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Performance Comparison Between Hama and Hadoop
Shuo Li,Baomin Xu 보안공학연구지원센터 2015 International Journal of Database Theory and Appli Vol.8 No.3
Massive scientific computations such as matrix, graph and network algorithms are very attractive when they come to modelling real-world data. Apache Hama is a pure BSP (Bulk Synchronous Parallel) distributed computing framework for massive scientific computations. In this paper, our experiments were conducted on a 4-node Hadoop cluster. We implement Monte Carlo algorithm of Pi in Hama and Hadoop under the same software and hardware environment. The experimental results show that Hama can achieve much higher performance than Hadoop in our testbed.
Task Scheduling Algorithm based-on QoS Constrains in Cloud Computing
Yi Zhang,Baomin Xu 보안공학연구지원센터 2015 International Journal of Grid and Distributed Comp Vol.8 No.6
Based on the study of traditional min-min scheduling algorithm, the paper proposed a min-min task scheduling algorithm based on QOS constraints in cloud computing. According to the vector which is generated by QOS parameters, the algorithm processes the matching of resources and tasks, and then provides users with resources which meet their requirements. Experimental results show that the min-min task scheduling algorithm for cloud computing has better performance in such aspects as task execution time, rate of discarding task and QOS satisfaction compared with traditional min-min scheduling algorithm.