TY - JOUR
T1 - Multiobjective computation offloading for workflow management in cloudlet-based mobile cloud using NSGA-II
AU - Xu, Xiaolong
AU - Fu, Shucun
AU - Yuan, Yuan
AU - Luo, Yun
AU - Qi, Lianyong
AU - Lin, Wenmin
AU - Dou, Wanchun
N1 - Publisher Copyright:
© 2018 Wiley Periodicals, Inc.
PY - 2019
Y1 - 2019
N2 - Cloudlet is a novel computing paradigm, introduced to the mobile cloud service framework, which moves the computing resources closer to the mobile users, aiming to alleviate the communication delay between the mobile devices and the cloud platform and optimize the energy consumption for mobile devices. Currently, the mobile applications, modeled by the workflows, tend to be complicated and computation-intensive. Such workflows are required to be offloaded to the cloudlet or the remote cloud platform for execution. However, it is still a key challenge to determine the offloading resolvent for the deadline-constrained workflows in the cloudlet-based mobile cloud, since a cloudlet often has limited resources. In this paper, a multiobjective computation offloading method, named MCO, is proposed to address the above challenge. Technically, an energy consumption model for the mobile devices is established in the cloudlet-based mobile cloud. Then, a corresponding computation offloading method, by improving Nondominated Sorting Genetic Algorithm II, is designed to achieve the goal of energy saving for all the mobile device while satisfying the deadline constraints of the workflows. Finally, extensive experimental evaluations are conducted to demonstrate the efficiency and effectiveness of our proposed method.
AB - Cloudlet is a novel computing paradigm, introduced to the mobile cloud service framework, which moves the computing resources closer to the mobile users, aiming to alleviate the communication delay between the mobile devices and the cloud platform and optimize the energy consumption for mobile devices. Currently, the mobile applications, modeled by the workflows, tend to be complicated and computation-intensive. Such workflows are required to be offloaded to the cloudlet or the remote cloud platform for execution. However, it is still a key challenge to determine the offloading resolvent for the deadline-constrained workflows in the cloudlet-based mobile cloud, since a cloudlet often has limited resources. In this paper, a multiobjective computation offloading method, named MCO, is proposed to address the above challenge. Technically, an energy consumption model for the mobile devices is established in the cloudlet-based mobile cloud. Then, a corresponding computation offloading method, by improving Nondominated Sorting Genetic Algorithm II, is designed to achieve the goal of energy saving for all the mobile device while satisfying the deadline constraints of the workflows. Finally, extensive experimental evaluations are conducted to demonstrate the efficiency and effectiveness of our proposed method.
KW - cloudlet
KW - computation offloading
KW - deadline
KW - energy
KW - workflow
UR - http://www.scopus.com/inward/record.url?scp=85058694207&partnerID=8YFLogxK
U2 - 10.1111/coin.12197
DO - 10.1111/coin.12197
M3 - 文章
AN - SCOPUS:85058694207
SN - 0824-7935
VL - 35
SP - 476
EP - 495
JO - Computational Intelligence
JF - Computational Intelligence
IS - 3
ER -