Otimizando o escalonamento de jobs no processo de rasterização de documentos personalizáveis

Abstract

Digital presses have consistently improved their speed in the past ten years. Meanwhile, the need for document personalization and customization has increased. As a consequence of these two facts, the traditional RIP (Raster Image Processing) process has become a highly demanding computational step in the print workflow. Print Service Providers (PSPs) are now using multiple RIP engines and parallelization strategies to speed up the whole ripping process which is currently performed on a per-page basis. Nevertheless, these strategies are not optimized in terms of ensuring the best resorces utilization for the RIP engines. Depending on the input document jobs characteristics, the ripping step may not achieve the print-engine speed creating a unwanted bottleneck. In previous works, some strategies have been introduced to increase the performance of the ripping procedure by using techniques of parallel and distributed computing. Despite of the good results achieved, it was possible to identify that some optimizations could be proposed in order to improve the load balance between ripping units. In this scenario, to maximize the use of resources, new strategies have been proposed to distribute the workload balancing between ripping units considering new characteristics of documents such as transparency and reusability of objects. The obtained results confirm that it was indeed possible to improve the performance through the use of these new features.