The rapid proliferation of smart city initiatives has generated vast amounts of data from heterogeneous sources, including sensors, Internet of Things (IoT) devices, and mobile applications. Traditional cloud infrastructures face high latency, bandwidth constraints, and scalability issues in handling such massive real-time data streams. Edge computing addresses these limitations by decentralizing data processing and bringing computation closer to the data source. This paradigm enables faster response, lower latency, optimized bandwidth use, and improved resilience. For applications such as traffic management, public safety, energy optimization, and environmental monitoring, edge computing significantly enhances efficiency and scalability. This paper investigates the role of edge computing in smart city applications, discusses benefits and challenges, and presents performance models focusing on latency reduction, bandwidth optimization, and energy efficiency. The study highlights how edge computing can be integrated into sustainable smart city frameworks to enhance urban living standards.
Thoutam et al. (Sun,) studied this question.