Skip to main content
Log in

Resource ratio based virtual machine placement in heterogeneous cloud data centres

  • Published:
Sādhanā Aims and scope Submit manuscript


Server consolidation through virtualization improves resource utilization significantly in Cloud Data Centres (CDCs). We study the case of a CDC hosting heterogeneous Physical Machines (PMs) as a variable size vector bin-packing problem. The PMs have different configurations of multiple resources like CPU, RAM, Disk Storage and Network Bandwidth. In this paper, we propose PMNeAR-vector heuristic for PM selection in PM-heterogeneity aware Virtual Machine (VM) initial placement. The proposed heuristic is compared with well-known heterogeneity aware FFD-DRR and BFD bin centric heuristics using a dataset with random instances of both VMs and PMs of heterogeneous configurations. Fifty rounds of VM initial placement simulation experiments were conducted to validate the average resource wastage. The results show that on average FFD-DRR and BFD bin centric heuristics are wasting 22.62% and 37.27% more resource units compared to the proposed PMNeAR-vector heuristic.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Figure 1
Figure 2
Figure 3
Figure 4


  1. Jangiti S and Sriram V S S 2018 Scalable and direct vector bin-packing heuristic based on residual resource ratios for virtual machine placement in cloud data centers. Comput. Electr. Eng.

  2. Zhang Y and Ansari N 2013 Heterogeneity aware dominant resource assistant heuristics for virtual machine consolidation. In: GLOBECOM - IEEE Glob. Telecommun. Conf., pp. 1297–1302

  3. Gabay M and Zaourar S 2016 Vector bin packing with heterogeneous bins: application to the machine reassignment problem. Ann. Oper. Res. 242(1): 161–194

    Article  MathSciNet  Google Scholar 

  4. Xu J and Fortes J A B 2010 Multi-objective virtual machine placement in virtualized data center environments. In: Proceedings - 2010 IEEE/ACM International Conference on Green Computing and Communications, GreenCom 2010, 2010 IEEE/ACM International Conference on Cyber, Physical and Social Computing, CPSCom 2010, Dresden, Germany, pp. 179–188

  5. Panigrahy R, Talwar KUyeda L and Wieder U 2011 Heuristics for Vector Bin Packing. Res. Microsoft, pp. 1–14

  6. Wang S, Liu Z, Zheng Z, Sun Q, and Yang F 2013 Particle swarm optimization for energy-aware virtual machine placement optimization in virtualized data centers. In: Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS, 2013, pp. 102–109

    Google Scholar 

  7. Gao Y, Guan H, Qi Z, Hou Y and Liu L 2013 A multi-objective ant colony system algorithm for virtual machine placement in cloud computing. J. Comput. Syst. Sci. 79(8): 1230–1242

    Article  MathSciNet  Google Scholar 

  8. Canali C and Lancellotti R 2017 Scalable and automatic virtual machines placement based on behavioral similarities. Computing 99(6): 575–595

    Article  MathSciNet  Google Scholar 

  9. Satpathy A, Addya S K, Turuk A K, Majhi B and Sahoo G 2017 Crow search based virtual machine placement strategy in cloud data centers with live migration. Comput. Electr. Eng., Dec.

  10. Jangiti S, Ram E S and Sriram V S S 2019 Aggregated Rank in First-Fit-Decreasing for Green Cloud Computing. In: Cognitive Informatics and Soft Computing, Springer, pp. 545–555

  11. Jangiti S, Sri Ram E, Ravi L and Sriram V S S 2019 Scalable hybrid and ensemble heuristics for economic virtual resource allocation in cloud and fog cyber-physical systems. J. Intell. Fuzzy Syst. 36(6): 4519–4529.

    Article  Google Scholar 

Download references


The authors thank the Department of Science and Technology for their financial support (SR/FST/ETI-349/2013) under Fund for Improvement of S&T Infrastructure in Universities and Higher Educational Institutions.

Author information

Authors and Affiliations


Corresponding author

Correspondence to V S Shankar Sriram.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jangiti, S., E, S., Jayaraman, R. et al. Resource ratio based virtual machine placement in heterogeneous cloud data centres. Sādhanā 44, 236 (2019).

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: