Energy-latency tradeoff for dynamic computation offloading in vehicular fog computing

Yadav, R, Zhang, W, Kaiwartya, O ORCID: https://orcid.org/0000-0001-9669-8244, Song, H and Yu, S, 2020. Energy-latency tradeoff for dynamic computation offloading in vehicular fog computing. IEEE Transactions on Vehicular Technology, 69 (12), pp. 14198-14211. ISSN 0018-9545

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Abstract

Vehicular Fog Computing (VFC) provides solutions to relieves overload cloudlet nodes, reduces service latency during peak times, and saves energy for battery-powered cloudlet nodes by offloading user tasks to a vehicle (vehicular node) by exploiting the under-utilized computation resources of nearby vehicular node. However, the wide deployment of VFC still confronts several critical challenges: lack of energy-latency tradeoff and efficient resource allocation mechanisms. In this paper, we address the challenges and provide an Energy-efficient dynamic Computation Offloading and resources allocation Scheme (ECOS) to minimize energy consumption and service latency. We first formulate the ECOS problem as a joint energy and latency cost minimization problem while satisfying vehicular node mobility and end-to-end latency deadline constraints. We then propose an ECOS scheme with three phases. In the first phase, we propose an overload cloudlet node detection policy based on resource utilization. In the second phase, we propose a computational offloading selection policy to select a task from an overloaded cloudlet node for offloading, which minimizes offloading cost and the risk of overload. Next, we propose a heuristic approach to solve the resource allocation problem between the vehicular node and selected user tasks for energy-latency tradeoff. Extensive simulations have been conducted under realistic highway and synthetic scenarios to examine the ECOS scheme's performance. In comparison, our proposed scheme outperforms the existing schemes in terms of energy-saving, service latency, and joint energy-latency cost.

Item Type:	Journal article
Publication Title:	IEEE Transactions on Vehicular Technology
Creators:	Yadav, R., Zhang, W., Kaiwartya, O., Song, H. and Yu, S.
Publisher:	Institute of Electrical and Electronics Engineers (IEEE)
Date:	December 2020
Volume:	69
Number:	12
ISSN:	0018-9545
Identifiers:	Number Type 10.1109/tvt.2020.3040596 DOI 1448502 Other
Divisions:	Schools > School of Science and Technology
Record created by:	Linda Sullivan
Date Added:	30 Jun 2021 14:27
Last Modified:	30 Jun 2021 14:27
URI:	https://irep.ntu.ac.uk/id/eprint/43276

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