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Journal of Combinatorial Optimization

, Volume 27, Issue 2, pp 221–240 | Cite as

An improved distributed data aggregation scheduling in wireless sensor networks

  • Deying Li
  • Qinghua Zhu
  • Hongwei Du
  • Jianzhong Li
Article

Abstract

This paper focuses on the distributed data aggregation collision-free scheduling problem, which is one of very important issues in wireless sensor networks. Bo et al. (Proc. IEEE INFOCOM, 2009) proposed an approximate distributed algorithm for the problem and Xu et al. (Proc. ACM FOWANC, 2009) proposed a centralized algorithm and its distributed implementation to generate a collision-free scheduling for the problem, which are the only two existing distributed algorithms. Unfortunately, there are a few mistakes in their performance analysis in Bo et al. (Proc. IEEE INFOCOM, 2009), and the distributed algorithm can not get the same latency as the centralized algorithm because the distributed implementation was not an accurate implementation of the centralized algorithm (Xu et al. in Proc. ACM FOWANC, 2009). According to those, we propose an improved distributed algorithm to generate a collision-free schedule for data aggregation in wireless sensor networks. Not an arbitrary tree in Bo et al. (Proc. IEEE INFOCOM, 2009) but a breadth first search tree (BFS) rooted at the sink node is adopted, the bounded latency 61R+5Δ−67 of the schedule is obtained, where R is the radius of the network with respect to the sink node and Δ is the maximum node degree. We also correct the latency bound of the schedule in Bo et al. (Proc. IEEE INFOCOM, 2009) as 61D+5Δ−67, where D is a diameter of the network and prove that our algorithm is more efficient than the algorithm (Bo et al. in Proc. IEEE INFOCOM, 2009). We also give a latency bound for the distributed implementation in Xu et al. (Proc. ACM FOWANC, 2009).

Keywords

Distributed approximation algorithm Data aggregation scheduling Collision-free Latency Wireless sensor networks 

Notes

Acknowledgements

This paper was jointly supported in part by National Natural Science Foundation of China under grants 61070191 and 91124001, the Fundamental Research Funds for the Central Universities, and the Research Funds of Renmin University of China under grant 10XNJ032, and Research Fund for the Doctoral Program of Higher Education of China under grant 20100004110001. Dr. Du was supported in part by National Natural Science Foundation of China under grant 61100191 and Natural Scientific Research Innovation Foundation of Harbin Institute of Technology under Project 2011128.

References

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Deying Li
    • 1
  • Qinghua Zhu
    • 1
  • Hongwei Du
    • 2
  • Jianzhong Li
    • 3
  1. 1.School of InformationRenmin University of ChinaBeijingChina
  2. 2.Shenzhen Graduate SchoolHarbin Institute of TechnologyShenzhenChina
  3. 3.School of Computer Science and TechnologyHarbin Institute of TechnologyHarbinChina

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