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.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2016 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2016 |
| Publisher | IEEE |
| Pages | 398-401 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781509051540 |
| DOIs | |
| Publication status | Published - 23 Feb 2017 |
| Event | 8th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2016 - Ascott Raffles City, Chengdu, China Duration: 13 Oct 2016 → 15 Oct 2016 |
Conference
| Conference | 8th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2016 |
|---|---|
| Country/Territory | China |
| City | Chengdu |
| Period | 13/10/16 → 15/10/16 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Cloud computing
- Correlation
- CPU utilization
- Resource provisioning
- VM allocation
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Safety, Risk, Reliability and Quality
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