Abstract
Embedded systems are identified by the processors, on which application-oriented programs have to run. Most of the actions on the processor are controlled and coordinated by the software, and also, it has a fundamental role in the system design. In this paper, we are estimating and optimizing the energy consumed by the processor with the Lagrange principle, by considering the task and energy consumed by the particular task for a particular time instant by the core in Ubuntu as well as in arm development studio-5. This helps to improve the performance of the processors dynamically in the future generations. Now they are widely used in hand-held devices and many other portable consumer gadgets. The ARM processors provide tremendous achievement with less power consumption and compact size performance analysis.
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References
Burd TD et al (2000) A dynamic voltage scaled microprocessor system. IEEE J Solid-State Circ 35:1571–1580
Konstantakos V, Chatzigeorgiou A, Nikolaidis S, Laopoulos T (2008) Energy consumption estimation in embedded systems. IEEE Trans Instrum Meas 57:747–794
Lee S, Ermedahl A, Min SL (2001) An accurate level energy consumption model for embedded processor. In: Proceedings of 5th ACM SIGPLAN workshop LCTES, Aug 2001
Devi UC, Anderson J (2005) Tardiness bounds for global edf scheduling on a multiprocessor. In: IEEERTSS
Hsu H-R, Chen J-J, Kuo T-W (2006) Multiprocessor synthesis for periodic hard real-time tasks under a given energy constraint. In: ACM/IEEE conference of design, automation, and test in Europe (DATE), pp 1061–1066
Kavvadias N, Neofotistos P, Nikolaidis S, Kosmatopoulos K (2004) Measurement analysis of the software related power consumption, Aug 2004
Tiwari V, Malik S, Wolfie A (1994) Power analysis of embedded software: a first step forward software minimization. In: IEEE transaction on VLSI systems, vol 2, no 4, pp 437–445, Dec 1994
AT91SAM7X256 Data Sheet, Atmel, 2009
Lee M, Tiwari V, Malik S, Fujita M (1997) Power analysis and minimization techniques for embedded DSP software. IEEE Trans VLSI Syst 5(1):123–135
Russell JT, Jacome MF (1998) Software power estimation and optimization for high performance, 32-bit embedded processors. In: Proceedings of ICCD: VLSI computers and processors, Oct 1998, pp 328–333
Vazirani VV (2001) Approximation algorithms. Springer
Konstantakos V, Chatzigeorgiou A, Nikolaidis S, Laopoulos T (2006) Energy consumption estimation in embedded systems. In: Proceeding of IEEE IMTC, Apr 2006, pp 235–238
Konstantotos V, Laopoulos T (2008) Energy consumption estimation of the embedded systems. IEEE Transac Instrum Electr Meas Syst 57(3)
Acknowledgements
Authors would like to thank the anonymous reviewers for their comments in improving the paper and also, we extend our gratitude to VIT University, Chennai, for their support.
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Ram, A., Murugan, M.S.B. (2018). Energy Estimation of Embedded Systems. In: Thalmann, D., Subhashini, N., Mohanaprasad, K., Murugan, M. (eds) Intelligent Embedded Systems. Lecture Notes in Electrical Engineering, vol 492. Springer, Singapore. https://doi.org/10.1007/978-981-10-8575-8_27
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DOI: https://doi.org/10.1007/978-981-10-8575-8_27
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