Dynamic Threshold Based Load Balancing and Server Consolidation in Cloud

Authors

  • Geetha Megharaj Computer Science and Engineering, Sri Krishna Institute of Technology, Bangalore, India
  • Mohan G Kabadi Computer Science and Engineering, Presidency University, Bangalore, India

Keywords:

VM Migration, Load Balancing, Server consolidation, Dynamic Threshold

Abstract

High power consumption in Cloud Data center leads to high emissions of carbon which is unsuitable for environment. Energy consumption in the data center can be reduced by balancing load among active physical nodes and minimizing the number of active servers which are lightly loaded. Static lower and upper thresholds are not suitable for dynamically changing resource usage of physical machines. Dynamic Threshold based load balancing algorithms are proposed: i)Upper threshold dynamically varied based on CPU utilization and the Lower Threshold is predefined. ii) The average utilization of all the machines in the datacenter is used to define Upper Threshold. System is monitored at regular intervals and whenever server load goes above the Upper Threshold or lower than Lower Threshold, system identified as in imbalance state and Virtual Machine migration is initiated for load balance and for server consolidation. Simulation results shows the proposed schemes can improve resource utilization and energy.

References

[1] Datacenter Dynamics 2012, Global Census.

[2] H. Jin et al., “Live virtual machine migration with adaptive memory compression”, Proceeding of the IEEE international conference on cluster computing, pp. 1-10, 2012.

[2] H. Jin et al., “Live migration of virtual machine based on full system trace and replay”, Proceeding of the 18th ACM 2009.

[3] R. Nathuji and K. Schwan, “Virtual power: Coordinated power management in virtualized enterprise systems”, Proceeding of the ACM SIGOPS Symp. on Op.Sys. Principles, ACM press, pp.265-278, Dec. 2007.

[4] A. Beloglazov, J. Abawajy, and R. Buyya, “Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing”, Future Generation Computer Systems, pp.755- 768, May. 2012.

[5] A. Beloglazov and R.Buyya. "Adaptive threshold-based approach for energy-efficient consolidation of virtual machines in cloud data centers”, Proceedings of the 8th international workshop on middleware for grids, clouds and e-science ACM, pp. 4, 2010.

[6] A. Beloglazov and R. Buyya, “Optimal Online Deterministic Algorithms and Adaptive Heuristics for Energy and Performance Efficient Dynamic Consolidation of Virtual Machines in Cloud Data Centers”, Concurrency and Computation: Practice and Experience(CCPE), Wiley Press, New York, USA, vol. 24, no. 13, pp. 1397-1420, Sep. 2012

[7] Amir Varasteh and Maziar Goudarzi, ”Server Consolidation Techniques in Virtualized Data Centers: A Survey”, IEEE Systems, VOL. 11, NO. 2, June 2017.

[8] C.C. Lin, P.Liu and J.J Wu, ”Energy-efficient Virtual Machine provision Algorithms for cloud systems”, Utility and Cloud Computing (UCC), 2011 Fourth IEEE International Conference, 2011,81-88.

[10] Shingo Takeda and Toshinori Takemura, ”A Rank based VM Consolidation Method for Power Saving in Datacenters”, IPSJ Online Transactions 3(2):88-96, January 2010.

[11] Liting Hu, Hai Jin, Xianjie Xiong and Haikun Liu, ”Magnet: A novel scheduling policy for power reduction in cluster with virtual machines”, 2008 IEEE International Conference on Cluster Computing, 13-22.

[12] Geetha Megharaj, Mohan G. Kabadi, “Server Consolidation through Virtual Machine Task Migration to achieve Green Cloud”, International Journal of Computer Science and Information Security (IJCSIS), Vol. 16, No. 3, March 2018.

[13] A Jain et al., “A Threshold Band Based Model for Automatic Load Balancing in Cloud Environment”, in proc. of IEEE International Conference on Cloud Computing in Emerging Markets, pp 1-7, 2013.

[14] J. M. Galloway, K. L. Smith, and S. S. Vrbsky, “Power aware load balancing for cloud computing”, Proc. the World Congress on Engineering and Computer Science, 2011, 19-21.

[15] Shivani Gupta, Damodar Tiwari, Shailendra Singh, “Energy Efficient Dynamic Threshold Based Load Balancing Technique in Cloud Computing Environment”, International Journal of Computer Science and Information Technologies, Vol. 6 (2) , 2015, 1023-1026

[16] R. N. Calheiros, R. Buyya, and A. Beloglazov, “CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms”, Software: Practice and Experience, Wiley Press, pp.23-50, Jan. 2011.

Downloads

Published

2025-11-25

How to Cite

[1]
G. Megharaj and M. G. Kabadi, “Dynamic Threshold Based Load Balancing and Server Consolidation in Cloud”, Int. J. Comp. Sci. Eng., vol. 7, no. 16, pp. 117–121, Nov. 2025.

Issue

Vol. 7 No. 16 (2019): IJCSE Special Issue May Edition

Section

Survey Article

License

Creative Commons License

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

Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.