A1 Journal article (refereed)
Joint optimization of energy and delay for computation offloading in cloudlet-assisted mobile cloud computing (2019)

Liu, L., Guo, X., Chang, Z., & Ristaniemi, T. (2019). Joint optimization of energy and delay for computation offloading in cloudlet-assisted mobile cloud computing. Wireless Networks, 25(4), 2027-2040. https://doi.org/10.1007/s11276-018-1794-0

JYU authors or editors

Publication details

All authors or editors: Liu, Liqing; Guo, Xijuan; Chang, Zheng; Ristaniemi, Tapani

Journal or series: Wireless Networks

ISSN: 1022-0038

eISSN: 1572-8196

Publication year: 2019

Volume: 25

Issue number: 4

Pages range: 2027-2040

Publisher: Springer New York LLC

Publication country: United States

Publication language: English

DOI: https://doi.org/10.1007/s11276-018-1794-0

Publication open access: Not open

Publication channel open access:


In the mobile cloud computing (MCC), although offloading requests to the distant central cloud or nearby cloudlet can reduce energy consumption at the mobile devices (MDs), it may also incur a large execution delay including transmission time from the MDs to the servers and waiting time at the servers. Therefore, how to balance the energy consumption and delay performance is of great research importance. In this paper, we bring a thorough study on the energy consumption and execution delay of offloading process in a cloudlet-assisted MCC. Specifically, heterogeneity of request executions are explicitly considered. When there is a small cell base station (SBS) available, the MDs can connect with cloudlet via the SBS and if only a macro cell base station is available, the MD can connect with the central cloud through it. We derive the analytic results of the energy consumption and execution delay performance with the assumption of three different queue models at the MD, cloudlet and central cloud. Based on the theoretical analysis, the multi-objective optimization problems are formulated with the joint objectives to minimize the energy consumption and delay by finding the optimal offloading probability. The simulation results demonstrate the effectiveness of the proposed scheme.

Keywords: cloud services; delay (technology); optimisation

Free keywords: energy consumption; execution delay; local execution; offloading probability; cloudlet-assistant MCC

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Ministry reporting: Yes

Reporting Year: 2019

JUFO rating: 1

Last updated on 2021-08-06 at 23:23