Temperature-adaptive time synchronization for wireless sensor networks

被引：0
|
作者：
Jin, Meng [1 ]
Chen, Xiao-Jiang [1 ]
Fang, Ding-Yi [1 ]
Tang, Zhan-Yong [1 ]
Liu, Chen [1 ]
Xu, Dan [1 ]
Wang, Wei [1 ]
机构：
[1] School of Information and Technology, Northwest University, Xi'an
来源：
Ruan Jian Xue Bao/Journal of Software | 2015年 / 26卷 / 10期
关键词：
Environment-adaptive; Skew estimation; Temperature sensitivity factor; Time synchronization; Wireless sensor network;
D O I：
10.13328/j.cnki.jos.004792
中图分类号：
学科分类号：
摘要：
The low-cost crystal oscillators in wireless sensor networks are prone to be affected by their working conditions such as temperature, voltage, and humidity. Such problem brings two key challenges for time synchronization in wireless sensor networks (WSNs): Excessive communication overhead and the trade-off between accuracy and cost. This paper introduces a novel environment-adaptive time synchronization approach that enables nodes to estimate their clock skew by exploiting temperature information. The approach can substantially reduce communication overhead since clock skew estimation mostly relies on local information. In addition, this work proposes an environmental-adaptive interval adjustment scheme for duty-cycled clock calibration, which provides a convenient trade-off between the timing accuracy and the energy efficiency. © Copyright 2015, Institute of Software, the Chinese Academy of Sciences. All rights reserved.
引用
收藏
页码：2667 / 2683
页数：16
相关论文
共 30 条
  • [1] Akyildiz I.F., Su W., Sankarasubramaniam Y., Cayirci E., Wireless sensor networks: A survey, Computer Networks, 38, 4, pp. 393-422, (2002)
  • [2] Cerpa A., Elson J., Estrin D., Girod L., Hamiltion M., Zhao J., Habitat monitoring: Application driver for wireless communications technology, Proc. of the ACM SIGCOMM Computer Communication Review-Workshop on Data Communication in Latin America and the Caribbean 2001, pp. 20-41, (2001)
  • [3] Virone G., Wood A., Selavo L., Cao Q., Fang L., Doan T., He Z., Stankovic J., An advanced wireless sensor network for health monitoring, Proc. of the Transdisciplinary Conf. on Distributed Diagnosis and Home Healthcare 2006, pp. 2-4, (2006)
  • [4] Natarajan A., de Silva B., Yap K.K., Motani M., Link layer behavior of body area networks at 2.4 Ghz, Proc. of the Int'l Conf. on Mobile Computing and Networking, pp. 241-252, (2009)
  • [5] Ye W., Heidemann J., Estrin D., Medium access control with coordinated adaptive sleeping for wireless sensor networks, Networking, 12, 3, pp. 493-506, (2004)
  • [6] Ye W., Heidemann J., Estrin D., An energy-efficient MAC protocol for wireless sensor networks, Proc. of the 21st Int'l Conf. on Computer Communications, pp. 1567-1576, (2002)
  • [7] Girod L., Estrin D., Robust range estimation using acoustic and multimodal sensing, Proc. of the 9th Conf. on Intelligent Robots and Systems, pp. 1312-1320, (2001)
  • [8] Jie X., Karthikeyan S., Kyle J., ToneTrack: Leveraging frequency-agile radios for time-based indoor wireless localization, Proc. of the Int'l Conf. on Mobile Computing and Networking, pp. 537-549, (2015)
  • [9] Yang Z., Cai L., Liu Y., Pan J.P., Environment-Aware clock skew estimation and synchronization for wireless sensor networks, Proc. of the Int'l Conf. on Computer Communications, pp. 1017-1025, (2012)
  • [10] Schmid T., Charbiwala Z., Shea R., Srivastava M.B., Temperature compensated time synchronization, Embedded Systems Letters, 1, 2, pp. 37-41, (2009)
123