Intelligent task offloading for smart devices in mobile edge computing

Document Type

Conference Proceeding

Publication Title

2022 International Wireless Communications and Mobile Computing, IWCMC 2022

First Page

312

Last Page

317

Publisher

IEEE

School

School of Engineering

RAS ID

45473

Comments

Saleem, O., Munawar, S., Tu, S., Ali, Z., Waqas, M., & Abbas, G. (2022, May). Intelligent task offloading for smart devices in mobile edge computing. In 2022 International Wireless Communications and Mobile Computing (IWCMC) (pp. 312-317). IEEE. https://doi.org/10.1109/IWCMC55113.2022.9825117

Abstract

Mobile edge computing (MEC) is used for compu-tationally complex applications by offloading it to the nearby edge server either partially or entirely. The problem arises of selecting whether the component is to be offloaded to the mobile edge server (MES) for execution, or it needs to be executed locally. Therefore, we propose a time-efficient decision offloading scheme (TEDOS) to derive a data set and train an artificial neural network (ANN) on the derived data set. TEDOS provide the smart decision on the optimal permutation of the divided components based on delay. We developed a mathematical model for delays in communication, execution and component queuing. We obtained a final delay for all possible permutations of component offloading policies. Our model obtained 91 % accurate results as compared to the existing schemes. The simulation result shows that our proposed model outperforms the state-of-the-art.

DOI

10.1109/IWCMC55113.2022.9825117

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