Open Access


An Efficient Framework for Utilizing Underloaded Servers in Compute Cloud

M. Hema1,*, S. Kanaga Suba Raja2
1 Department of Information Technology, Easwari Engineering College, Chennai, 600089, India
2 Department of Computer Science and Engineering, Easwari Engineering College, Chennai, 600089, India
* Corresponding Author: M. Hema. Email:

Computer Systems Science and Engineering 2023, 44(1), 143-156.

Received 03 November 2021; Accepted 10 December 2021; Issue published 01 June 2022


In cloud data centers, the consolidation of workload is one of the phases during which the available hosts are allocated tasks. This phenomenon ensures that the least possible number of hosts is used without compromise in meeting the Service Level Agreement (SLA). To consolidate the workloads, the hosts are segregated into three categories: normal hosts, under-loaded hosts, and overloaded hosts based on their utilization. It is to be noted that the identification of an extensively used host or underloaded host is challenging to accomplish. Threshold values were proposed in the literature to detect this scenario. The current study aims to improve the existing methods that choose the underloaded hosts, get rid of Virtual Machines (VMs) from them, and finally place them in some other hosts. The researcher proposes a Host Resource Utilization Aware (HRUAA) Algorithm to detect those underloaded and place its virtual machines on different hosts in a vibrant Cloud environment. The mechanism presented in this study is contrasted with existing mechanisms empirically. The results attained from the study establish that numerous hosts can be shut down, while at the same time, the user's workload requirement can also be met. The proposed method is energy-efficient in workload consolidation, saves cost and time, and leverages active hosts.


Workload consolidation; energy consumption; under load server; resource utilization

Cite This Article

M. Hema and S. Kanaga Suba Raja, "An efficient framework for utilizing underloaded servers in compute cloud," Computer Systems Science and Engineering, vol. 44, no.1, pp. 143–156, 2023.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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