Abstract
Wireless sensor networks promise a new paradigm for gathering data via collaboration among sensors spreading over a large geometrical region. Many real-time applications impose stringent delay requirements and ask for time-efficient schedules of data aggregations in which sensed data at sensors are combined at intermediate sensors along the way towards the data sink. The Minimum Data Aggregation Time (MDAT) problem is to find the schedule that routes data appropriately and has the shortest time for all requested data to be aggregated to the data sink.
In this paper we study the MDAT problem with uniform transmission range of all sensors. We assume that, in each time round, data sent by a sensor reaches exactly all sensors within its transmission range, and a sensor receives data if it is the only data that reaches the sensor in this time round. We first prove that this problem is NP-hard even when all sensors are deployed a grid and data on all sensors are required to be aggregated to the data sink. We then design a (Δ–1)-approximation algorithm for MDAT problem, where Δ equals the maximum number of sensors within the transmission range of any sensor. We also simulate the proposed algorithm and compare it with the existing algorithm. The obtained results show that our algorithm has much better performance in practice than the theoretically proved guarantee and outperforms other algorithm.
This work was supported in part by the NSF of China under Grant No. 70221001 and 60373012.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Annamalai, V., Gupta, S.K.S., Schwiebert, L.: On tree-based convergecasting in wireless sensor networks. In: WCNC 2003-IEEE Wireless Communication and Networking Conference, vol. 4(1), pp. 1942–1947 (2003)
Bar-Noy, A., Guha, S., Naor, J., Schieber, B.: Message multicasting in heterogeneous networks. SIAM J. Comput. 30(2), 347–358
Bulusu, N., Heidemann, J., Estrin, D.: GPS-less low cost outdoor localization for very small devices, Technical Report 00-729, Computer Science Department, University of Sourthern California (April 2000)
Lichtenstein, D.: Planar formulae and their uses. SIAM J. Comput. 11, 329–343 (1982)
Biedl, T., Kant, G.: A better heuristic for orthogonal graph drawings. Computational Geometry 9, 159–180 (1998)
Di Battista, G., Liotta, G., Vargiu, F.: Spirality of orthogonal representations and optimal drawings of series-parallel graphs and 3-planar graphs. In: Dehne, F., Sack, J.-R., Santoro, N. (eds.) WADS 1993. LNCS, vol. 709, pp. 151–162. Springer, Heidelberg (1993)
Kesselman, A., Kowalski, D.: Fast distributed algorithm for convergecast in ad hoc geometric radio networks. In: Proc. 2nd Annual Conf. on Wireless on Demand Network Systems and Serveices (WoNS 2005), St. Moritz, Switzerland (January 2005)
Varshnery, M., Bagrodia, R.: Detailed models for sensor network simulations and their impact on network performance. In: MSWim 2004, Venezia, Italy (October 2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chen, X., Hu, X., Zhu, J. (2005). Minimum Data Aggregation Time Problem in Wireless Sensor Networks. In: Jia, X., Wu, J., He, Y. (eds) Mobile Ad-hoc and Sensor Networks. MSN 2005. Lecture Notes in Computer Science, vol 3794. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11599463_14
Download citation
DOI: https://doi.org/10.1007/11599463_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30856-0
Online ISBN: 978-3-540-32276-4
eBook Packages: Computer ScienceComputer Science (R0)