REAL-TIME DATA PROCESSING IN CLOUDAND EDGE COMPUTING
Keywords:
Real-time Processing, Distributed Computing, Latency Optimization, IoT InfrastructureAbstract
This article explores the integration of cloud and edge computing in enabling real-time data processing across various industries. It examines the fundamental differences between real-time and batch-processing approaches, highlighting the technical requirements and architectural considerations necessary for effective implementation. The article explores how the symbiotic relationship between cloud and edge computing creates a robust framework for processing time-sensitive data, with a particular focus on applications in predictive maintenance, autonomous driving, and healthcare monitoring. Through analysis of current implementations and emerging technologies, the article demonstrates how this integration optimizes resource utilization, reduces latency, and enhances system reliability while addressing key challenges in data quality, system reliability, and security.
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