XIAO Mingjun, HUANG Liusheng, XING Kai, et al., “Opportunistic Data Aggregation in Low-Duty-Cycle Wireless Sensor Networks with Unreliable Links,” Chinese Journal of Electronics, vol. 22, no. 3, pp. 599-603, 2013,
Citation: XIAO Mingjun, HUANG Liusheng, XING Kai, et al., “Opportunistic Data Aggregation in Low-Duty-Cycle Wireless Sensor Networks with Unreliable Links,” Chinese Journal of Electronics, vol. 22, no. 3, pp. 599-603, 2013,

Opportunistic Data Aggregation in Low-Duty-Cycle Wireless Sensor Networks with Unreliable Links

Funds:  This work is supported by the National Grand Fundamental Research 973 Program of China (No.2011CB302905), the National Science and Technology Major Project (No.2011ZX03005-002), the National Natural Science Foundation of China (No.60803009, No.61003044), the Natural Science Foundation of Jiangsu Province in China (No.BK2009150, No.BK2010257), and Chinese Universities Scientific Fund.
  • Received Date: 2012-07-01
  • Rev Recd Date: 2012-10-01
  • Publish Date: 2013-06-15
  • This paper proposes an opportunistic data aggregation algorithm to support the data collection in low-duty-cycle Wireless sensor networks (WSNs) with unreliable links. In this algorithm, each sensor selectively waits for some certain time to maximize the number of packets that it can aggregate from its downstream nodes, then transmits the aggregated result to an adaptively selected upstream node following an optimal forwarding sequence. Simulation results show that the algorithm can significantly increase the data aggregation efficiency, and reduce energy consumption and message overhead.
  • loading
  • M. Xiao, J. Wu L. Huang, “Time -sensitive utility-based routing in duty-cycle wireless sensor networks with unreliable link”, IEEE SRDS, Irvine, California, USA, 2012.
    Y. Gu and T.He, “Dynamic switching-based data forwarding for low-duty-cycle wireless sensor networks”, IEEE Transactions on Mobile Computing, Vol.10, No.12, pp.1741-1754, 2011.
    W.R. Heinzelman, A. Chandrakasan and H. Balakishnan, “Energyefficient communication protocol forwireless microsensor networks”, HICSS, Maui, Hawaii, USA, 2000.
    S. Lindsey, C. Raghavendra and K.M. Sivalingam, “Data gathering algorithms in sensor networks using energy metrics”, IEEE Transactions on Parallel and Distributed Systems, Vol.13, No.9, pp.924-935, 2002.
    S. Madden, M.J. Franklin, J.M. Hellerstein and W. Hong, “Tag: A tiny aggregation service for ad-hoc sensor networks”, OSDI, Boston, Massacnuretts, USA, 2002.
    S. Yoon and C. Shahabi, “The clustered aggregation (cag) technique leveraging spatial and temporal correlations in wireless sensor networks”, ACM Trans. on Sensor Networks, Vol.3, No.1, pp.Art. 3: 1-39, 2007.
    J. Considine, M. Hadjieleftheriou, F. Li, J. Byers, G. Kollios, “Robust approximate aggregation in sensor data management systems”, ACM Trans. on Database Systems, Vol.34, No.1, pp.Art. 6:1-35, 2009.
    S. Nath, P.B. Gibbons, S. Seshan, Z. Anderson, “Synopsis diffusion for robust aggregation in sensor networks”, ACM Transactions on Sensor Networks, Vol.4, No.2, pp.Art. 7:1-40, 2008.
    H. Tan, I. Korpeoglu, I. Stojmenovic, “Computing localized power efficient data aggregation trees for sensor networks”, IEEE Transactions on Parallel and Distributed Systems, 2010.
    K. Zhang, M. Liu, J. Zhu, J. Song, J. Zeng, “Data aggregationbased adaptive datareproductive delivery scheme for delay tolerant mobile sensor networks”, Chinese Journal of Electronics, Vol.19, No.1, pp.175-180, 2010.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (572) PDF downloads(1743) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return