Optimized Task Mapping for Inkjet Printer Pixel Data Transmission Based on Improved Particle Swarm Optimization Algorithm

Inkjet printers are integral to various industries, offering high-quality printing solutions. In inkjet printing applications, field programmable gate arrays (FPGAs), composed of configurable logic blocks (CLBs), play a critical role by providing the flexibility and computational power necessary for executing complex tasks. However, conventional task mapping methods to CLBs often fail to account for communication costs, which can impair system efficiency. This paper proposes an optimization approach for task mapping based on the Similarity-Aware Gaussian Particle Swarm Optimization (SAG-PSO) algorithm, aiming to enhance mapping efficiency while minimizing communication overhead. The SAG-PSO algorithm incorporates a similarity-aware Gaussian mutation strategy and additional search iterations, improving global exploration and reducing the risk of local optima. Experimental results show that SAG-PSO outperforms traditional task mapping methods, achieving significant reductions in communication costs and improvements in task mapping efficiency. This work advances embedded systems optimization and provides a foundation for future improvements in FPGA-based task mapping strategies.