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Efficient multi-tasks scheduling algorithm in mobile cloud computing with time constraints

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Abstract

The explosive growth of mobile devices and the rapid development of wireless networks and mobile computing technologies have stimulated the emergence of many new computing paradigms, such as Fog Computing, Mobile Cloud Computing (MCC) etc. These newly emerged computation paradigms try to promote the mobile applications’ Quality of Service (QoS) through allowing the mobile devices to offload their computation tasks to the edge cloud and provide their idle computation capabilities for executing other devices’ offloaded tasks. Therefore, it is very critical to efficiently schedule the offloaded tasks especially when the available computation, storage, communication resources and energy supply are limited. In this paper, we investigate the MCC-assisted execution of multi-tasks scheduling problem in hybrid MCC architecture. Firstly, this problem is formulated as an optimization problem. Secondly, a Cooperative Multi-tasks Scheduling based on Ant Colony Optimization algorithm (CMSACO) is put forward to tackle this problem, which considers task profit, task deadline, task dependence, node heterogeneity and load balancing. Finally, a series of simulation experiments are conducted to evaluate the performance of the proposed scheduling algorithm. Experimental results have shown that our proposal is more efficient than a few typical existing algorithms.

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Acknowledgements

This research was supported in part by the National Natural Science Foundation of China under Grant No. 61402521, the Jiangsu Province Natural Science Foundation of China under Grant No. BK20140068 and No. BK20150201, the Major State Basic Research Development Program of China (973 Program) No. 2012CB315806.

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Authors and Affiliations

  1. College of Communications Engineering, PLA University of Science and Technology, Nanjing, 210007, China

    Tongxiang Wang

  2. Nanjing Telecommunication Technology Research Institute, Nanjing, 210007, China

    Xianglin Wei & Jianhua Fan

  3. School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, 221116, China

    Chaogang Tang

Authors
  1. Tongxiang Wang
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  2. Xianglin Wei
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  3. Chaogang Tang
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  4. Jianhua Fan
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Corresponding author

Correspondence to Xianglin Wei.

Additional information

This article is part of the Topical Collection: Special Issue on Fog Computing on Wheels

Guest Editors: Hongzi Zhu, Tom H. Luan, Mianxiong Dong, and Peng Cheng

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Wang, T., Wei, X., Tang, C. et al. Efficient multi-tasks scheduling algorithm in mobile cloud computing with time constraints. Peer-to-Peer Netw. Appl. 11, 793–807 (2018). https://doi.org/10.1007/s12083-017-0561-9

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  • DOI: https://doi.org/10.1007/s12083-017-0561-9

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