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An Efficient Replicated System for the Metadata of HDFS
Zhanye Wang,Tao Xu,Dongsheng Wang 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.5
Hadoop HDFS is an open source project from Apache Software Foundation for scalable, distributed computing and data storage. HDFS has become a critical component in today's cloud computing environment and a wide range of applications built on top of it. However, the initial design of HDFS has introduced a single-point-of-failure, since HDFS contains only one active namenode, if this namenode experiences software or hardware failures, the whole HDFS cluster is unusable, this is a reason why people are reluctant to deploy HDFS for an application whose requirement is high availability. In this paper, we present a solution to enable the high availability for HDFS's namenode through efficient metadata replication. Our solution has 3 major advantages than existing ones: We utilize multiple active namenodes, instead of one, to build a cluster to serve requests of metadata simultaneously; We implement a pub/sub system to handle the metadata replication process across these active namonodes efficiently; We also propose a novel replication algorithm to deal with the network delay when the namonodes are deployed in different areas. Based on the solution we build a prototype called NCluster and integrate it with HDFS. We evaluate NCluster to exhibit its feasibility and effectiveness. The experimental results show that our solution performs well with low replication cost, good throughput and scalability.
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Min Tan,Zhen Shang,Chenbo Xie,Hui Ma,Qian Deng,Xiaomin Tian,Peng Zhuang,Zhanye Zhang,Yingjian Wang 한국광학회 2018 Current Optics and Photonics Vol.2 No.1
To measure atmospheric temperature, water vapor, and aerosol simultaneously, an efficient multi-function Raman lidar using an ultraviolet-wavelength laser has been developed. A high-performance spectroscopic box that utilizes multicavity interference filters, mounted sequentially at small angles of incidence, is used to separate the lidar return signals at different wavelengths, and to extract the signals with high efficiency. The external experiments are carried out for simultaneous detection of atmospheric temperature, water vapor, and aerosol extinction coefficient in Beijing, under clear and hazy weather conditions. The vertical profiles of temperature, water vapor, and aerosol extinction coefficient are analyzed. The results show that for an integration time of 5 min and laser energy of 200 mJ, the mean deviation between measurements obtained by lidar and radiosonde is small, and the overall trend is similar. The statistical temperature error for nighttime is below 1 K up to a height of 6.2 km under clear weather conditions, and up to a height of 2.5 km under slightly hazy weather conditions, with 5 min of observation time. An effective range for simultaneous detection of temperature and water vapor of up to 10 km is achieved. The temperature-inversion layer is found in the low troposphere. Continuous observations verify the reliability of Raman lidar to achieve real-time measurement of atmospheric parameters in the troposphere.
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