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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.
Chenglong Zhu,Baomin Li,Jianwei Xia,Na Zhang,Rui Liu 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.6
In this paper, an adaptive event-triggered asymptotic tracking control problem is addressed for switched nonlinear systems with unknown control directions. In existing control schemes, the proposed controller is not directly aimed at the original system, which affects the control performance. Different from the existing control schemes, based on the original system, an event-triggered control law is constructed in this paper. The proposed event-triggered controller guarantees that the tracking error ς1 asymptotically converges to the origin. Finally, the effectiveness of the proposed controller design scheme is proved by simulation examples.