Article

Sparse data aggregation in sensor networks

Authors:

Leonidas Guibas,

Nikola Milosavljevic,

John HershbergerAuthors Info & Claims

IPSN '07: Proceedings of the 6th international conference on Information processing in sensor networks

Pages 430 - 439

https://doi.org/10.1145/1236360.1236414

Published: 25 April 2007 Publication History

Abstract

We study the problem of aggregating data from a sparse set of nodes in a wireless sensor network. This is a common situation when a sensor network is deployed to detect relatively rare events. In such situations, each node that should participate in the aggregation knows this fact based on its own sensor readings, but there is no global knowledge in the network of where all these interesting nodes are located. Instead of blindly querying all nodes in the network, we show how the interesting nodes can autonomously discover each other in a distributed fashion and form an ad hoc aggregation structure that can be used to compute cumulants, moments, or other statistical summaries. Key to our approach is the capability for two nodes that wish to communicate at roughly the same time to discover each other at a cost that is proportional to their network distance. We show how to build nearly optimal aggregation structures that can further deal with network volatility and compensate for the loss or duplication of data by exploiting probabilistic techniques.

References

[1]

D. Braginsky and D. Estrin. Rumor routing algorithm for sensor networks. In Proc. 1st ACM International Workshop on Wireless Sensor Networks and Applications, pages 22--31, 2002.

Digital Library

[2]

E. Cohen. Size-estimation framework with applications to transitive closure and reachability. J. Comput. Syst. Sci., 55(3):441--453, 1997.

Digital Library

[3]

J. Considine, F. Li, G. Kollios, and J. Byers. Approximate aggregation techniques for sensor databases. In ICDE'04: Proceedings of the 20th International Conference on Data Engineering, pages 449--460, 2004.

Digital Library

[4]

G. Cormode, M. Garofalakis, S. Muthukrishnan, and R. Rastogi. Holistic aggregates in a networked world: Distributed tracking of approximate quantiles. In SIGMOD'05: Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data, pages 25--36, 2005.

Digital Library

[5]

S. P. Fekete, M. Kaufmann, A. Kröller, and K. Lehmann. A new approach for boundary recognition in geometric sensor networks. In 17th Canaidan Conference on Computational Geometry, pages 82--85, 2005.

[6]

S. Funke. Topological hole detection in wireless sensor networks and its applications. In DIALM-POMC '05: Proceedings of the 2005 Joint Workshop on Foundations of Mobile Computing, pages 44--53, 2005.

Digital Library

[7]

B. Karp and H. Kung. GPSR: Greedy perimeter stateless routing for wireless networks. In Proc. of the ACM/IEEE International Conference on Mobile Computing and Networking (MobiCom), pages 243--254, 2000.

Digital Library

[8]

M. Khan, V. Kumar, and G. Pandurangan. Distributed local algorithms for constructing approximate minimum spanning trees with applications to wireless sensor networks. Dept. Comput. Sci., Purdue University, West Lafayette, Indiana, 2006.

[9]

A. Kröller, S. P. Fekete, D. Pfisterer, and S. Fischer. Deterministic boundary recognition and topology extraction for large sensor networks. In Proceedings of the 17th Annual ACM-SIAM Symposium on Discrete Algorithms, pages 1000--1009, 2006.

Digital Library

[10]

X. Liu, Q. Huang, and Y. Zhang. Combs, needles, haystacks: balancing push and pull for discovery in large-scale sensor networks. In SenSys '04: Proceedings of the 2nd International Conference on Embedded networked sensor systems, pages 122--133, New York, NY, USA, 2004. ACM Press.

Digital Library

[11]

S. Madden, M. J. Franklin, J. M. Hellerstein, and W. Hong. TAG: A Tiny AGgregation service for ad-hoc sensor networks. SIGOPS Oper. Syst. Rev., 36(SI):131--146, 2002.

Digital Library

[12]

A. Manjhi, S. Nath, and P. B. Gibbons. Tributaries and deltas: Efficient and robust aggregation in sensor network streams. In SIGMOD'05: Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data, pages 287--298, 2005.

Digital Library

[13]

S. Nath, P. B. Gibbons, S. Seshan, and Z. R. Anderson. Synopsis diffusion for robust aggregation in sensor networks. In SenSys'04: Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems, pages 250--262, 2004.

Digital Library

[14]

D. Niculescu and B. Nath. Trajectory-based forwarding and its applications. In Proc. 9th Annual International Conference on Mobile Computing and Networking (MobiCom 2003), pages 260--272. ACM Press, 2003.

Digital Library

[15]

R. Sarkar, X. Zhu, and J. Gao. Double rulings for information brokerage in sensor networks. In Proc. of the ACM/IEEE International Conference on Mobile Computing and Networking (MobiCom), pages 286--297, September 2006.

Digital Library

[16]

S. Shakkottai. Asymptotics of query strategies over a sensor network. In Proc. of the 23rd Annual Joint Conference of the IEEE Computer and Communications Societies (InfoCom), pages 557--565, March 2004.

[17]

N. Shrivastava, C. Buragohain, D. Agrawal, and S. Suri. Medians and beyond: New aggregation techniques for sensor networks. In SenSys'04: Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems, pages 239--249, 2004.

Digital Library

[18]

P. Skraba, Q. Fang, A. Nguyen, and L. Guibas. Sweeps over wireless sensor networks. In IPSN '06: Proceedings of the 5th international conference on Information processing in sensor networks, pages 143--151, 2006.

Digital Library

[19]

F. Stann, J. Heidemann, R. Shroff, and M. Z. Murtaza. RBP: robust broadcast propagation in wireless networks. In SenSys'06: Proceedings of the 4th international conference on Embedded networked sensor systems, pages 85--98, 2006.

Digital Library

[20]

Y. Wang, J. Gao, and J. S. B. Mitchell. Boundary recognition in sensor networks by topological methods. In Proc. of the ACM/IEEE International Conference on Mobile Computing and Networking (MobiCom), pages 122--133, September 2006.

Digital Library

Cited By

Wei WKe QZielonka APleszczyński MWoźniak M(2023)Vehicle Parking Navigation Based on Edge Computing With Diffusion Model and Information Potential FieldIEEE Transactions on Services Computing10.1109/TSC.2023.328633216:5(3827-3836)Online publication date: Sep-2023
https://doi.org/10.1109/TSC.2023.3286332
Li XWang MShi SQian CLandsiedel ONahrstedt K(2019)VERIDProceedings of the International Conference on Internet of Things Design and Implementation10.1145/3302505.3310074(118-129)Online publication date: 15-Apr-2019
https://dl.acm.org/doi/10.1145/3302505.3310074
Randhawa SJain S(2017)Data Aggregation in Wireless Sensor NetworksWireless Personal Communications: An International Journal10.1007/s11277-017-4674-597:3(3355-3425)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1007/s11277-017-4674-5
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Index Terms

Sparse data aggregation in sensor networks
1. Networks
  1. Network protocols
    1. Network layer protocols
      1. Routing protocols
2. Theory of computation
  1. Randomness, geometry and discrete structures
    1. Computational geometry

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Information & Contributors

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Published In

cover image ACM Conferences

IPSN '07: Proceedings of the 6th international conference on Information processing in sensor networks

April 2007

592 pages

ISBN:9781595936387

DOI:10.1145/1236360

General Chair:
Tarek Abdelzaher
University of Illinois at Urbana-Champaign
,
Program Chairs:
Leo Guibas
Stanford University
,
Matt Welsh
Harvard University

Copyright © 2007 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 April 2007

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IPSN07

Sponsor:

IPSN07: The 6th International Conference on Information Processing in Sensor Networks

April 25 - 27, 2007

Massachusetts, Cambridge, USA

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Overall Acceptance Rate 143 of 593 submissions, 24%

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Citations

Cited By

Wei WKe QZielonka APleszczyński MWoźniak M(2023)Vehicle Parking Navigation Based on Edge Computing With Diffusion Model and Information Potential FieldIEEE Transactions on Services Computing10.1109/TSC.2023.328633216:5(3827-3836)Online publication date: Sep-2023
https://doi.org/10.1109/TSC.2023.3286332
Li XWang MShi SQian CLandsiedel ONahrstedt K(2019)VERIDProceedings of the International Conference on Internet of Things Design and Implementation10.1145/3302505.3310074(118-129)Online publication date: 15-Apr-2019
https://dl.acm.org/doi/10.1145/3302505.3310074
Randhawa SJain S(2017)Data Aggregation in Wireless Sensor NetworksWireless Personal Communications: An International Journal10.1007/s11277-017-4674-597:3(3355-3425)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1007/s11277-017-4674-5
Blanchard FFouchal HHerbin M(2017)Energy and activity monitoring over wireless sensor networksConcurrency and Computation: Practice and Experience10.1002/cpe.426029:23Online publication date: 29-Aug-2017
https://doi.org/10.1002/cpe.4260
Sharma GBusch C(2016)Near-Optimal Deterministic Steiner Tree Maintenance in Sensor NetworksACM Transactions on Sensor Networks10.1145/285415512:1(1-29)Online publication date: 10-Mar-2016
https://dl.acm.org/doi/10.1145/2854155
Ebrahimi DAssi C(2015)Network Coding-Aware Compressive Data Gathering for Energy-Efficient Wireless Sensor NetworksACM Transactions on Sensor Networks10.1145/282995311:4(1-24)Online publication date: 2-Nov-2015
https://dl.acm.org/doi/10.1145/2829953
Fouchal HHerbin MBlanchard F(2015)Centralized energy monitoring over wireless sensor networks2015 International Wireless Communications and Mobile Computing Conference (IWCMC)10.1109/IWCMC.2015.7289183(788-792)Online publication date: Aug-2015
https://doi.org/10.1109/IWCMC.2015.7289183
Sharma GBusch C(2014)Near-Optimal Deterministic Steiner Tree Maintenance in Sensor NetworksProceedings of the 2014 IEEE International Conference on Distributed Computing in Sensor Systems10.1109/DCOSS.2014.12(201-208)Online publication date: 26-May-2014
https://dl.acm.org/doi/10.1109/DCOSS.2014.12
Urteaga IYu NHubbell NHan Q(2014)AWAREPervasive and Mobile Computing10.1016/j.pmcj.2013.10.01113(111-124)Online publication date: 1-Aug-2014
https://dl.acm.org/doi/10.1016/j.pmcj.2013.10.011
Faulkner MLiu AKrause AAbdelzaher TRömer KRajkumar R(2013)A fresh perspectiveProceedings of the 12th international conference on Information processing in sensor networks10.1145/2461381.2461387(7-18)Online publication date: 8-Apr-2013
https://dl.acm.org/doi/10.1145/2461381.2461387
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