Load Predicting Model of Mobile Cloud Computing Based on Glowworm Swarm Optimization LSTM Network

Authors

  • P. Sudhakaran Department of Computer Science, SRM TRP Engineering College, Trichy, India
  • Subbiah Swaminathan Department of Computer of Science and Engineering, Saveetha School of Engineering, Saveetha Institute of medical and Technical Sciences, Chennai, India
  • D. Yuvaraj Department computer of Science, Cihan university-Duhok, Kurdistan region, Iraq
  • S.Shanmuga Priya Department of Computer Science, M.I.E.T Engineering College, Trichy, India

DOI:

https://doi.org/10.3991/ijim.v14i05.13361

Keywords:

Mobile cloud, LSTM Network, Glowworm Swarm Optimization Algorithm, Load Forecasting.

Abstract


Focusing on the issue of host load estimating in mobile cloud computing, the Long Short Term Memory networks (LSTM)is introduced, which is appropriate for the intricate and long-term arrangement information of the cloud condition and a heap determining calculation dependent on Glowworm Swarm Optimization LSTM neural system is proposed. Specifically, we build a mobile cloud load forecasting model using LSTM neural network, and the Glowworm Swarm Optimization Algorithm (GSO) is used to search for the optimal LSTM parameters based on the research and analysis of host load data in the mobile cloud computing data center. Finally, the simulation experiments are implemented and similar prediction algorithms are compared. The experimental results show that the prediction algorithms proposed in this paper are in prediction accuracy higher than equivalent prediction algorithms.

Author Biographies

P. Sudhakaran, Department of Computer Science, SRM TRP Engineering College, Trichy, India

Department of Computer Science, SRM TRP Engineering College

Subbiah Swaminathan, Department of Computer of Science and Engineering, Saveetha School of Engineering, Saveetha Institute of medical and Technical Sciences, Chennai, India

Department of Computer of Science and Engineering, Saveetha School of Engineering, Saveetha Institute of medical and Technical Sciences

D. Yuvaraj, Department computer of Science, Cihan university-Duhok, Kurdistan region, Iraq

Department computer of Science, Cihan university-Duhok

S.Shanmuga Priya, Department of Computer Science, M.I.E.T Engineering College, Trichy, India

Department of Computer Science, M.I.E.T Engineering College

Downloads

Published

2020-04-07

How to Cite

Sudhakaran, P., Swaminathan, S., Yuvaraj, D., & Priya, S. (2020). Load Predicting Model of Mobile Cloud Computing Based on Glowworm Swarm Optimization LSTM Network. International Journal of Interactive Mobile Technologies (iJIM), 14(05), pp. 150–163. https://doi.org/10.3991/ijim.v14i05.13361

Issue

Vol. 14 No. 05 (2020)

Section

Papers

License

The submitting author warrants that the submission is original and that she/he is the author of the submission together with the named co-authors; to the extend the submission incorporates text passages, figures, data or other material from the work of others, the submitting author has obtained any necessary permission.
Articles in this journal are published under the Creative Commons Attribution Licence (CC-BY What does this mean?). This is to get more legal certainty about what readers can do with published articles, and thus a wider dissemination and archiving, which in turn makes publishing with this journal more valuable for you, the authors.
By submitting an article the author grants to this journal the non-exclusive right to publish it. The author retains the copyright and the publishing rights for his article without any restrictions.
This journal has been awarded the SPARC Europe Seal for Open Access Journals (What's this?)