Edge Computing for Low-Latency loT Applications in Smart Cities
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Abstract
The swift advancement of Internet of Things (IoT) technologies is transforming traditional urban landscapes into intelligent cities, generating substantial volumes of data from interconnected devices. Nonetheless, the latency associated with cloud computing solutions creates obstacles for time-critical applications, including real-time traffic control, emergency response systems, and environmental monitoring. This paper examines the utilization of edge computing as a practical solution to reduce latency and enhance the effectiveness of IoT applications within smart cities. By processing data nearer to its origin—such as IoT sensors and devices—edge computing significantly diminishes the duration required for data transfer and analysis. This localized data processing enhances response times, optimizes bandwidth utilization, and alleviates the stress on centralized cloud infrastructures. Through case studies and empirical evaluations, we assess the efficacy of edge computing in diverse smart city situations, underscoring its capacity to facilitate real-time decision-making and boost overall urban efficiency. Additionally, the paper addresses architectural considerations, security issues, and prospective trends in the integration of edge computing within smart city frameworks. The results indicate that adopting edge computing can cultivate more resilient, adaptive, and effective smart city ecosystems, ultimately improving the quality of life for urban inhabitants.
Keywords
Edge computing Internet of things Smart cities Low latency Real-time processingReferences (15)
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