MFF: Performance Interference-Aware VM Placement Algorithm for Reducing Energy Consumption in Data Centers
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Date
2020
Authors
Journal Title
Journal ISSN
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Publisher
Open Journal for Information Technology
Abstract
Virtualization is the main technology that powers cloud computing and has enabled the execution
of multiple applications in same physical hardware using virtual machines (VM) for efficient
utilization of resources and energy savings. Although virtualization successfully isolates coresident
VMs from a security perspective, it does not offer a guarantee from a performance
interference perspective. This means that sharing of resources results in competition, which is
the cause of performance interference. Performance interference is more pronounced in
homogenous workloads, where applications workloads contend to the same shared resource. In
this case, application workloads run for longer times due to reduced performance and thus
consume more energy. To address this problem, a VM allocation policy should ensure that VM
running homogeneous workloads is not co-located. In this paper, we propose a VM allocation
algorithm called Minimum Interference First Fit (MFF), which co-locates dissimilar workloads.
The algorithm clusters VMs using K-means based on resources usage. Before a VM is placed into
a physical machine (PM), similarity index (SI) of all the active PMs is computed, the VM is then
placed in a PM with least SI. MFF has been evaluated on a simulated data center using CloudSim
Plus cloud simulator on application workloads logs obtained from a production data center.
Results show that MFF outperforms well-known VM allocations algorithms such as first fit (FF),
worst fit (WF) and best fit (BF) from an energy consumption perspective.
Description
Keywords
Cloud computing, k-means, Virtualization, Data center energy consumption, Performance interference
Citation
Mosoti, D., Omwenga, V. O., & Ogao, P. (2020). Mff: Performance interference-aware vm placement algorithm for reducing energy consumption in data centers. Open Journal for Information Technology, 3(1), 1. https://doi.org/10.32591/coas.ojit.0301.01001m