English  |  正體中文  |  简体中文  |  Items with full text/Total items : 51258/86283 (59%)
Visitors : 8019842      Online Users : 59
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/99981


    Title: Adaptive Job Assign Algorithm Based on Hierarchical Server Cloud Computing
    Authors: Qiu, Jing-Yue;Wei, Hsin-Wen;Lee, Wei-Tsong;Lin, Yu-Chang
    Contributors: 淡江大學電機工程學系
    Date: 2014-08-27
    Issue Date: 2015-01-20 14:22:06 (UTC+8)
    Abstract: The size of data used by enterprises, academia and sciences in recently years has been growing at an exponential rate day by day. Simultaneously, the requirement to process and analyze the large quality of data is also increased. In the previous method, a single computer or a small number of computers cannot process and monitor these large amounts of data, but cloud system can handle the requirement and reduce the costs of data processing now. Therefore, lots of enterprises use the cloud system to process this problem. A basic framework of the cloud system is MapReduce. User must configure the relative setting including the number of computers and virtual machines before running the MapReduce. Each data size is not the same, and users may claim more or less computers and virtual machines than they need, and waste cloud resources or run out of resources. When the job is put in to cloud system, at first, it is processed by a single node for a period of time and if the node detects that the job cannot be completed within the period of time, the node ask another to share the computation. Then, all nodes continue processing until the end of the job. Therefore we proposed mechanism constructs hierarchical dynamic configuration of cloud system (HDCOCS) to efficiently use the resources in the cloud.
    Appears in Collections:[電機工程學系暨研究所] 會議論文

    Files in This Item:

    File Description SizeFormat
    index.html全文0KbHTML16View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback