Fog following me: Latency and quality balanced task allocation in vehicular fog computing

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Researchers

Research units

  • Tsinghua University

Abstract

Emerging vehicular applications, such as real-time situational awareness and cooperative lane change, demand for sufficient computing resources at the edge to conduct time-critical and data-intensive tasks. This paper proposes Fog Following Me (Folo), a novel solution for latency and quality balanced task allocation in vehicular fog computing. Folo is designed to support the mobility of vehicles, including ones generating tasks and the others serving as fog nodes. We formulate the process of task allocation across stationary and mobile fog nodes into a joint optimization problem, with constraints on service latency, quality loss, and fog capacity. As it is a NP-hard problem, we linearize it and solve it using Mixed Integer Linear Programming. To evaluate the effectiveness of Folo, we simulate the mobility of fog nodes at different times of day based on real-world taxi traces, and implement two representative tasks, including video streaming and real-time object recognition. Compared with naive and random fog node selection, the latency and quality balanced task allocation provided by Folo achieves higher performance. More specifically, Folo shortens the average service latency by up to 41% while reducing the quality loss by up to 60%.

Details

Original languageEnglish
Title of host publication2018 15th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)
Publication statusPublished - Jun 2018
MoE publication typeA4 Article in a conference publication
EventIEEE International Conference on Sensing, Communication and Networking - Hong Kong, China
Duration: 11 Jun 201813 Jun 2018
http://secon2018.ieee-secon.org/

Publication series

NameAnnual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks workshops
ISSN (Electronic)2155-5494

Conference

ConferenceIEEE International Conference on Sensing, Communication and Networking
Abbreviated titleSECON
CountryChina
CityHong Kong
Period11/06/201813/06/2018
Internet address

    Research areas

  • vehicular fog computing, task allocation

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