Bio-Inspired Heuristics for VM Consolidation in Cloud Data Centers
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Detail(s)
Original language | English |
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Article number | 8665989 |
Pages (from-to) | 152-163 |
Journal / Publication | IEEE Systems Journal |
Volume | 14 |
Issue number | 1 |
Online published | 12 Mar 2019 |
Publication status | Published - Mar 2020 |
Externally published | Yes |
Link(s)
Abstract
In
infrastructure-as-a-service environments, Cloud data centers employ
virtualization technology to host various applications in virtual
machines (VMs) and enable application isolation on shared physical
resources. Additionally, live VM migration has been adopted to perform
load balancing by moving VMs across distinct hosts. However, co-located
VMs that show significant positive correlations on their CPU utilization
patterns are at a higher risk of triggering overloading events and
incurring performance degradation, even when their host is operating
below its critical limits. To address this problem, a VM consolidation
mechanism inspired by host-switching behaviors in symbiotic associates
is proposed in this paper. In the proposed mechanism, hosts and VMs in
Cloud data centers represent symbionts in an ecosystem. Two heuristic
functions, inspired by host susceptibility and symbiotic coefficient
among symbionts, are proposed to yield better resource utilization via
VM consolidations. Experiment results demonstrate that the proposed
mechanism can achieve reductions in both energy consumption and service
level agreement violations of Cloud data centers.
Research Area(s)
- Bio-inspired, heuristics, resource management, utilization correlation, virtual machine (VM) consolidation
Citation Format(s)
Bio-Inspired Heuristics for VM Consolidation in Cloud Data Centers. / Jing V. Wang; Nuwan Ganganath; Chi-Tsun Cheng et al.
In: IEEE Systems Journal, Vol. 14, No. 1, 8665989, 03.2020, p. 152-163.
In: IEEE Systems Journal, Vol. 14, No. 1, 8665989, 03.2020, p. 152-163.
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review