Enhancing IoT Efficiency by Minimizing Latency and Boosting Real-Time Processing with Edge Computing

Enhancing IoT Efficiency by Minimizing Latency and Boosting Real-Time Processing with Edge Computing

연구 분야: Networking

학회: SN Computer Science

Edge computing has arisen as an essential paradigm in the Internet of things (IoT) ecosystem to overcome the limitations of those traditional cloud-centric systems. The role of edge computing helps in processing the data and making decisions in real-time making it super quick as the data is processed near the origin. In applications like smart healthcare, industrial automation, cars etc. where, immediate response is critical and thus we need this transformation to happen at a faster pace. Sending data to centralized cloud servers for processing, as was the traditional approach, is difficult and unnecessary in IoT environments with large and high-frequency data volume generated by dispersed devices. Edge computing helps improve the efficiency and scalability of Internet of Things applications by decentralizing some processing resources taking advantage of that. This decentralized model elevates the security and privacy of data, as sensitive information can be processed at the edge instead of being sent across potentially insecure network paths, easing some of the load on cellular traffic networks. In addition to increasing the cognitive capabilities and response times of IoT applications, edge computing represents an additional benefit as it provides the means to incorporate advanced technologies like artificial intelligence and machine learning at the edge. As, edge computing enables real-time analytics, while also reducing latency, which greatly increases the speed and reliability of an IoT system. This method quickly converts raw data into actionable insights. In this article, to tried to focus on core principles of edge computing design, how edge computing improvises real-time processing in IoT, and how it is responsible for reducing latency. It also tackles numerous real-life use cases and the anticipated further developments of edge computing that will lead to the next surge of IoT innovation.