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An OO-Based Approach of Computing Offloading and Resource Allocation for Large-Scale Mobile Edge Computing Systems

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Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom 2021)

Abstract

Mobile edge computing (MEC) is an emerging paradigm to meet the increasing real-time performance demands for Internet of Things and mobile applications. By offloading the computationally intensive workloads to edge servers, the quality of service (QoS) could be greatly improved. However, with the growing popularity of MEC, the MEC systems grow extremely large, and thus the QoS optimization suffers from search space explosion problem, making it impractical in real-life scenarios. To attack this challenge, this paper studies the joint optimization of task offloading and computational resource allocation for large-scale MEC systems. We formulate this problem as a cost minimization problem and illustrate the NP-hardness of this problem. In order to solve this problem, we divide the original problem into two sub-problems and introduce the theory of Ordinal Optimization (OO) to search for a near-optimal computing offloading and resource allocation policy within a significantly reduced search space. Finally, the efficacy of our approach is validated by simulation experiments.

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Acknowledgment

This work is supported by Beijing Nova Program (No. Z201100006820082), National Natural Science Foundation of China (No. 61972414), National Key Research and Development Plan (No. 2016YFC0303700), Beijing Natural Science Foundation (No. 4202066), and the Fundamental Research Funds for Central Universities (Nos. 2462018YJRC040 and 2462020YJRC001).

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Authors and Affiliations

  1. Beijing Key Laboratory of Petroleum Data Mining, China University of Petroleum - Beijing, Beijing, 102249, China

    Yufu Tan, Sikandar Ali, Haotian Wang & Jiwei Huang

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  1. Yufu Tan
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  2. Sikandar Ali
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  3. Haotian Wang
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  4. Jiwei Huang
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Correspondence to Jiwei Huang .

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Editors and Affiliations

  1. Shanghai University, Shanghai, China

    Honghao Gao

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

    Xinheng Wang

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Tan, Y., Ali, S., Wang, H., Huang, J. (2021). An OO-Based Approach of Computing Offloading and Resource Allocation for Large-Scale Mobile Edge Computing Systems. In: Gao, H., Wang, X. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 407. Springer, Cham. https://doi.org/10.1007/978-3-030-92638-0_5

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  • DOI: https://doi.org/10.1007/978-3-030-92638-0_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-92637-3

  • Online ISBN: 978-3-030-92638-0

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