Mobile-Edge Computation Offloading for Ultradense IoT Networks

Hongzhi Guo, Jiajia Liu, Jie Zhang, Wen Sun, Nei Kato

Research output: Contribution to journalArticlepeer-review

233 Citations (Scopus)


The emergence of massive Internet of Things (IoT) mobile devices (MDs) and the deployment of ultradense 5G cells have promoted the evolution of IoT toward ultradense IoT networks. In order to meet the diverse quality-of-service and quality of experience demands from the ever-increasing IoT applications, the ultradense IoT networks face unprecedented challenges. Among them, a fundamental one is how to address the conflict between the resource-hungry IoT mobile applications and the resource-constrained IoT MDs. By offloading the IoT MDs' computation tasks to the edge servers deployed at the radio access infrastructures, including macro base station (MBS) and small cells, mobile-edge computation offloading (MECO) provides us a promising solution. However, note that available MECO research mostly focused on single-tier base station scenario and computation offloading between the MDs and the edge server connected to the MBS. Little works can be found on performing MECO in ultradense IoT networks, i.e., a multiuser ultradense edge server scenario. Toward this end, we provide this paper to study the MECO problem in ultradense IoT networks, and propose a two-tier game-theoretic greedy offloading scheme as our solution. Extensive numerical results corroborate the superior performance of conducting computation offloading among multiple edge servers in ultradense IoT networks.

Original languageEnglish
Article number8361406
Pages (from-to)4977-4988
Number of pages12
JournalIEEE Internet of Things Journal
Issue number6
Publication statusPublished - 2018 Dec


  • Edge computing
  • Internet of Things (IoT)
  • Mobile-edge computation offloading (MECO)
  • Mobile-edge computing (MEC)
  • Ultradense IoT network
  • Ultradense network (UDN)


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