• DocumentCode
    266997
  • Title

    Job Scheduling for Cloud Computing Integrated with Wireless Sensor Network

  • Author

    Chunsheng Zhu ; Xiuhua Li ; Leung, Victor C. M. ; Xiping Hu ; Yang, Laurence T.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of British Columbia, Vancouver, BC, Canada
  • fYear
    2014
  • fDate
    15-18 Dec. 2014
  • Firstpage
    62
  • Lastpage
    69
  • Abstract
    The powerful data storage and data processing abilities of cloud computing (CC) and the ubiquitous data gathering capability of wireless sensor network (WSN) complement each other in CC-WSN integration, which is attracting growing interest from both academia and industry. However, job scheduling for CC integrated with WSN is a critical and unexplored topic. To fill this gap, this paper first analyzes the characteristics of job scheduling with respect to CC-WSN integration and then studies two traditional and popular job scheduling algorithms (i.e., Min-Min and Max-Min). Further, two novel job scheduling algorithms, namely priority-based two phase Min-Min (PTMM) and priority-based two phase Max-Min (PTAM), are proposed for CC integrated with WSN. Extensive experimental results show that PTMM and PTAM achieve shorter expected completion time than Min-Min and Max-Min, for CC integrated with WSN.
  • Keywords
    cloud computing; minimax techniques; scheduling; ubiquitous computing; wireless sensor networks; CC-WSN integration; PTAM algorithms; PTMM algorithms; cloud computing; data processing; data storage; expected completion time; expected execution time; job scheduling algorithms; priority-based two phase max-min algorithms; priority-based two phase min-min algorithms; ubiquitous data gathering capability; wireless sensor network; Job shop scheduling; Memory; Scheduling algorithms; Temperature sensors; Wireless sensor networks; Cloud computing; Max-Min; Min-Min; expected execution time; job scheduling; priority; wireless sensor network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing Technology and Science (CloudCom), 2014 IEEE 6th International Conference on
  • Conference_Location
    Singapore
  • Type

    conf

  • DOI
    10.1109/CloudCom.2014.106
  • Filename
    7037649