A job profile oriented scheduling architecture for improving the throughput of industrial printing environments. (October 2015)

• Record Type: Journal Article
• Authors: do Carmo, Andriele Busatto; Raeder, Mateus; Nunes, Thiago; Kolberg, Mariana; Fernandes, Luiz Gustavo
• Is Part Of: Computers & industrial engineering. Volume 88(2015)
• Page Start: 191
• Page End: 205
• Publication Date: 2015-10
• Subjects: Scheduling -- High performance printing -- Documents ripping -- Load balancing -- Documents profiling -- Parallel and distributed computing; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2015.07.001
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: We defined a new scheduling architecture in the context of PSPs. The proposed scheduling architecture improve the overall ripping procedure throughput. The proposed architecture allows a better load distribution among the available RIP engines. We provide an adaptive environment to experiment different scheduling algorithms. Abstract: The Digital Printing industry has become extremely specialized in the past few years. The use of personalized documents has emerged as a consolidated trend in this field. In order to meet this demand, languages to describe templates for personalized documents were proposed along with procedures which allow the correct printing of such documents. One of these procedures, which demands a high computational effort, is the ripping phase performed over a queue of documents in order to convert them into a printable format. An alternative to decrease the ripping phase computational time is to use high performance computing techniques to allow parallel ripping of different documents. However, such strategies present several unsolved issues. One of the most severe issues is the impossibility to assure a fair load balancing for any job queue. In this scenario, this work proposes a job profile oriented scheduling architecture for improving the throughput of industrial printing environments through a more efficient use of the available resources. Our results show a performance gain of up to 10% in average over the previous existing strategies applied on different job queue scenarios.