Optimizing Real-Time Data Processing: Edge and Cloud Computing Integration for Low-Latency Applications in Smart Cities

  • Rajesh Kumar Malviya, Ravi Kumar Vankayalapati, Lakshminarayan
Keywords: Real-Time Data Processing, Edge Computing, Cloud Computing, Low-Latency Applications, Smart Cities, Data Integration, IoT (Internet of Things), Distributed Computing, Latency Optimization, Data Analytics, Scalability, Network Architecture, Fog Computing, Stream Processing, Data Sovereignty, Machine Learning at the Edge, Real-Time Analytics, Smart Infrastructure, Urban Computing, Sensor Networks, Resource Management, Traffic Management Systems, Predictive Maintenance, Interoperability, Data Security.

Abstract

The rapid expansion of smart city infrastructure necessitates efficient real-time data processing to enhance urban services and improve citizen experiences. This paper explores the integration of edge and cloud computing as a strategic framework for optimizing low-latency applications in smart cities. By distributing data processing tasks between edge devices and cloud servers, we minimize latency and bandwidth usage while maximizing computational efficiency. We analyze various use cases, including traffic management, environmental monitoring, and public safety systems, demonstrating how this hybrid approach addresses the unique challenges of real-time data handling in urban environments. Through experimental evaluations and simulations, we quantify performance improvements and propose best practices for implementing this integrated architecture. Our findings suggest that leveraging edge-cloud synergy can significantly enhance responsiveness and scalability in smart city applications, paving the way for more adaptive and intelligent urban ecosystems.

Published
2023-01-08
Issue
Volume 2023
Section
Regular Issue

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