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Robust Optimization Model for Designing Emerging Cloud-Fog Networks

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Book cover Big Data, Cloud Computing, and Data Science Engineering (BCD 2019)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 844))

Abstract

I focus on designing the placement and capacity for Internet of Things (IoT) infrastructures consisting of three layers; cloud, fog, and communication. It is extremely difficult to predict the future demand of innovative IoT services; thus, I propose a robust design model for economically constructing IoT infrastructures under uncertain demands, which is formulated as a robust optimization problem. I also present a method of solving this problem, which is practically difficult to solve. I experimentally evaluated the effectiveness of the proposed model and the possibility of applying the method to this model to practical scaled networks.

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Authors and Affiliations

  1. NTT Network Technology Laboratories, 3-9-11 Midori-Cho, Musashino-Shi, Tokyo, 180-8585, Japan

    Masayuki Tsujino

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  1. Masayuki Tsujino
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Correspondence to Masayuki Tsujino .

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Editors and Affiliations

  1. Software Engineering and Information Technology Institute, Central Michigan University, Mount Pleasant, MI, USA

    Roger Lee

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Tsujino, M. (2020). Robust Optimization Model for Designing Emerging Cloud-Fog Networks. In: Lee, R. (eds) Big Data, Cloud Computing, and Data Science Engineering. BCD 2019. Studies in Computational Intelligence, vol 844. Springer, Cham. https://doi.org/10.1007/978-3-030-24405-7_1

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