Mobile Edge Computing, " Joint Optimization Offloading Strategy of Execution Time and Energy Consumption of", The International Arab Journal of Information Technology (IAJIT) ,Volume 18, Number 05, pp. 87 - 94, September 2021, doi: 10.34028/iajit/18/5/11 .

Abstract: As mobile devices become more and more powerful, applications generate a large number of computing tasks, and mobile devices themselves cannot meet the needs of users. This article proposes a computation offloading model in which execution units including mobile devices, edge server, and cloud server. Previous studies on joint optimization only considered tasks execution time and the energy consumption of mobile devices, and ignored the energy consumption of edge and cloud server. However, edge server and cloud server energy consumption have a significant impact on the final offloading decision. This paper comprehensively considers execution time and energy consumption of three execution units, and formulates task offloading decision as a single-objective optimization problem. Genetic algorithm with elitism preservation and random strategy is adopted to obtain optimal solution of the
URL: https://iajit.org/paper/2071

@ARTICLE{2071,
author={Mobile Edge Computing},
journal={The International Arab Journal of Information Technology (IAJIT)},
title={Joint Optimization Offloading Strategy of Execution Time and Energy Consumption of},
volume={18},
number={05},
pages={87 - 94},
doi={10.34028/iajit/18/5/11 },
year={1970}

,abstract={As mobile devices become more and more powerful, applications generate a large number of computing tasks, and mobile devices themselves cannot meet the needs of users. This article proposes a computation offloading model in which execution units including mobile devices, edge server, and cloud server. Previous studies on joint optimization only considered tasks execution time and the energy consumption of mobile devices, and ignored the energy consumption of edge and cloud server. However, edge server and cloud server energy consumption have a significant impact on the final offloading decision. This paper comprehensively considers execution time and energy consumption of three execution units, and formulates task offloading decision as a single-objective optimization problem. Genetic algorithm with elitism preservation and random strategy is adopted to obtain optimal solution of the},
keywords={},
ISSN={2413-9351},
month={Jan}}

TY - JOUR
TI - Joint Optimization Offloading Strategy of Execution Time and Energy Consumption of
T2 -
SP - 87
EP - 94
AU - Mobile Edge Computing
DO - 10.34028/iajit/18/5/11
JO - The International Arab Journal of Information Technology (IAJIT)
IS - 9
SN - 2413-9351
VO - 18
VL - 18
JA -
Y1 - Jan 1970
ER -
PY - 1970

AB - As mobile devices become more and more powerful, applications generate a large number of computing tasks, and mobile devices themselves cannot meet the needs of users. This article proposes a computation offloading model in which execution units including mobile devices, edge server, and cloud server. Previous studies on joint optimization only considered tasks execution time and the energy consumption of mobile devices, and ignored the energy consumption of edge and cloud server. However, edge server and cloud server energy consumption have a significant impact on the final offloading decision. This paper comprehensively considers execution time and energy consumption of three execution units, and formulates task offloading decision as a single-objective optimization problem. Genetic algorithm with elitism preservation and random strategy is adopted to obtain optimal solution of the