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Optimal mobile device selection for mobile cloud service providing

Authors:

Shangguang Wang,

Fangchun YangAuthors Info & Claims

The Journal of Supercomputing, Volume 72, Issue 8

Pages 3222 - 3235

https://doi.org/10.1007/s11227-016-1704-0

Published: 01 August 2016 Publication History

Abstract

With the rapid growth of the mobile devices and the emergence of cloud computing, mobile cloud computing has gained widespread interest. In mobile cloud computing, a large-scale collection of mobile devices cooperate with each other to provide a cloud service at the edge. However, the improper mobile device selection has a negative effect on the quality of service. Existing methods are difficult to solve the problem, because they do not take the status and the historical characteristics of the mobile devices into consideration. This paper introduces a device status-aware and stability-aware mobile device selection method. Firstly, a model is designed to store the status and the historical characteristics of each mobile device. Secondly, an optimized cloud model is employed to evaluate the stability of each mobile device. Lastly, an optimal mobile device searching algorithm is presented to select the optimal mobile device. We provide an extensive evaluation of our method. The results show that our method can increase the quality of mobile cloud service compared with the traditional method.

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Cited By

Koukosias AAnagnostopoulos CKolomvatsos K(2025)Task-Aware Data Selectivity in Pervasive Edge Computing EnvironmentsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.348553137:1(513-525)Online publication date: 1-Jan-2025
https://dl.acm.org/doi/10.1109/TKDE.2024.3485531
Pramanik PPal SChoudhury P(2024)Mobile crowd computing: potential, architecture, requirements, challenges, and applicationsThe Journal of Supercomputing10.1007/s11227-023-05545-080:2(2223-2318)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1007/s11227-023-05545-0
Papathanasiou DKolomvatsos K(2024)Data management and selectivity in collaborative pervasive edge computingComputing10.1007/s00607-024-01297-8106:8(2561-2584)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s00607-024-01297-8
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Published In

cover image The Journal of Supercomputing

The Journal of Supercomputing Volume 72, Issue 8

August 2016

370 pages

ISSN:0920-8542

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Copyright © Copyright © 2016 Springer Science+Business Media New York.

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 August 2016

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Cited By

Koukosias AAnagnostopoulos CKolomvatsos K(2025)Task-Aware Data Selectivity in Pervasive Edge Computing EnvironmentsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.348553137:1(513-525)Online publication date: 1-Jan-2025
https://dl.acm.org/doi/10.1109/TKDE.2024.3485531
Pramanik PPal SChoudhury P(2024)Mobile crowd computing: potential, architecture, requirements, challenges, and applicationsThe Journal of Supercomputing10.1007/s11227-023-05545-080:2(2223-2318)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1007/s11227-023-05545-0
Papathanasiou DKolomvatsos K(2024)Data management and selectivity in collaborative pervasive edge computingComputing10.1007/s00607-024-01297-8106:8(2561-2584)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s00607-024-01297-8
Dutta Pramanik PBiswas TChoudhury P(2022)Multicriteria-based Resource-Aware Scheduling in Mobile Crowd Computing: A Heuristic ApproachJournal of Grid Computing10.1007/s10723-022-09633-y21:1Online publication date: 20-Dec-2022
https://dl.acm.org/doi/10.1007/s10723-022-09633-y
Nooraei Abadeh MAjoudanian S(2021)Reconfigurable edge as a service: enhancing edges using quality-based solutionsThe Journal of Supercomputing10.1007/s11227-020-03579-277:7(6754-6787)Online publication date: 1-Jul-2021
https://dl.acm.org/doi/10.1007/s11227-020-03579-2
Shahraki AGeitle MHaugen Ø(2020)A comparative node evaluation model for highly heterogeneous massive‐scale Internet of Things‐Mist networksTransactions on Emerging Telecommunications Technologies10.1002/ett.392431:12Online publication date: 22-Dec-2020
https://dl.acm.org/doi/10.1002/ett.3924
(2018)Emerging issues and challenges for cloud data at the edgeInternational Journal of Web and Grid Services10.1504/IJWGS.2018.09074114:2(123-145)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1504/IJWGS.2018.090741
(2018)PSPOInternational Journal of Web and Grid Services10.1504/IJWGS.2018.09074014:2(170-199)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1504/IJWGS.2018.090740

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