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heuristic algorithms for cloud server consolidation.
Our main concerns are power consumption and SLA
violation. We designed and deployed an architecture
using cloud-based R servers as the decision support
system. Forecast models were built for each VM, and
predictions made as to their future CPU resource re-
quirements. The simulation-based experiments anal-
ysed the proposed algorithms with respect to their
consistency, robustness, and performance. The re-
sults demonstrate that the proposed approach, com-
pared with other heuristics, can significantly reduce
power consumption, the number of VM migrations,
and number of SLA violations. The analytical model
has not taken load-balancing into consideration, and
this will be addressed in future work.
ACKNOWLEDGEMENTS
This work is supported by the Telecommunications
Graduate Initiative (TGI) program which is funded by
the Higher Education Authority under the Programme
for Research in Third-Level Institutions (PTRLI) Cy-
cle 5 and co-founded under the European Regional
Development Fund (ERDF).
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