2026, Vol. 8, Issue 1, Part A

Edge computing has emerged as a critical paradigm for improving the efficiency and scalability of data processing in the Internet of Things (IoT) ecosystem. The rapid proliferation of IoT devices generates massive amounts of data that require processing close to the source to reduce latency, alleviate bandwidth pressures, and ensure real-time decision-making. Traditional cloud computing approaches, which rely on centralized data centers, struggle to meet the growing demand for fast data processing in latency-sensitive applications. This is where edge computing plays a pivotal role, offering distributed computing resources at the "edge" of the network, where data is generated. By enabling data processing at or near the point of origin, edge computing ensures more efficient use of network resources, reduces data transmission delays, and enhances the overall responsiveness of IoT systems.

The impact of edge computing on data processing in IoT devices extends beyond simply improving latency and bandwidth. It also enhances the reliability, security, and scalability of IoT applications. With edge computing, sensitive data can be processed locally, minimizing the risks associated with transmitting data over networks. Furthermore, it provides a more scalable solution, as the distributed nature of edge computing reduces the dependency on centralized cloud infrastructure. However, despite its potential benefits, edge computing introduces several challenges related to device management, security, and interoperability. These challenges require innovative solutions to fully realize the potential of edge computing in IoT environments. This paper explores the fundamentals of edge computing, its role in IoT data processing, and the challenges and opportunities it presents for the future of connected devices.