Correlation-aware virtual machine allocation for energy-efficient datacenters
Proceedings of the Conference on Design, Automation and Test in Europe
ACM Transactions on Embedded Computing Systems (TECS)
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The negative effects of the Dynamic Voltage and Frequency Scaling (DVFS) technique on the system reliability has recently promoted the research on reliability-aware power management (RAPM). RAPM aims at reducing the system energy consumption while preserving the system's reliability. In this paper, we study the RAPM problem for parallel realtime applications for shared memory multiprocessor systems in the presence of precedence constraints. We show that this problem is NP-hard. Depending on how recoveries are scheduled and utilized by a subset of selected tasks, we investigate both individual-recovery and shared-recovery based RAPM heuristics. Online RAPM schemes that exploit dynamic slack generated at runtime are also considered. The proposed schemes are evaluated through extensive simulations. The results show that all schemes can preserve system reliability under all settings. For modest system loads, similar energy savings are obtained by all static schemes. However, when the system load is low, the shared-recovery based schemes need coordinated recovery operations on all processors and thus save less energy. Moreover, by reclaiming dynamic slack, the online schemes yield better energy savings.