Managing energy consumption in FPGA-based edge computing systems with soft-core CPUs

Edge computing, characterized by processing data closer to its source, has emerged as a promising paradigm to address the challenges of latency, bandwidth, and privacy in the Internet of Things (IoT) era. At the same time, Field-ProgrammableGate Arrays (FPGAs) have gained significant attention in edge computing due to their ability to reconfigure design, low power consumption, and high performance. However, the energy consumption of FPGA-based edge computing systems remains a critical concern, particularly in resource-constrained environments where power efficiency is crucial. This paper presents an energy-efficient edge computing system focusing on job scheduling and power management optimization. We review existing techniques and methodologies for optimizing energy consumption in computing systems, including FPGA-based edge devices, identify key challenges and opportunities for future enhancement and propose a flexible, low-power system design with soft-core CPUs.