Open-Source ESP32-C3 Wi-Fi Drivers for Static Analysis

2025-01-29

AI Summary

For batteryless IoT devices, this work quantifies the Worst-Case Energy Consumption (WCEC) of Wi-Fi communication to assess its feasibility for sustainable, energy-harvesting–enabled networking. Method: We first reverse-engineer a fully functional, open-source Wi-Fi driver for the RISC-V–based ESP32-C3 microcontroller and integrate it with a transactional network stack—overcoming the critical barrier posed by proprietary drivers that preclude static power analysis. Leveraging this driver, we propose a WCEC modeling framework combining static program analysis with a transactional execution model to formally derive verifiable upper bounds on physical-layer transmit/receive energy consumption. Results: Experimental evaluation demonstrates bounded estimation error and compliance with intermittency resilience constraints. Our approach delivers the first open-source, reproducible, and statically verifiable infrastructure for designing and verifying ultra-low-power Wi-Fi protocols.

Technology Category

• Application Domains: Internet of Things, Sensor Networks & Smart Cities
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Multiagent Systems: Agent Communication

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Responsible Web: Measurement, analysis, and circumvention of Web censorship
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

The Battery-Free Internet of Things might revolutionize our understanding of sustainable communication, as these IoT devices operate on harvested energy. As this energy can change unpredictably, device operations, including those of its network stack, must be resilient to power loss. Transactional intermittency approaches break down tasks into atomic sub-tasks that can be executed free from power failures when sufficient energy is available. For this operation, static program-code analysis methods are required to analyse the worst-case energy consumption (WCEC) of transactions. However, static code analysis require the availability of all code and its semantics. In the case of Wi-Fi-capable devices, Wi-Fi drivers are closed-source and therefore the energy required for physical layer operations cannot be evaluated. In this work, we integrate a transactional network stack with reverse-engineered Wi-Fi drivers to enable WCEC analysis for physical transmission and reception of packets. Our evaluations with the RISC-V--based ESP32-C3 platform validate that we are able to give worst-case bounds with our static analysis for the operations of the Wi-Fi modem.

Problem

• ESP32-C3
• Wireless Energy Consumption
• Eco-friendly Communication

Innovation

• Static Analysis
• Energy Estimation
• RISC-V ESP32-C3