EDGE COMPUTING FOR LATENCY-SENSITIVE AI APPLICATIONS

Edge computing has emerged as a transformative technology for latency-sensitive applications, addressing the limitations of traditional cloud-centric approaches by processing data closer to the source. This paradigm shift has become crucial for applications requiring near-instantaneous response times, such as autonomous vehicles, industrial IoT, and augmented reality experiences. The technology enables reduced latency, optimized bandwidth utilization, and enhanced data privacy through localized processing. This article explores the architectural strategies, optimization techniques, and implementation challenges in edge computing, examining resource allocation, data synchronization, and security considerations. Additionally, it presents real-world use cases across various sectors, demonstrating how edge computing isSandeep Konakanchi