The improvement of Hadoop performance has received considerable attention from researchers in cloud computing fields. Most studies have focused on improving the performance of a Hadoop cluster. Notably, various parameters are required to configure Hadoop and must be adjusted to improve performance. This paper proposes a mechanism to improve Hadoop, schedule jobs, and allocate and utilize resources. Specifically, we present an improved ant colony optimization method to schedule jobs according to the job size and the time expected for execution. Priority is given to the job with the minimum data size and minimum response time. The resource usage and running jobs by data node are predicted using an artificial neural network, and job activity and resource usage are monitored using the resource manager. Moreover, we enhance the Hadoop Name node performance by adding an aggregator node to the default HDFS framework architecture. The changes involve four entities: the name node, secondary name node, aggregator nodes, and data nodes, where the aggregator node is responsible for assigning the jobs among the data node, and the Name node keeps tracking only the aggregator nodes. We test the overall scheme among Amazon EC2 and S3, and show the results of throughput and CPU response time for different data sizes. Finally, we show that the proposed approach shows significant improvement compare to native Hadoop and other approaches.
The temperature and mechanism of phase transition of poly(N-isopropylacrylamide-co-acrylic acid) [P(NiPAAm-co-AAc)], which is one of the multi-stimuli responsive polymers, were investigated at various pHs using infrared (IR) spectroscopy, two-dimensional (2D) gradient mapping, and two-dimensional correlation spectroscopy (2D-COS). The determined phase transition temperature of P(NiPAAm-co-AAc) at pH 4, 3, and 2 based on 2D gradient mapping and principal component analysis (PCA) showed that it decreases with decreasing pH, because COOH group in AAc changes with variation of pH. The results of 2D-COS analysis indicated that the phase transition mechanism of P(NiPAAm-co-AAc) hydrogel at pH4 is different from that at pH2 due to the effect of COOH group of AAc.
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