A Recursive Ant Colony Optimization Algorithm for Energy Consumption in Cloud Computing

Authors

  • Usha Kirana Sonangeri Pushpavathi Department of Computer Science and Engineering, Canara College of Engineering, Visvesvaraya Technological University, Mangaluru, India
  • Demian Antony D’Mello Department of Computer Science and Engineering, Canara College of Engineering, Visvesvaraya Technological University, Mangaluru, India

DOI:

https://doi.org/10.48048/tis.2022.4502

Keywords:

Ant colony optimization, Cloud computing, Cloud Sim, Energy consumption, Service level agreements, Virtual machines

Abstract

The Cloud Computing (CC) has vast amount of data centers that consists of many computing nodes and consumes a huge amount of electrical energy. Hence the researchers found that the high service-level agreements (SLAs) violations and Energy Consumption (EC) are the major challenging issues in CC. The various traditional approaches reduced the EC, but ignored the SLA violation during the selection of Virtual Machine (VM) from overloaded hosts. In order to effectively deal with these issues, this paper proposed the Recursive Ant Colony Optimization (RACO) in 2 different workloads. The main aim of the RACO is to minimize the high EC and SLA violations by the movement of best ant, which is random and identified the distance between their movements. The algorithm consists of 3 major steps includes tracking and updating the pheromone and finally city selection. The proposed method simulated on Cloud Sim to validate the efficiency and stability of the proposed RACO and their performance compared to that of other existing techniques. The results showed that RACO reduced the EC by 40 - 42 % (approx.) which is less than the traditional ACO algorithm in Planet Lab data.

HIGHLIGHTS

  • Reduced EC and SLA Violation of Data Center are done via RACO
  • VM Allocations are done by IQR and utilises micro, small, medium and extra-large instances
  • Pheromone Tracking, updating and city selection are the endeavours of RACO
  • RACO reduced EC by 40 - 42 % and SLA Violation

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Published

2022-05-31

Issue

Vol. 19 No. 11 (2022): Trends in Sciences, Volume 19, Number 11, 1 June 2022

Section

Research Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.