@inproceedings{88864e811cfb4097b73ba16dba682be9,
title = "Effects of Correlation-based VM Allocation Criteria to Cloud Data Centers",
abstract = "Virtualization technology has been widely adopted in Cloud data centers for adaptive resource provisioning. With virtualization, multiple virtual machines (VMs) can be colocated on a single physical host to yield maximum efficiency. However, VMs which show high CPU utilization correlations to other co-located peers are more likely to trigger overloading incidents. This work provides an analysis on effects of correlation-based VM allocation criteria to Cloud data centers. The correlations among VMs' CPU utilizations are considered as parameters for decision making in VM allocation processes. Three different expressions of correlation-based criteria are introduced and evaluated in this work. According to our simulation results obtained from CloudSim with real-world workload traces, Cloud data centers with correlation-based allocation criteria can perform better in terms of reducing energy consumption and avoid committing Service Level Agreements violations than those with power-based criteria.",
keywords = "Cloud computing, Correlation, CPU utilization, Resource provisioning, VM allocation",
author = "Wang, \{Jing V.\} and Chi-Tsun Cheng and Tse, \{Chi K.\}",
year = "2016",
month = oct,
doi = "10.1109/CyberC.2016.83",
language = "English",
series = "Proceedings - 2016 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2016",
publisher = "IEEE",
pages = "398--401",
booktitle = "Proceedings - 2016 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC 2016)",
address = "United States",
note = "8th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2016 ; Conference date: 13-10-2016 Through 15-10-2016",
}