TY - GEN
T1 - Energy-Efficient Computation Offloading in Cloudlet-Based Mobile Cloud Using NSGA-II
AU - Xu, Xiaolong
AU - Fu, Shucun
AU - Yuan, Yuan
AU - Qi, Lianyong
AU - Dou, Wanchun
N1 - Publisher Copyright:
© 2018 IPSJ.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - Cloudlet is a novel computing paradigm, introduced to the mobile cloud service framework, aiming to alleviate the communication delay between the mobile devices and the cloud platform. 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 solutions for the deadline-constrained workflows in the cloudlet-based mobile cloud, since a cloudlet often has limited resources. In this paper, an Energy-efficient Computation Offloading method, named ECO, is proposed to address the above challenge. Technically, an energy consumption model for computing tasks is established in the cloudlet-based mobile computing. Then a corresponding computation offloading method, by leveraging NSGA-II (Non-dominated Sorting Genetic Algorithm II), is designed to achieve the goal of energy saving for each mobile device, while satisfying the deadline constraints. 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, aiming to alleviate the communication delay between the mobile devices and the cloud platform. 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 solutions for the deadline-constrained workflows in the cloudlet-based mobile cloud, since a cloudlet often has limited resources. In this paper, an Energy-efficient Computation Offloading method, named ECO, is proposed to address the above challenge. Technically, an energy consumption model for computing tasks is established in the cloudlet-based mobile computing. Then a corresponding computation offloading method, by leveraging NSGA-II (Non-dominated Sorting Genetic Algorithm II), is designed to achieve the goal of energy saving for each mobile device, while satisfying the deadline constraints. Finally, extensive experimental evaluations are conducted to demonstrate the efficiency and effectiveness of our proposed method.
KW - cloudlet
KW - computation offloading
KW - dead-line
KW - energy
KW - workflow
UR - https://www.scopus.com/pages/publications/85063419196
U2 - 10.23919/ICMU.2018.8653606
DO - 10.23919/ICMU.2018.8653606
M3 - 会议稿件
AN - SCOPUS:85063419196
T3 - 2018 11th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2018
BT - 2018 11th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2018
Y2 - 5 October 2018 through 8 October 2018
ER -