Architectural Evolution and Performance Optimization in Embedded Systems: A Comparative Analysis of ESP8266, ESP32-S3, and ESP32-C6 Platforms
Keywords:
Embedded System Architecture, ESP Series Microcontrollers, Internet of Things (IoT), Performance Optimization, Power Management, ConnectivityAbstract
The rapid proliferation of Internet of Things (IoT) applications has placed increasing demands on embedded system architectures, particularly in terms of connectivity, power efficiency, and computational capability. This paper presents a systematic analysis of the evolution and performance optimization of embedded development architectures centered on the ESP8266, ESP32-S3, and ESP32-C6 microcontroller series. We trace the architectural trajectory from the foundational Wi-Fi capabilities of the ESP8266 to the enhanced AI and dual-core processing of the ESP32-S3, and further to the multi-protocol (Wi-Fi 6 and Bluetooth 5.0) and low-power innovations of the ESP32-C6. The study conducts a comparative performance evaluation across these platforms, focusing on critical metrics such as power consumption, data throughput, and real-time task execution efficiency. Furthermore, we propose and validate a suite of software-level optimization strategies, including tailored power management algorithms, hybrid task scheduling models, and memory allocation schemes, designed to maximize the potential of each hardware iteration. The experimental results demonstrate that the evolutionary path of the ESP series reflects a strategic optimization trade-off between connectivity, performance, and energy autonomy. This work provides a structured framework for developers to select and optimize the appropriate ESP-based architecture, thereby accelerating the development of next-generation, resource-constrained IoT devices.
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Copyright (c) 2025 Pengyu Yan
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