DOT: Decentralized Offloading of Tasks in OFDMA-Based Heterogeneous Computing Networks

  • Liantao Wu
  • , Zening Liu
  • , Peng Sun
  • , Honglong Chen
  • , Kunlun Wang
  • , Yong Zuo
  • , Yang Yang*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

A fundamental issue in multiaccess edge computing (MEC) is efficiently offloading multiple tasks to multiple helper nodes (MTMH), i.e., MEC servers. However, most of the existing decentralized schemes do not consider interuser interference or merely adopt time division multiple access (TDMA) as the multiple access scheme for MTMH in the heterogeneous scenario, leading to a large latency. To address these issues, we propose DOT, a novel Decentralized Offloading of Tasks scheme in orthogonal frequency division multiple access (OFDMA)-based heterogeneous MEC, to minimize the sum cost in terms of energy consumption and delay. Specifically, we first formulate DOT as an optimization problem considering the interuser interference and dynamics in communication and computation resource allocation. Then, considering the huge dimension of potential offloading decisions and conflicting objectives of different users, the total cost of each user is minimized in a distributed manner by modeling the offloading problem as a potential game. The formulated potential game is proved to be an ordinal potential game and thus admits a Nash equilibrium (NE). Further, we develop an offloading algorithm to achieve the NE by exploiting the finite improvement property. Finally, simulation results demonstrate that DOT can achieve a lower cost compared with other baselines.

Original languageEnglish
Pages (from-to)20071-20082
Number of pages12
JournalIEEE Internet of Things Journal
Volume9
Issue number20
DOIs
StatePublished - 15 Oct 2022

Keywords

  • Computation offloading
  • heterogeneous multiaccess edge computing (MEC)
  • interuser interference
  • orthogonal frequency division multiple access (OFDMA)
  • potential game

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