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Robust Computation of Aggregates in Wireless Sensor Networks: Distributed Randomized Algorithms and Analysis
September 2006 (vol. 17 no. 9)
pp. 987-1000
ASCII Text
x 
 
Jen-Yeu Chen, Gopal Pandurangan, Dongyan Xu, "Robust Computation of Aggregates in Wireless Sensor Networks: Distributed Randomized Algorithms and Analysis," IEEE Transactions on Parallel and Distributed Systems, vol. 17, no. 9, pp. 987-1000, September, 2006.
 
 
BibTex
x
 
@article{ 10.1109/TPDS.2006.128,
author = {Jen-Yeu Chen and Gopal Pandurangan and Dongyan Xu},
title = {Robust Computation of Aggregates in Wireless Sensor Networks: Distributed Randomized Algorithms and Analysis},
journal ={IEEE Transactions on Parallel and Distributed Systems},
volume = {17},
number = {9},
issn = {1045-9219},
year = {2006},
pages = {987-1000},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPDS.2006.128},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Parallel and Distributed Systems
TI - Robust Computation of Aggregates in Wireless Sensor Networks: Distributed Randomized Algorithms and Analysis
IS - 9
SN - 1045-9219
SP987
EP1000
EPD - 987-1000
A1 - Jen-Yeu Chen,
A1 - Gopal Pandurangan,
A1 - Dongyan Xu,
PY - 2006
KW - Probabilistic algorithms
KW - randomized algorithms
KW - distributed algorithms
KW - sensor networks
KW - fault tolerance
KW - graph theory
KW - aggregate
KW - data query
KW - stochastic processes.
VL - 17
JA - IEEE Transactions on Parallel and Distributed Systems
ER -
 

Abstract—A wireless sensor network consists of a large number of small, resource-constrained devices and usually operates in hostile environments that are prone to link and node failures. Computing aggregates such as average, minimum, maximum and sum is fundamental to various primitive functions of a sensor network, such as system monitoring, data querying, and collaborative information processing. In this paper, we present and analyze a suite of randomized distributed algorithms to efficiently and robustly compute aggregates. Our Distributed Random Grouping (DRG) algorithm is simple and natural and uses probabilistic grouping to progressively converge to the aggregate value. DRG is local and randomized and is naturally robust against dynamic topology changes from link/node failures. Although our algorithm is natural and simple, it is nontrivial to show that it converges to the correct aggregate value and to bound the time needed for convergence. Our analysis uses the eigenstructure of the underlying graph in a novel way to show convergence and to bound the running time of our algorithms. We also present simulation results of our algorithm and compare its performance to various other known distributed algorithms. Simulations show that DRG needs far fewer transmissions than other distributed localized schemes.

[1] F. Bauer and A. Varma, “Distributed Algorithms for Multicast Path Setup in Data Networks,” IEEE/ACM Trans. Networking, vol. 4, no. 2, pp. 181-191, Apr. 1996.
[2] M. Bawa, H. Garcia-Molina, A. Gionis, and R. Motwani, “Estimating Aggregates on a Peer-to-Peer Network,” technical report, Computer Science Dept., Stanford Univ., 2003.
[3] A. Boulis, S. Ganeriwal, and M.B. Srivastava, “Aggregation in Sensor Networks: An Energy-Accuracy Trade-Off,” Proc. First IEEE Int'l Workshop Sensor Network Protocols and Applications (SNPA), May 2003.
[4] S. Boyd, A. Ghosh, B. Prabhakar, and D. Shah, “Gossip Algorithms: Design, Analysis, and Applications,” Proc. IEEE Infocom, 2005.
[5] J.-Y. Chen, G. Pandurangan, and D. Xu, “Robust and Distributed Computation of Aggregates in Wireless Sensor Networks,” technical report, Computer Science Dept, Purdue Univ., 2004. A preliminary version of this paper appeared in Proc. Fourth Int'l Symp. Information Processing in Sensor Networks (IPSN), 2005.
[6] C. Ching and S.P. Kumar, “Sensor Networks: Evolution, Opportunities, and Challanges,” invited paper, Proc. IEEE, vol. 91, no. 8, Aug. 2003.
[7] D.M. Cvetković, M. Doob, and H. Sachs, Spectra of Graphs, Theory and Application. Academic Press, 1980.
[8] J. Elson and D. Estrin, “Time Synchronization for Wireless Sensor Networks,” Proc. IEEE Int'l Parallel and Distributed Processing Symp. (IPDPS), Apr. 2001.
[9] M. Enachescu, A. Goel, R. Govindan, and R. Motwani, “Scale Free Aggregation in Sensor Networks,” Proc. Algorithmic Aspects Wireless Sensor Networks: First Int'l Workshop (ALGOSENSORS), 2004.
[10] D. Estrin, R. Govindan, J.S. Heidemann, and S. Kumar, “Next Century Challenges: Scalable Coordination in Sensor Networks,” Proc. ACM Int'l Conf. Mobile Computing and Networking (MobiCom), 1999.
[11] M. Fiedler, “Algebraic Connectivity of Graphs,” Czechoslovak Math. J., vol. 23, pp. 298-305, 1973.
[12] B. Ghosh and S. Muthukrishnan, “Dynamic Load Balancing by Random Matchings,” J. Computer and System Science, vol. 53, no. 3, pp. 357-370, 1996.
[13] J. Gray, S. Chaudhuri, A. Bosworth, A. Layman, D. Reichart, M. Venkatrao, F. Pellow, and H. Pirahesh, “Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals,” J. Data Mining and Knowledge Discovery, pp. 29-53, 1997.
[14] P. Gupta and P.R. Kumar, “Critical Power for Asymptotic Connectivity in Wireless Networks,” Stochastic Analysis, Control, Optimization and Applications: A Volume in Honor of W. H. Fleming, W. M. McEneaney, G. Yin, and Q. Zhang, eds. Boston: Birkhauser, 1998.
[15] J. Heidemann, F. Silva, C. Intanagonwiwat, R. Govindan, D. Estrin, and D. Ganesan, “Building Efficient Wireless Sensor Networks with Low-Level Naming,” Proc. 18th ACM Symp. Operating Systems Principles (SOSP), 2001.
[16] J.M. Hellerstein, P.J. Haas, and H.J. Wang, “Online Aggregation,” Proc. ACM SIGMOD Int'l Conf. Management of Data (SIGMOD), May 1997.
[17] E. Hung and F. Zhao, “Diagnostic Information Processing for Sensor-Rich Distributed Systems,” Proc. Second Int'l Conf. Information Fusion, 1999.
[18] D. Kempe, A. Dobra, and J. Gehrke, “Gossip-Based Computation of Aggregate Information,” Proc. 44th Ann. IEEE Symp. Foundations Computer Science (FOCS), 2003.
[19] B. Krishnamachari, D. Estrin, and S. Wicker, “Impact of Data Aggregation in Wireless Sensor Networks,” Proc. Int'l Workshop Distributed Event-Based Systems (DEBS), 2002.
[20] D. Liu and M. Prabhakaran, “On Randomized Broadcasting and Gossiping in Radio Networks,” Proc. Eighth Ann. Int'l Computing and Combinatorics Conf. (COCOON), Aug. 2002.
[21] S. Madden, M Franklin, J. Hellerstein, and W. Hong, “TAG: A Tiny Aggregation Service for Ad Hoc Sensor Network,” Proc. Fifth Symp. Operating Systems Design and Implementation (USENIX OSDI), 2002.
[22] S.R. Madden, R. Szewczyk, M.J. Franklin, and D. Culler, “Supporting Aggregate Queries over Ad-Hoc Wireless Sensor Networks,” Proc. Fourth IEEE Workshop Mobile Computing Systems and Applications (WMCSA), 2002.
[23] R. Merris, “Laplacian Matrices of Graphs: A Survey,” Linear Algebra and its Applications, vols. 197-198, pp. 143-176, 1994.
[24] R. Motwani and P. Raghavan, Randomized Algorithms. Cambridge Univ. Press, 1995.
[25] S. Nath, P.B. Gibbons, Z. Anderson, and S. Seshan, “Synopsis Diffusion for Robust Aggregation in Sensor Networks,” Proc. ACM Conf. Embedded Networked Sensor Systems (SenSys), 2004.
[26] R. Olfati-Saber, “Flocking for Multi-Agent Dynamic Systems: Algorithms and Theory,” Technical Report CIT-CDS 2004-005, 2004.
[27] M. Penrose, Random Geometric Graphs. Oxford Univ. Press, 2003.
[28] H. Qi, S.S. Iyengar, and K. Chakrabarty, “Multiresolution Data Integration Using Mobile Agents in Distributed Sensor Networks,” IEEE Trans. Systems, Man, and Cybernetics C, vol. 31, no. 3, pp. 383-391, Aug. 2001.
[29] D. Scherber and B. Papadopoulos, “Locally Constructed Algorithms for Distributed Computations in Ad-Hoc Networks,” Proc. Conf. Information Processing in Sensor Networks (IPSN), 2004.
[30] N. Shrivastava, C. Buragohain, D. Agrawal, and S. Suri, “Medians and Beyond: New Aggregation Techniques for Sensor Networks,” Proc. ACM Conf. Embedded Networked Sensor Systems (SenSys), 2004.

Index Terms:
Probabilistic algorithms, randomized algorithms, distributed algorithms, sensor networks, fault tolerance, graph theory, aggregate, data query, stochastic processes.
Citation:
Jen-Yeu Chen, Gopal Pandurangan, Dongyan Xu, "Robust Computation of Aggregates in Wireless Sensor Networks: Distributed Randomized Algorithms and Analysis," IEEE Transactions on Parallel and Distributed Systems, vol. 17, no. 9, pp. 987-1000, Sept. 2006, doi:10.1109/TPDS.2006.128
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