Abstract:
Data Centre (DC) administrators try to
delivering performance guarantees while
managing resources for utilization in terms of
reducing cost. With the advent of server
consolidation provided by virtualization
technology, multiple heterogeneous virtual
machines (VMs) can be coexisted on a physical
server and shared resources together. Fixed
allocation of resources to VMs is not the optimal
allocation method as over provisioning and
under provisioning can be caused. For dynamic
allocation, simultaneous on demand provisioning
of shared physical resources to VMs becomes the
key challenge.
This paper proposes resource usage
prediction system by making analysis on the
accuracy of three different models; Fuzzy
modeling, adaptive Fuzzy modeling and NeuroFuzzy modeling. To evaluate the efficiency of
three different models, experiments are carried
out by workload-resource mapping and
resource-resource mapping approaches. CPU
profiles from real world data centre are used to
analyze through a simulating program.
Experimental results show that the proposed
resource prediction models can predict well next
time interval resource usage of virtual machine
even in the condition of unexpected high spikes
CPU.
