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QoS-Aware Service Migration in Multi-access Edge Compute Using Closed-Loop Adaptive Particle Swarm Optimization Algorithm

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Abstract

In the 5G network, hosting services in multi-access edge compute (MEC) infrastructure is a crucial enabler to achieving the high bandwidth and low latency targets for various applications. When MEC infrastructure gets overloaded, service migrations are performed to meet the users’ service level agreement (SLA) requirements. Performing service migration in MEC without impacting user experience is a challenge because of the geographically distributed infrastructure, heterogeneous applications and varying SLA from users. Many existing studies are focused either on system resource utilisation or the user’s geographic location to decide when to trigger service migrations in MEC. However, they seldom consider users’ quality of service (QoS) needs or application characteristics while performing service migrations. This paper proposes a novel method to proactively perform service migrations in MEC, considering the system resource utilisation, application characteristics and the QoS experienced by the user. We have developed a closed loop adaptive particle swarm optimisation (CLA-PSO) algorithm, inspired by particle swarm optimisation (PSO) method, to trigger service migrations in MEC. Our study showed that the SLA violations are minimised significantly by performing an application-aware service migration using CLA-PSO, compared to migrating services based on resource utilisation. The proposed CLA-PSO algorithm performs much better when compared to the standard PSO and the state-of-the-art three-parameter smoothing exponentially weighted moving average (EWMA3) algorithms.

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Acknowledgements

We thank the School of Computing Sciences and Department of Research at Hindustan Institute of Technology and Science for their support.

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We wish to confirm that the authors did not receive any financial support or Grants from any organization for the submitted work.

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Authors and Affiliations

  1. Department of Computer Science Engineering, Hindustan Institute of Technology and Science, Chennai, India

    Saravanan Velrajan

  2. Department of Information Technology, Hindustan Institute of Technology and Science, Chennai, India

    V. Ceronmani Sharmila

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  1. Saravanan Velrajan
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  2. V. Ceronmani Sharmila
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Contributions

SV conceived of the presented idea, developed the theory, validated the theory in the lab, performed the computations and created the final manuscript. VCH provided guidance for the research, verified the analytical methods, supervised the findings of this work and reviewed the final manuscript.

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Correspondence to Saravanan Velrajan.

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Velrajan, S., Ceronmani Sharmila, V. QoS-Aware Service Migration in Multi-access Edge Compute Using Closed-Loop Adaptive Particle Swarm Optimization Algorithm. J Netw Syst Manage 31, 17 (2023). https://doi.org/10.1007/s10922-022-09707-y

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