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

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dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorZhu, Chaoen_US
dc.contributor.authorTao, Jinen_US
dc.contributor.authorPastor Figueroa, Giancarloen_US
dc.contributor.authorXiao, Yuen_US
dc.contributor.authorJi, Yushengen_US
dc.contributor.authorZhou, Quanen_US
dc.contributor.authorLi, Yongen_US
dc.contributor.authorYlä-Jääski, Anttien_US
dc.contributor.departmentDepartment of Computer Scienceen
dc.contributor.departmentDepartment of Electrical Engineering and Automationen
dc.contributor.departmentDepartment of Communications and Networkingen
dc.contributor.groupauthorHelsinki Institute for Information Technology (HIIT)en
dc.contributor.groupauthorProfessorship Ylä-Jääski A.en
dc.contributor.groupauthorMobile Cloud Computingen
dc.contributor.groupauthorRobotic Instrumentsen
dc.contributor.groupauthorComputer Science - Computing Systems (ComputingSystems)en
dc.contributor.organizationNational Institute of Informaticsen_US
dc.contributor.organizationTsinghua Universityen_US
dc.date.accessioned2018-10-24T09:40:08Z
dc.date.available2018-10-24T09:40:08Z
dc.date.issued2019-06en_US
dc.description| openaire: EC/H2020/815191/EU//PriMO-5G
dc.description.abstractWith 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.description.versionPeer revieweden
dc.format.extent12
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationZhu, C, Tao, J, Pastor Figueroa, G, Xiao, Y, Ji, Y, Zhou, Q, Li, Y & Ylä-Jääski, A 2019, ' Folo: Latency and Quality Optimized Task Allocation in Vehicular Fog Computing ', IEEE Internet of Things Journal, vol. 6, no. 3, pp. 4150 - 4161 . https://doi.org/10.1109/JIOT.2018.2875520en
dc.identifier.doi10.1109/JIOT.2018.2875520en_US
dc.identifier.issn2327-4662
dc.identifier.otherPURE UUID: 79cdeb37-0ef9-4532-812c-63c568ddd48ben_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/79cdeb37-0ef9-4532-812c-63c568ddd48ben_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/36100736/AALTO_Folo_Latency_and_Quality_Optimized_Task_Allocation_in_Vehicular_Fog_Computing.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/34467
dc.identifier.urnURN:NBN:fi:aalto-201810245529
dc.language.isoenen
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/815191/EU//PriMO-5Gen_US
dc.relation.ispartofseriesIEEE Internet of Things Journalen
dc.rightsopenAccessen
dc.subject.keywordComputing Offloadingen_US
dc.subject.keywordVehicular Fog Computing (VFC)en_US
dc.subject.keywordDynamic Task Allocationen_US
dc.subject.keywordLinear programming (LP)en_US
dc.subject.keywordBinary Particle Swarm Optimization (BPSO)en_US
dc.titleFolo: Latency and Quality Optimized Task Allocation in Vehicular Fog Computingen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
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