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energy_aware/abstract.tex
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Cloud computing has gained popularity in recent years delivering | |
various services as cost-effective platforms. However, the increasing | |
energy consumption needs to be addressed in order to preserve the | |
cost-effectiveness of these systems. In this work, we target the | |
storage infrastructure in a cloud system and introduce several energy | |
efficient storage node allocation methods by exploiting the metadata | |
heterogeneity of cloud users. Our proposed methods preserve load balance | |
on demand and switch inactive nodes into low-energy modes to save energy. | |
We provide a mathematical model to estimate the outcome of proposed methods | |
and conduct theoretical and simulative analyses using real-world workloads. |