Reducing carbon footprint is a trend within modern green restaurants. A carbon footprint is the total set of greenhouse gas (GHG) emissions caused by an organization, event or product. Food and beverage restaurants have to deliver food using a minimal carbon footprint. Of previous researches, only a small fraction is focused on reducing carbon footprints in a culinary room. Besides, a carbon footprint cost model was hard to solve in economic computation time. Therefore, the main purpose of this research is through a distributed information system to accelerate computing ability of a carbon footprint cost model. Through the distributed computing, our experimental results showed that the proposed approach outperformed the literature approach efficiently. The algorithm improved rate was 68.6%, and low down 82.1% carbon footprint than manual. The proposed approach could contribute to accelerate calculations in others problems due to using multiple machines in future researches.