Energy Efficiency in Large Scale Distributed Systems: COST by Mohammed El Mehdi Diouri, Manuel F. Dolz, Olivier Glück,

By Mohammed El Mehdi Diouri, Manuel F. Dolz, Olivier Glück, Laurent Lefèvre, Pedro Alonso (auth.), Jean-Marc Pierson, Georges Da Costa, Lars Dittmann (eds.)

This e-book constitutes revised chosen papers from the convention on power potency in huge Scale allotted structures, EE-LSDS, held in Vienna, Austria, in April 2013. It served because the ultimate occasion of the fee motion IC0804 which begun in may possibly 2009. The 15 complete papers awarded during this quantity have been rigorously reviewed and chosen from 31 contributions. additionally, 7 brief papers and three demo papers are incorporated during this ebook. The papers are prepared in sections named: modeling and tracking of energy intake; dispensed, cellular and cloud computing; HPC computing; stressed and instant networking; and standardization issues.

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Mob. Comput. 6(12), 1398–1409 (2007) 27. : Comparative analysis of energy-saving techniques in 3g pp and 3gpp 2 systems. IEEE Trans. Veh. Technol. nz Abstract. Many techniques have previously been proposed for using low-level CPU Performance Monitoring Counters in power estimation models. In this paper, we present some common myths of these techniques, and their potential impact. Such myths include: (1) sampling rate can be ignored; (2) thermal effects are neutral; and (3) memory events correlate well with power.

The most likely cause for the warmup effects is static power leakage from the processor, which is due to the high temperatures. 6GHz. It might seem that the only way to reliably monitor thermal effects is through embedded temperature sensors. However, since their placement inside the socket is some distance away from the top of CPU, embedded sensors do not provide reliable temperature data [3]. Also such sensors were not designed for high precision temperature reading, as their purpose is to provide an early warning system to prevent hardware damage.

ACM (2002) 11. : Avoiding the rush hours: Wifi energy management via traffic isolation. IEEE Trans. Mob. Comput. 11(5), 739–752 (2012) 12. : Simulation inspired model for energy consumption in 3g always-on mobiles. In: IEEE 2nd National Conference on Telecommunications (CONATEL 2011), pp. 1–7 (2011) 13. : fine grained energy accounting on smartphones with eprof. In: Proceedings of the 7th ACM European Conference on Computer Systems, EuroSys ’12, pp. 29–42 (2012) 14. : Understanding traffic dynamics in cellular data networks.

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