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A comparative review of meta-heuristic approaches to optimize the SLA violation costs for dynamic execution of cloud services

  • Ajay KumarEmail author
  • Seema Bawa
Methodologies and Application

Abstract

This paper presents comparative analysis results of research work done using the five most popular meta-heuristic techniques to optimize the service-level agreement (SLA) violation cost in cloud computing. The meta-heuristic algorithms have the ability to handle multifarious types of constraints and offer better results. The Quality of Service criteria, SLA penalty cost and the cloud-domain-specific constraints have been mathematically formulated in this paper. The sole motivation of this paper is that the constraints of feasible domain must be satisfied and the profit of cloud service provider should be maximized. An effort has been made to experimentally demonstrate the comparative performance of five meta-heuristic algorithms, namely Ant Colony Optimization, Particle Swarm Optimization, Genetic Algorithm, Gray Wolf Optimizer and Harmony Search. Eleven test benchmark functions have been applied to demonstrate the efficiency and performance. The best solutions of each meta-heuristic technique have been reported in four performance metric cases: worst, best, average and standard deviation.

Keywords

Cloud computing Service-level agreement Meta-heuristic algorithms Resource optimization 

Notes

Compliance with ethical standards

Conflicts of interest

We have no conflicts of interest to disclose.

Human and animal rights

This article does not contain any studies with human participants or animals performed by any of the authors.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Computer Science and Engineering DepartmentThapar Institute of Engineering and TechnologyPatialaIndia

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