A PSO based Computation Offloading Model in Edge Computing

Limitations of traditional cloud computing have fueled the rise of edge computing. This technique addresses the latency and real-time processing issues that come with using a typical cloud, and it operates at the edge of the network. While the applications of edge computing have grown, it's requiring a more sophisticated offloading strategy. Considerations needed to be made for elements including network circumstances, computing complexity, and energy efficiency. In this work, a Particle Swarm Optimization (PSO) based offloading model is proposed to optimize computation offloading in edge computing. PSO dynamically distributes the tasks for optimal efficiency and highlights its effectiveness in minimizing system costs, reducing task execution time and energy consumption, that improve overall performance.