A fault‐tolerant dynamic scheduling method on hierarchical mobile edge cloud computing. (27th May 2019)

• Record Type: Journal Article
• Authors: Meng, Shunmei; Li, Qianmu; Wu, Taoran; Huang, Weijia; Zhang, Jing; Li, Weimin
• 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: 577
• Page End: 598
• Publication Date: 2019-05-27
• Subjects: dynamic scheduling -- fault‐tolerant scheduling -- hierarchical cloud -- mobile edge cloud computing; Artificial intelligence -- Periodicals; Computational linguistics -- Periodicals; 006.3
• DOI: 10.1111/coin.12219
• Languages: English
• ISSNs: 0824-7935

Abstract

Abstract: Mobile edge cloud computing has been a promising computing paradigm, where mobile users could offload their application workloads to low‐latency local edge cloud resources. However, compared with remote public cloud resources, conventional local edge cloud resources are limited in computation capacity, especially when serve large number of mobile applications. To deal with this problem, we present a hierarchical edge cloud architecture to integrate the local edge clouds and public clouds so as to improve the performance and scalability of scheduling problem for mobile applications. Besides, to achieve a trade‐off between the cost and system delay, a fault‐tolerant dynamic resource scheduling method is proposed to address the scheduling problem in mobile edge cloud computing. The optimization problem could be formulated to minimize the application cost with the user‐defined deadline satisfied. Specifically, firstly, a game‐theoretic scheduling mechanism is adopted for resource provisioning and scheduling for multiprovider mobile applications. Then, a mobility‐aware dynamic scheduling strategy is presented to update the scheduling with the consideration of mobility of mobile users. Moreover, a failure recovery mechanism is proposed to deal with the uncertainties during the execution of mobile applications. Finally, experiments are designed and conducted to validate the effectiveness of our proposal. The experimental results show that our method could achieve a trade‐off between the cost and system delay.