dc.identifier.doi 10.1109/JIOT.2018.2875520


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