Power-Aware Design Strategies for Energy-Efficient Embedded Systems: A Comprehensive Review
Abstract
With the increasing demand for battery-operated and energy-efficient computing systems, power-aware design has become a crucial aspect of embedded system development. Embedded systems are widely used in various domains, including Internet of Things (IoT), healthcare, automotive, industrial automation, and consumer electronics. However, their limited power budgets and stringent performance requirements necessitate the adoption of energy-efficient design methodologies. This review explores various power-aware design strategies that contribute to optimizing energy consumption without compromising system performance and reliability.
The article categorizes power-saving techniques into hardware optimizations, software-based approaches, and architectural innovations. Key hardware-based strategies include dynamic voltage and frequency scaling (DVFS), which adjusts processor power dynamically based on workload; power gating, which selectively turns off idle hardware blocks to minimize leakage power; and energy-efficient memory management, which focuses on reducing power consumption in caches and storage elements. Additionally, emerging low-power circuit design techniques, such as advanced CMOS technologies and near-threshold computing, are examined for their impact on energy-efficient embedded architectures.
On the software side, we analyze compiler-assisted power optimizations, real-time operating system (RTOS) power management policies, and power-aware task scheduling techniques. These methods enable better resource allocation, reduce unnecessary processing, and optimize code execution for energy efficiency. Furthermore, recent advances in machine learning-based power optimization methods are discussed, highlighting how predictive analytics and AI-driven models enhance power management in embedded platforms.
Beyond individual techniques, the review also examines system-level approaches, such as energy-aware network protocols for IoT, edge computing for reduced cloud dependency, and renewable energy integration for sustainable embedded systems. The role of energy-efficient embedded system applications is analyzed across different industries, with case studies on automotive systems, healthcare monitoring devices, smart manufacturing, and wireless sensor networks (WSNs).
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