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Joint Allocation of Computing and Wireless Resources to Autonomous Devices in Mobile Edge Computing

Authors:

Slađana Jošilo,

György DánAuthors Info & Claims

MECOMM'18: Proceedings of the 2018 Workshop on Mobile Edge Communications

Pages 13 - 18

https://doi.org/10.1145/3229556.3229559

Published: 07 August 2018 Publication History

Abstract

We consider the interaction between mobile edge computing (MEC) resource management and wireless devices that offload computationally intensive tasks through shared wireless links to edge cloud servers, so as to minimize their completion times. We model the interaction between the devices and the operator that optimizes the allocation of the wireless and computing resources as a Stackelberg game. We show that a pure strategy Stackelberg equilibrium exists, and we provide an efficient algorithm for computing equilibrium allocations. Our simulation results show that joint optimization of the wireless and computing resources can provide a significant reduction of completion times at little increase in computational complexity compared to a system where resource allocation is not optimized.

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Cited By

Tütüncüoğlu FDán G(2024)Joint Resource Management and Pricing for Task Offloading in Serverless Edge ComputingIEEE Transactions on Mobile Computing10.1109/TMC.2023.333491423:6(7438-7452)Online publication date: Jun-2024
https://doi.org/10.1109/TMC.2023.3334914
Qadeer ALee M(2024)HRL-Edge-Cloud: Multi-Resource Allocation in Edge-Cloud based Smart-StreetScape System using Heuristic Reinforcement LearningInformation Systems Frontiers10.1007/s10796-022-10366-226:4(1399-1415)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s10796-022-10366-2
Qadeer ALee M(2023)Deep-Deterministic Policy Gradient Based Multi-Resource Allocation in Edge-Cloud System: A Distributed ApproachIEEE Access10.1109/ACCESS.2023.324915311(20381-20398)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3249153
Show More Cited By

Index Terms

Joint Allocation of Computing and Wireless Resources to Autonomous Devices in Mobile Edge Computing
1. Networks
  1. Network algorithms
    1. Control path algorithms
      1. Network resources allocation
  2. Network services
    1. Cloud computing

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cover image ACM Conferences

MECOMM'18: Proceedings of the 2018 Workshop on Mobile Edge Communications

August 2018

56 pages

ISBN:9781450359061

DOI:10.1145/3229556

Copyright © 2018 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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SIGCOMM: ACM Special Interest Group on Data Communication

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 August 2018

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SIGCOMM '18

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SIGCOMM

SIGCOMM '18: ACM SIGCOMM 2018 Conference

August 20, 2018

Budapest, Hungary

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Cited By

Tütüncüoğlu FDán G(2024)Joint Resource Management and Pricing for Task Offloading in Serverless Edge ComputingIEEE Transactions on Mobile Computing10.1109/TMC.2023.333491423:6(7438-7452)Online publication date: Jun-2024
https://doi.org/10.1109/TMC.2023.3334914
Qadeer ALee M(2024)HRL-Edge-Cloud: Multi-Resource Allocation in Edge-Cloud based Smart-StreetScape System using Heuristic Reinforcement LearningInformation Systems Frontiers10.1007/s10796-022-10366-226:4(1399-1415)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s10796-022-10366-2
Qadeer ALee M(2023)Deep-Deterministic Policy Gradient Based Multi-Resource Allocation in Edge-Cloud System: A Distributed ApproachIEEE Access10.1109/ACCESS.2023.324915311(20381-20398)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3249153
Chu SFang ZSong SZhang ZGao CXu C(2022)Efficient Multi-Channel Computation Offloading for Mobile Edge Computing: A Game-Theoretic ApproachIEEE Transactions on Cloud Computing10.1109/TCC.2020.299414510:3(1738-1750)Online publication date: 1-Jul-2022
https://doi.org/10.1109/TCC.2020.2994145
Josilo SDan G(2021)Joint Management of Wireless and Computing Resources for Computation Offloading in Mobile Edge CloudsIEEE Transactions on Cloud Computing10.1109/TCC.2019.29237689:4(1507-1520)Online publication date: 1-Oct-2021
https://doi.org/10.1109/TCC.2019.2923768
Shakarami AShahidinejad AGhobaei‐Arani M(2020) A review on the computation offloading approaches in mobile edge computing: A g ame‐theoretic perspective Software: Practice and Experience10.1002/spe.283950:9(1719-1759)Online publication date: 23-Apr-2020
https://doi.org/10.1002/spe.2839
Josilo SDan G(2019)Wireless and Computing Resource Allocation for Selfish Computation Offloading in Edge ComputingIEEE INFOCOM 2019 - IEEE Conference on Computer Communications10.1109/INFOCOM.2019.8737480(2467-2475)Online publication date: Apr-2019
https://doi.org/10.1109/INFOCOM.2019.8737480

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