Multiobjective computation offloading for workflow management in cloudlet‐based mobile cloud using NSGA‐II. (18th December 2018)

• Record Type: Journal Article
• Authors: Xu, Xiaolong; Fu, Shucun; Yuan, Yuan; Luo, Yun; Qi, Lianyong; Lin, Wenmin; Dou, Wanchun
• Other Names: Pang Shaoning guestEditor.; Zhang Xuyun guestEditor.; Ikeda Kazushi guestEditor.; Puthal Deepak guestEditor.; Li Jianxin guestEditor.; Sarrafzahed Abdolhossein guestEditor.
• Is Part Of: Computational intelligence. Volume 35:Number 3(2019)
• Page Start: 476
• Page End: 495
• Publication Date: 2018-12-18
• Subjects: cloudlet -- computation offloading -- deadline -- energy -- workflow; Artificial intelligence -- Periodicals; Computational linguistics -- Periodicals; 006.3
• DOI: 10.1111/coin.12197
• Languages: English
• ISSNs: 0824-7935

Abstract

Abstract: 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.