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2013 IEEE Eighth International Conference on Networking, Architecture and Storage (2013)
Xi'an, Shaanxi, China China
July 17, 2013 to July 19, 2013
pp: 105-114
This paper presents a novel Predictive Energy-Aware Management (PEAM) system that is able to reduce the energy costs of storage systems by appropriately selecting data transmission methods. In particular, we evaluate the energy costs of three methods (1. transfer data without archiving and compression, 2. archive and transfer data, 3. compress and transfer data) in preliminary experiments. According to the results, we observe that the energy consumption of data transmission greatly varies case by case. We cannot simply apply one method in all cases. Therefore, we design an energy prediction model that can estimate the total energy cost of data transmission by using particular transmission methods. Based on the model, our predictive energy-aware management system can automatically select the most energy efficient method for data transmission. Our experimental results show that our system performs better than simply selecting any one among the three methods for data transmission in terms of energy efficiency.
Predictive models, Thermal management, Temperature distribution, Energy consumption, Data communication, Servers, Energy storage

X. Jiang, J. Zhang, M. I. Alghamdi, X. Qin, M. Jiang and J. Zhang, "PEAM: Predictive Energy-Aware Management for Storage Systems," 2013 IEEE 8th International Conference on Networking, Architecture, and Storage (NAS), Xi'an, Shaanxi, China, 2013, pp. 105-114.
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