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  • IoT Edge Computing

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Deploying Edge Computing Nodes for Large-scale IoT: A Diversity Aware Approach

Research output: Contribution to journalJournal article

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  • Zhiwei Zhao
  • Geyong Min
  • Weifeng Gao
  • Yulei Wu
  • Hancong Duan
  • Qiang Ni
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<mark>Journal publication date</mark>10/2018
<mark>Journal</mark>IEEE Internet of Things Journal
Issue number5
Volume5
Number of pages9
Pages (from-to)3606 - 3614
Publication statusPublished
Early online date9/04/18
Original languageEnglish

Abstract

The recent advances in microelectronics and communications have led to the development of large-scale IoT networks, where tremendous sensory data is generated and needs to be processed. To support real-time processing for large-scale IoT, deploying edge servers with storage and computational capability is a promising approach. In this paper, we carefully analyze the impacting factors and key challenges for edge node deployment. We then propose a novel three-phase deployment approach which considers both traffic diversity and the wireless diversity of IoT. The proposed work aims at providing real-time processing service for the IoT network and reducing the required number of edge nodes. We conducted extensive simulation experiments, the results show that compared to the existing works that overlooked the two kinds of diversities, the proposed work greatly reduces the number of edge nodes and improves the throughput between IoT and edge nodes.

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©2018 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.