research-article

An Offloading Algorithm of Dense-Tasks for Mobile Edge Computing

Authors:

Jing YueAuthors Info & Claims

icWCSN '20: Proceedings of the 2020 International Conference on Wireless Communication and Sensor Networks

Pages 35 - 40

https://doi.org/10.1145/3411201.3411203

Published: 26 August 2020 Publication History

Abstract

With the increasing number of mobile devices (MDs) and computationally intensive applications, the conflict between the MDs limited computing and battery resources and the ever increasing resource demands from the mobile applications becomes more and more prominent. It is becoming more and more difficult to meet simultaneously the requirements of industrial applications in terms of latency and energy only using traditional cloud computing paradigm. Mobile edge computing (MEC), as a novel computing paradigm, promises dramatic reduction in latency, energy consumption and improve mobile service quality and enhance Quality of Experience by offloading computation-intensive tasks to edge servers in close proximity to mobile users. However, most researches of MEC offloading focused on one of two aspects: transmission delays and energy consumption. In this paper, different from these studies, three factors of energy consumption, latency and cloud computing costs are comprehensively considered. At the same time, two weight factors are introduced, which depend on the remaining power of MDs and the urgency of tasks to balance between execution delay, energy consumption and cloud computing cost. Then, the multiuser computation offloading problem is formulated as a constrained optimization problem, which is NP-hard. Due to the computation complexity of the formulated problem, An iterative heuristic task-intensive assignment algorithm is designed to make the offloading decision dynamically. Simulation results demonstrate that our algorithm outperforms the existing schemes in terms of offloading overhead.

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Cited By

Barboza VKniess J(2024)Task Allocation Based on Simulated Annealing for Edge Industrial InternetAdvanced Information Networking and Applications10.1007/978-3-031-57870-0_19(210-221)Online publication date: 10-Apr-2024
https://doi.org/10.1007/978-3-031-57870-0_19
Tang HWu HZhao YLi R(2022)Joint Computation Offloading and Resource Allocation Under Task-Overflowed Situations in Mobile-Edge ComputingIEEE Transactions on Network and Service Management10.1109/TNSM.2021.313538919:2(1539-1553)Online publication date: 1-Jun-2022
https://dl.acm.org/doi/10.1109/TNSM.2021.3135389

Index Terms

An Offloading Algorithm of Dense-Tasks for Mobile Edge Computing
1. Computer systems organization
  1. Architectures
    1. Distributed architectures
      1. Cloud computing
2. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing theory, concepts and paradigms
      1. Mobile computing

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Published In

icWCSN '20: Proceedings of the 2020 International Conference on Wireless Communication and Sensor Networks

May 2020

71 pages

ISBN:9781450377638

DOI:10.1145/3411201

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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AGH University of Science and Technology: AGH University of Science and Technology

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 August 2020

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icWCSN 2020

icWCSN 2020: 2020 International Conference on Wireless Communication and Sensor Networks

May 13 - 15, 2020

Warsaw, Poland

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Cited By

Barboza VKniess J(2024)Task Allocation Based on Simulated Annealing for Edge Industrial InternetAdvanced Information Networking and Applications10.1007/978-3-031-57870-0_19(210-221)Online publication date: 10-Apr-2024
https://doi.org/10.1007/978-3-031-57870-0_19
Tang HWu HZhao YLi R(2022)Joint Computation Offloading and Resource Allocation Under Task-Overflowed Situations in Mobile-Edge ComputingIEEE Transactions on Network and Service Management10.1109/TNSM.2021.313538919:2(1539-1553)Online publication date: 1-Jun-2022
https://dl.acm.org/doi/10.1109/TNSM.2021.3135389

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