Abstract

The growth of resource-constrained and latency-sensitive devices in advanced wireless networks necessitates incorporating energy efficiency into their design. This work describes an energy-efficient design and expressive structure that integrates hardware specialization, protocol-level energy optimization, and task offloading with wireless edge computing. The study examines power-efficient hardware design, energy-efficient communication implementation, and effective dynamic task rescheduling to optimize energy consumption. Edge offloading in a case study of an energy-aware Internet of Things model demonstrated significant improvements in energy efficiency and communication latency compared to processing on the device and in the cloud. The integrated, scalable, and secure resource adaptive control suggests critical trade-offs for energy, uptime, latency, and system reliability. The focus of ongoing work will be on intelligent offloading to heterogeneous wired edge systems. These systems will integrate new algorithms and advanced energy optimization techniques. Integrated solutions bridge the gap in the sustainability and performance of wireless systems.