Energy Optimization in Embedded Systems: Hardware and Software Approaches

Anurag Chaturvedi

Anurag Chaturvedi Ph D Scholar, Department of Embedded Systems, Rajiv Gandhi Proudyogiki Vishwavidyalaya (RGPV), Bhopal, India

Abstract

Energy efficiency is a critical concern in the design of embedded systems, particularly for battery-operated and resource-constrained devices. As embedded systems continue to be integrated into various applications, including the Internet of Things (IoT), wearable devices, and c, optimizing power consumption has become a fundamental design objective. This review explores power-aware design strategies for energy-efficient embedded systems, discussing various hardware and software optimization techniques. Key topics include dynamic voltage and frequency scaling (DVFS), power gating, clock gating, energy-efficient scheduling, workload management, and AI-driven power optimization. Additionally, low-power communication protocols, energy harvesting techniques, and the role of machine learning in adaptive power management are examined. The review highlights recent advancements in ultra-low-power architectures, energy-efficient task scheduling, and emerging power-aware computing paradigms. Despite significant progress, challenges such as trade-offs between performance and energy efficiency, increasing hardware complexity, and security implications of power optimization techniques remain areas of active research. This study provides a comprehensive overview of power-aware strategies, identifies key research gaps, and suggests future directions for next-generation energy-efficient embedded systems.

References

1. Pedram M. Power minimization in IC design: Princi¬ples and applications. ACM Transactions on Design Automation of Electronic Systems (TODAES). 1996 Jan 1;1(1):3-56.
2. Pedram M. Logic synthesis for low power. InLow Power Design Methodologies 1996 (pp. 129-160). Boston, MA: Springer US.
3. Mittal S. A survey of techniques for improving energy efficiency in embedded computing systems. Interna¬tional Journal of Computer Aided Engineering and Technology. 2014 Jan 1;6(4):440-59.
4. Mittal S. A survey of techniques for improving energy efficiency in embedded computing systems. Interna¬tional Journal of Computer Aided Engineering and Technology. 2014 Jan 1;6(4):440-59.
5. Djelouat H, Amira A, Bensaali F. Compressive sens¬ing-based IoT applications: A review. Journal of Sensor and Actuator Networks. 2018 Oct 22;7(4):45.
6. Roy K, Mukhopadhyay S, Mahmoodi-Meimand H. Leakage current mechanisms and leakage reduction techniques in deep-submicrometer CMOS circuits. Proceedings of the IEEE. 2003 Feb;91(2):305-27.
7. Tiwari V, Malik S, Wolfe A. Power analysis of embed¬ded software: A first step towards software power minimization. IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 1994 Dec;2(4):437-45.
8. Hsu CH, Kremer U. The design, implementation, and evaluation of a compiler algorithm for CPU energy reduction. InProceedings of the ACM SIGPLAN 2003 conference on Programming language design and im¬plementation 2003 May 9 (pp. 38-48).
9. Benini L, Bogliolo A, De Micheli G. A survey of design techniques for system-level dynamic power manage¬ment. IEEE transactions on very large scale integration (VLSI) systems. 2000 Jun;8(3):299-316.
10. Min R, Bhardwaj M, Cho SH, Shih E, Sinha A, Wang A, Chandrakasan A. Low-power wireless sensor networks. InVLSI Design 2001. Fourteenth International Confer¬ence on VLSI Design 2001 Jan 7 (pp. 205-210). IEEE.
11. Huang K, Lian Y. A low-power low-VDD nonvolatile latch using spin transfer torque MRAM. IEEE transactions on nanotechnology. 2013 Aug 30;12(6):1094-103.
12. Koomey J. Growth in data center electricity use 2005 to 2010. A report by Analytical Press, completed at the re¬quest of The New York Times. 2011 Aug 1;9(2011):161.
13. Ye W, Heidemann J, Estrin D. An energy-efficient MAC protocol for wireless sensor networks. InProceedings. Twenty-first annual joint conference of the IEEE com¬puter and communications societies 2002 Jun 23 (Vol. 3, pp. 1567-1576). IEEE.