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A Novel Probabilistic-Performance-Aware and Evolutionary Game-Theoretic Approach to Task Offloading in the Hybrid Cloud-Edge Environment

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Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom 2020)

Abstract

The mobile edge computing (MEC) paradigm provides a promising solution to solve the resource-insufficiency problem in mobile terminals by offloading computation-intensive and delay-sensitive tasks to nearby edge nodes. However, pure edge resources can be limited and insufficient for computational-intensive applications raised by multiple users, which calls for a hybrid architecture with a centralized cloud server and multiple edge nodes and smart resource management strategies in such hybrid environment. The problem is however challenging due to the distributed nature and intrinsic dynamicness of the environment. Existing researches in this direction mainly see that edge servers are with constant performance and consider the offloading decision-making as a static optimization problem. In this paper, instead, we consider that geographically distributed edge servers are with time-varying performance and introduce a dynamic offloading strategy based on a probabilistic evolutionary game-theoretic framework. To validate our proposed framework, we conduct experimental case studies based on a real-world dataset of cloud edge resource locations and show that our proposed approach outperforms traditional ones in terms of multiple metrics.

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Acknowledgement

This work is supported in part by the Graduate Scientific Research and Innovation Foundation of Chongqing, China (Grant No. CYB20062 and CYS20066), and the Fundamental Research Funds for the Central Universities (China) under Project 2019CDXYJSJ0022.

Author information

Authors and Affiliations

  1. Software Theory and Technology Chongqing Key Lab, Chongqing University, Chongqing, China

    Ying Lei & Yunni Xia

  2. School of Mathematics, Kunming University of Science and Technology, Yunnan, 650500, China

    Wanbo Zheng

  3. School of Computer and Information Engineering, Jiangxi Normal University, Nanchang, China

    Yong Ma

  4. Chongqing Key Laboratory of Smart Electronics Reliability Technology, Chongqing, China

    Qing Xia

Authors
  1. Ying Lei
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  2. Wanbo Zheng
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  3. Yong Ma
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  4. Yunni Xia
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  5. Qing Xia
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Corresponding authors

Correspondence to Wanbo Zheng or Yunni Xia .

Editor information

Editors and Affiliations

  1. Shanghai University, Shanghai, China

    Honghao Gao

  2. Xi’an Jiaotong-Liverpool University, Suzhou, China

    Xinheng Wang

  3. London South Bank University, London, UK

    Muddesar Iqbal

  4. Hangzhou Dianzi University, Hangzhou, China

    Yuyu Yin

  5. Zhejiang University, Hangzhou, China

    Jianwei Yin

  6. Fudan University, Shanghai, China

    Ning Gu

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Lei, Y., Zheng, W., Ma, Y., Xia, Y., Xia, Q. (2021). A Novel Probabilistic-Performance-Aware and Evolutionary Game-Theoretic Approach to Task Offloading in the Hybrid Cloud-Edge Environment. In: Gao, H., Wang, X., Iqbal, M., Yin, Y., Yin, J., Gu, N. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 349. Springer, Cham. https://doi.org/10.1007/978-3-030-67537-0_16

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  • DOI: https://doi.org/10.1007/978-3-030-67537-0_16

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  • Online ISBN: 978-3-030-67537-0

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