👉 Landscape computing, also known as distributed or edge computing with a spatial focus, is an architectural approach that leverages the computational power of devices and networks spread across various geographical locations to process data closer to where it is generated. This paradigm addresses the limitations of traditional centralized cloud computing by reducing latency, enhancing privacy and security, and improving efficiency in handling large-scale, geographically dispersed data. In landscape computing, data processing occurs at the edge of the network, closer to the source of data generation, such as IoT devices, sensors, or local servers. This allows for real-time analytics and decision-making, crucial in applications like smart cities, autonomous vehicles, and industrial IoT. By distributing computational tasks across a network of devices, landscape computing optimizes resource utilization, minimizes bandwidth usage, and supports the seamless integration of diverse data sources, ultimately enabling more responsive and intelligent systems that can adapt to dynamic environments.
