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SOSW: scalable and optimal nearsighted location selection for fog node deployment and routing in SDN-based wireless networks for IoT systems

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Abstract

In a fog computing (FC) architecture, cloud services migrate towards the network edge and operate via edge devices such as access points (AP), routers, and switches. These devices become part of a virtualization infrastructure and are referred to as “fog nodes.” Recently, software-defined networking (SDN) has been used in FC to improve its control and manageability. The current SDN-based FC literature has overlooked two issues: (a) fog nodes’ deployment at optimal locations and (b) SDN best path computation for data flows based on constraints (i.e., end-to-end delay and link utilization). To solve these optimization problems, this paper suggests a novel approach, called scalable and optimal near-sighted location selection for fog node deployment and routing in SDN-based wireless networks for IoT systems (SOSW). First, the SOSW model uses singular-value decomposition (SVD) and QR factorization with column pivoting linear algebra methods on the traffic matrix of the network to compute the optimal locations for fog nodes, and second, it introduces a new heuristic-based traffic engineering algorithm, called the constraint-based shortest path algorithm (CSPA), which uses ant colony optimization (ACO) to optimize the path computation process for task offloading. The results show that our proposed approach significantly reduces average latency and energy consumption in comparison with existing approaches.

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Notes

  1. This is true in terms of storage, energy, and computing

  2. http://mininet.org

  3. http://github.com/noxrepo/pox

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Funding

The work was supported by the “National Natural Science Foundation of China” grant no. 61902052, “National Key Research and Development Plan” grant no. 2017YFC0821003-2, “Science and Technology Major Industrial Project of Liaoning Province” grant no. 2020JH1/10100013, “Dalian Science and Technology Innovation Fund” grants no. 2019J11CY004 and 2020JJ26GX037, Science Foundation Ireland Research Centres Programme grants no. 12/RC/2289_P2 (Insight) and 16/SP/3804 (ENABLE) and “Fundamental Research Funds for the Central Universities” grants no. DUT20ZD210 and DUT20TD107.

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Authors and Affiliations

  1. School of Software, Dalian University of Technology, Dalian, China

    Muhammad Ibrar, Lei Wang & Khalid Ibrahim Qureshi

  2. Key Lab of Ubiquitous Network and Service Software of Liaoning Province, Shenzhen, China

    Lei Wang

  3. Peng Cheng Laboratory, Shenzhen, China

    Lei Wang

  4. School of Electronic Engineering, Dublin City University, Dublin, Ireland

    Gabriel-Miro Muntean

  5. Department of Computer Science, COMSATS University Islamabad, Wah Campus, Islamabad, Pakistan

    Nadir Shah

  6. Department of Computer Science, Abdul Wali Khan University Mardan (AWKUM), Mardan, Pakistan

    Aamir Akbar

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  1. Muhammad Ibrar
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  2. Lei Wang
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  3. Gabriel-Miro Muntean
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  4. Nadir Shah
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  5. Aamir Akbar
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  6. Khalid Ibrahim Qureshi
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Correspondence to Muhammad Ibrar or Lei Wang.

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Ibrar, M., Wang, L., Muntean, GM. et al. SOSW: scalable and optimal nearsighted location selection for fog node deployment and routing in SDN-based wireless networks for IoT systems. Ann. Telecommun. 76, 331–341 (2021). https://doi.org/10.1007/s12243-021-00845-z

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  • DOI: https://doi.org/10.1007/s12243-021-00845-z

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