A multi-agent simulation framework on small Hadoop cluster

In this paper, we explore the benefits and possibilities about the implementation of multi-agents simulation framework on a Hadoop cloud. Scalability, fault-tolerance and failure-recovery have always been a challenge for a distributed systems application developer. The highly efficient fault tolerant nature of Hadoop, flexibility to include more systems on the fly, efficient load balancing and the platform-independent Java are useful features for development of any distributed simulation. In this paper, we propose a framework for agent simulation environment built on Hadoop cloud. Specifically, we show how agents are represented, how agents do their computation and communication, and how agents are mapped to datanodes. Further, we demonstrate that even if some of the systems fail in the distributed setup, Hadoop automatically rebalances the work load on remaining systems and the simulation continues. We present some performance results on this environment for a few example scenarios.     

Glycerol Hydrogenolysis to 1,2-Propanediol by Cu/ZnO/Al2O3 Catalysts

The effect of preparation methods on the Cu/ZnO/Al₂O₃ catalyst structure and catalytic activity on liquid glycerol hydrogenolysis to 1,2-propanediol has been investigated. The physicochemical properties of the catalysts were characterized by BET, XRD, TG/DTA, NH₃-TPD and TPR. The experimental results showed that the catalyst prepared by an oxalate gel–coprecipitation had the highest activity. At 200 °C and 400 psi hydrogen pressure, the glycerol conversion and 1,2-propanediol selectivity catalyzed by the Cu/ZnO/Al₂O₃ catalyst prepared via oxalate gel–coprecipitation were 92.3 and 94.5 % respectively. It was found that the 1,2-propanediol selectivity was dependent on hydrogen pressure and the un-desired by-products were mainly due to the side reactions caused by the presence of the intermediate acetol.