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VALKYRIE: a suite of topology-aware clustering approaches for cloud-based virtual network services

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Abstract

Complex networks are practical tools for modeling, studying, and analyzing complex interactions between objects. These tools are essential in understanding applications, end-users, interactions between compute nodes, and their behaviors in computer networks. Computer networks are undergoing significant expansion due to the proliferation of network devices and compute nodes. One of the main challenges in computer networks is categorizing these compute nodes into clusters of connected compute nodes within these large-scale structures sharing similar features (e.g., Central Processing Unit, memory, disk storage). This paper proposes a set of novel, dynamic, and proactive topology-aware clustering approaches, namely, an Integer Linear Program, chemical reaction optimization, and a game theory approach that leverages the Irving algorithm, originally proposed to solve the stable roommate problem, to form clusters based on the compute nodes’ features and their topological structures. Our proposed techniques are suggested to reduce the search space concerning Network Function Virtualization, Cloud-based Networks deployment, and to build on-demand clusters to meet their requirements. In this regard, the solutions aim to help decision-makers facing issues related to scalability and computational complexities of their mechanisms to deploy their cloud-based services effectively. Experimental results demonstrate the proposed approaches’ effectiveness and suitability, given their polynomial-time complexities, making them easy to integrate into cloud providers’ orchestration systems compared to K-Means and Density-based spatial clustering of applications with noise.

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Acknowledgements

This work has been supported by Ericsson Canada and the Natural Sciences and Engineering Research Council of Canada (NSERC). The authors would like to thank Mohssine Arrouch, a Master’s student at the School of Superior Technology (ETS), University of Quebec (Canada), for providing the experimental results using DBSCAN and K-Means.

Funding

This work has been supported by Ericsson Canada and the Natural Sciences and Engineering Research Council of Canada (NSERC).

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Authors and Affiliations

  1. Department of Software Engineering and IT, École de Technologie Supérieure, University of Quebec, Montreal, Canada

    Imane El Mansoum, Laaziz Lahlou, Fawaz A. Khasawneh & Nadjia Kara

  2. Ericsson Canada, Mississauga, Canada

    Claes Edstrom

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  1. Imane El Mansoum
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  2. Laaziz Lahlou
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  3. Fawaz A. Khasawneh
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  4. Nadjia Kara
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Correspondence to Imane El Mansoum, Laaziz Lahlou, Fawaz A. Khasawneh or Nadjia Kara.

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El Mansoum, I., Lahlou, L., Khasawneh, F.A. et al. VALKYRIE: a suite of topology-aware clustering approaches for cloud-based virtual network services. J Supercomput 79, 3298–3328 (2023). https://doi.org/10.1007/s11227-022-04786-9

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