EDGE COMPUTING FOR LATENCY-SENSITIVE AI APPLICATIONS
Keywords:
Edge Computing, Latency Optimization, IoT Applications, Distributed Architecture, Real-time ProcessingAbstract
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 is revolutionizing industries through improved efficiency, reliability, and performance. The comprehensive article provides insights into how organizations can leverage edge computing to gain competitive advantages while addressing the evolving demands of modern applications.
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