• DocumentCode
    3192726
  • Title

    A load-balanced data aggregation scheduling for duty-cycled wireless sensor networks

  • Author

    Zhengyu Chen ; Geng Yang ; Lei Chen ; Jian Xu ; Haiyong Wang

  • Author_Institution
    Key Lab. of Broadband Wireless Commun. & Sensor Network Technol. of Minist. of Educ., Nanjing Univ. of Posts &Telecommun., Nanjing, China
  • fYear
    2012
  • fDate
    3-6 Dec. 2012
  • Firstpage
    888
  • Lastpage
    893
  • Abstract
    To bridge the gap between limited energy supplies of the sensor nodes and the system lifetime, duty-cycle Wireless Sensor Networks (WSNs) with data aggregation are studied in this paper. We proposed a load-balanced and latency-efficient data aggregation scheduling for duty-cycled WSNs. A shortest path tree (SPT) is used as the routing structure for data aggregation scheduling. In SPT, parent-children assignments are well-designed to assign nodes from level h+1 to the parents at level h such that every parent has a balanced load, while reducing the sleep latency which is a period of time for a sender to wait for its parent to be active. Finally, through the simulation and comparisons, we prove the effectiveness of our approach.
  • Keywords
    resource allocation; scheduling; telecommunication network routing; trees (mathematics); wireless sensor networks; SPT; WSN; duty-cycled wireless sensor networks; latency-efficient data aggregation scheduling; load-balanced data aggregation scheduling; parent-children assignments; routing structure; sensor nodes; shortest path tree; sleep latency reduction; system lifetime; Algorithm design and analysis; Bipartite graph; Cloud computing; Conferences; Routing; Scheduling; Wireless sensor networks; Data aggregation; Duty-cycle; Load-Balanced; Wireless Sensor Networks; latency;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing Technology and Science (CloudCom), 2012 IEEE 4th International Conference on
  • Conference_Location
    Taipei
  • Print_ISBN
    978-1-4673-4511-8
  • Electronic_ISBN
    978-1-4673-4509-5
  • Type

    conf

  • DOI
    10.1109/CloudCom.2012.6427533
  • Filename
    6427533