Data Aggregation, Spatio-Temporal Correlation and Energy-Aware Solutions to Perform Data Collection in Wireless Sensor Networks
Abstract
This work discusses different approaches for data aggregation and spatio-temporal data correlation in Wireless Sensor Networks (WSNs). In the thesis, we investigate and propose solutions that are suitable for many different scenarios in WSNs. The proposed algorithms reduce the number of messages necessary to set up a routing tree, maximize the number of overlapping routes, select routes with the highest aggregation rate, and perform reliable data aggregation transmission. Moreover, our algorithms have been extensively compared with the ones available in the literature and the results show that they are potential alternatives to perform data aggregation and spatio-temporal data correlation during the routing process in WSNs. This thesis resulted in 4 journal papers and 18 conference papers.References
Chakrabarty, K., Member, S., Iyengar, S. S., Qi, H., and Cho, E. (2002). Grid coverage for surveillance and target location in distributed sensor networks. IEEE Transactions on Computers, 51:1448–1453.
Deligiannakis, A. and Kotidis, Y. (2008). Geosensor networks. In Nittel, S., Labrinidis, A., and Stefanidis, A., editors, Book chapter: Exploiting Spatio-temporal Correlations for Data Processing in Sensor Networks, pages 45–65. Springer-Verlag.
Le, T. D., Pham, N. D., and Choo, H. (2008). Towards a distributed clustering scheme based on spatial correlation in wsns. In Wireless Communications and Mobile Computing Conference, 2008. IWCMC ’08. International, pages 529 –534.
Liu, L., Member, S., and Yu, P. S. (2007). Asap: An adaptive sampling approach to data collection in sensor networks. IEEE Transactions on Parallel and Distributed Systems, 2007:1766–1783.
Min, J.-K. and Chung, C.-W. (2010). Edges: Efficient data gathering in sensor networks using temporal and spatial correlations. J. Syst. Softw., 83:271–282.
Pham, N. D., Le, T. D., Park, K., and Choo, H. (2010). Sccs: Spatiotemporal clustering and compressing schemes for efficient data collection applications in wsns. International Journal of Communication Systems, 23:1311–1333.
Schmid, U. and Schossmaier, K. (2001). How to reconcile fault-tolerant interval intersection with the lipschitz condition. Distrib. Comput., 14:101–111.
Villas, L., Boukerche, A., Ramos Filho, H., Oliveira, H., Araujo, R., and Loureiro, A. (2012a). Drina: A lightweight and reliable routing approach for innetwork aggregation in wireless sensor networks. Computers, IEEE Transactions on, PP(99):1.
Villas, L. A., Boukerche, A., Araujo, R. B., and Loureiro, A. A. (2012b). Data Aggregation, Spatio-Temporal Correlation and Energy-Aware Solutions to perform Data Collection in Wireless Sensor Networks. PhD thesis, Federal University of Minas Gerais, [link].
Villas, L. A., Boukerche, A., de Oliveira, H. A., de Araujo, R. B., and Loureiro, A. A. (2011). A spatial correlation aware algorithm to perform efficient data collection in wireless sensor networks. Ad Hoc Networks.
Deligiannakis, A. and Kotidis, Y. (2008). Geosensor networks. In Nittel, S., Labrinidis, A., and Stefanidis, A., editors, Book chapter: Exploiting Spatio-temporal Correlations for Data Processing in Sensor Networks, pages 45–65. Springer-Verlag.
Le, T. D., Pham, N. D., and Choo, H. (2008). Towards a distributed clustering scheme based on spatial correlation in wsns. In Wireless Communications and Mobile Computing Conference, 2008. IWCMC ’08. International, pages 529 –534.
Liu, L., Member, S., and Yu, P. S. (2007). Asap: An adaptive sampling approach to data collection in sensor networks. IEEE Transactions on Parallel and Distributed Systems, 2007:1766–1783.
Min, J.-K. and Chung, C.-W. (2010). Edges: Efficient data gathering in sensor networks using temporal and spatial correlations. J. Syst. Softw., 83:271–282.
Pham, N. D., Le, T. D., Park, K., and Choo, H. (2010). Sccs: Spatiotemporal clustering and compressing schemes for efficient data collection applications in wsns. International Journal of Communication Systems, 23:1311–1333.
Schmid, U. and Schossmaier, K. (2001). How to reconcile fault-tolerant interval intersection with the lipschitz condition. Distrib. Comput., 14:101–111.
Villas, L., Boukerche, A., Ramos Filho, H., Oliveira, H., Araujo, R., and Loureiro, A. (2012a). Drina: A lightweight and reliable routing approach for innetwork aggregation in wireless sensor networks. Computers, IEEE Transactions on, PP(99):1.
Villas, L. A., Boukerche, A., Araujo, R. B., and Loureiro, A. A. (2012b). Data Aggregation, Spatio-Temporal Correlation and Energy-Aware Solutions to perform Data Collection in Wireless Sensor Networks. PhD thesis, Federal University of Minas Gerais, [link].
Villas, L. A., Boukerche, A., de Oliveira, H. A., de Araujo, R. B., and Loureiro, A. A. (2011). A spatial correlation aware algorithm to perform efficient data collection in wireless sensor networks. Ad Hoc Networks.
Published
2013-07-23
How to Cite
VILLAS, Leandro A.; ARAUJO, Regina B. de; LOUREIRO, Antonio A. F..
Data Aggregation, Spatio-Temporal Correlation and Energy-Aware Solutions to Perform Data Collection in Wireless Sensor Networks. In: THESIS AND DISSERTATION CONTEST (CTD), 26. , 2013, Maceió/AL.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2013
.
p. 23-28.
ISSN 2763-8820.
