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Considering User Distribution and Cost Awareness to Optimize Server Deployment

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Big Data (BigData 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1120))

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Abstract

In edge computing systems, it is crucial issue to select suitable placement sites and quantity of servers so as to realize the low latency of Internet of Things (IoT) applications and balance the sever utilization. Hence, this paper proposes a cost-aware edge server optimization deployment method. Firstly, we model the edge server placement problem as a Mixed Integer Nonlinear Programming problem (MNIP), which comprehensively considers the resource allocation ratio, regional average load, and access delay. And then, the Benders decomposition algorithm is employed to solve it. The simulation results show that the proposed method can find better solution to place the edge micro datacenter (MDC) compared with the state-of-art server deployment strategies in terms of latency for applications and utilization of resources.

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Author information

Authors and Affiliations

  1. Nanyang Institute of Technology, Nanyang, 473000, China

    Yanling Shao & Wenyong Dong

  2. Computer School, Wuhan University, Wuhan, 430072, China

    Wenyong Dong

  3. Department of Computer and Science, Wuhan University of Technology, Wuhan, 430063, China

    Yanling Shao

Authors
  1. Yanling Shao
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  2. Wenyong Dong
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Corresponding author

Correspondence to Wenyong Dong .

Editor information

Editors and Affiliations

  1. Huazhong University of Science and Technology, Wuhan, China

    Hai Jin

  2. East China Normal University, Shanghai, China

    Xuemin Lin

  3. Chinese Academy of Sciences, Beijing, China

    Xueqi Cheng

  4. Huazhong University of Science and Technology, Wuhan, China

    Xuanhua Shi

  5. National University of Defense Technology, Changsha, China

    Nong Xiao

  6. Nanjing University, Nanjing, China

    Yihua Huang

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© 2019 Springer Nature Singapore Pte Ltd.

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Shao, Y., Dong, W. (2019). Considering User Distribution and Cost Awareness to Optimize Server Deployment. In: Jin, H., Lin, X., Cheng, X., Shi, X., Xiao, N., Huang, Y. (eds) Big Data. BigData 2019. Communications in Computer and Information Science, vol 1120. Springer, Singapore. https://doi.org/10.1007/978-981-15-1899-7_10

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  • DOI: https://doi.org/10.1007/978-981-15-1899-7_10

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-1898-0

  • Online ISBN: 978-981-15-1899-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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