Abstract
A sensor network consists of sensing devices which may exchange data through wireless communication; sensor networks are highly energy constrained since they are usually battery operated. Data aggregation is a possible way to save energy consumption: nodes may delay data in order to aggregate them into a single packet before forwarding them towards some central node (sink). However, many applications impose constraints on data freshness; this translates into latency constraints for data arriving at the sink.
We study the problem of data aggregation to minimize maximum energy consumption under latency constraints on sensed data delivery and we assume unique transmission paths that form a tree rooted at the sink. We prove that the off-line problem is strongly NP-hard and we design a 2-approximation algorithm. The latter uses a novel rounding technique.
Almost all real life sensor networks are managed on-line by simple distributed algorithms in the nodes. In this context we consider both the case in which sensor nodes are synchronized or not. We consider distributed on-line algorithms and use competitive analysis to assess their performance.
Supported by EU Integrated Project AEOLUS (FET-15964), EU project ADONET (MRTN-CT-2003-504438), EU COST-action 293, MIUR-FIRB project VICOM, Dutch project BRICKS, DFG Focus Program 1126, “Algorithmic Aspects of Large and Complex Networks”, grant SK 58/5-3, MIUR-FIRB Israel-Italy project RBIN047MH9.
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
Akyildiz, I., Su, W., Sanakarasubramaniam, Y., Cayirci, E.: Wireless sensor networks: A survey. Computer Networks Journal 38(4), 393–422 (2002)
Becchetti, L., Korteweg, P., Marchetti-Spaccamela, A., Skutella, M., Stougie, L., Vitaletti, A.: Latency Constrained Aggregation in Sensor Networks. SPOR-report 2006-08, TU Eindhoven (2006), http://www.win.tue.nl/bs/spor
Boulis, A., Ganeriwal, S., Srivastava, M.B.: Aggregation in sensor networks: an energy - accuracy tradeoff. Ad-hoc Networks Journal 1(2-3), 317–331 (2003)
Brito, C., Koutsoupias, E., Vaya, S.: Competitive analysis of organization networks or multicast acknowledgement: how much to wait? In: Proceedings of the Fifteenth Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 627–635 (2004)
Broder, A.Z., Mitzenmacher, M.: Optimal plans for aggregation. In: PODC, pp. 144–152 (2002)
Goel, A., Estrin, D.: Simultaneous optimization for concave costs: single sink aggregation or single source buy-at-bulk. In: Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 499–505 (2003)
Heinzelman, W., Chandrakasan, A., Balakrishnan, H.: Energy efficient communication protocols for wireless microsensor networks. In: Proceedings of Hawaiian International Conference on Systems Science, pp. 3005–3014 (2000)
Hu, F., Cao, X., May, C.: Optimized scheduling for data aggregation in wireless sensor networks. In: International Conference on Information Technology Coding and Computing (ITCC), pp. 557–561 (2005)
Intanagonwiwat, C., Estrin, D., Govindan, R., Heidemann, J.: Impact of network density on data aggregation in wireless sensor networks. In: Proceedings of the 22nd International Conference on Distributed Computing Systems (ICDCS), pp. 414–458 (2002)
Intanagonwiwat, C., Govindan, R., Estrin, D.: Directed diffusion: a scalable and robust communication paradigm for sensor networks. In: Mobile Computing and Networking, pp. 56–67 (2000)
Kalpakis, K., Dasgupta, K., Namjoshi, P.: Efficient algorithms for maximum lifetime data gathering and aggregation in wireless sensor networks. Computer Networks 42(6), 697–716 (2003)
Lindsey, S., Raghavendra, C.S.: Pegasis: Power-efficient gathering in sensor information systems. In: Proceedings of IEEE Aerospace Conference, pp. 1125–1130 (2000)
Madden, S., Franklin, M.J., Hellerstein, J.M., Hong, W.: Tag: A tiny aggregation service for ad-hoc sensor networks. In: Proceedings of the 5th ACM Symposium on Operating System Design and Implementation (OSDI), pp. 131–146 (2002)
Madden, S., Franklin, M.J., Hellerstein, J.M., Hong, W.: Tinydb: an acquisitional query processing system for sensor networks. ACM Transactions on Database Systems (TODS) 30(1), 122–173 (2005)
Yuan, W., Krishnamurthy, V.S., Tripathi, S.K.: Synchronization of multiple levels of data fusion in wireless sensor networks. In: Proceedings of IEEE Globecom, pp. 221–225 (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Becchetti, L., Korteweg, P., Marchetti-Spaccamela, A., Skutella, M., Stougie, L., Vitaletti, A. (2006). Latency Constrained Aggregation in Sensor Networks. In: Azar, Y., Erlebach, T. (eds) Algorithms – ESA 2006. ESA 2006. Lecture Notes in Computer Science, vol 4168. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11841036_11
Download citation
DOI: https://doi.org/10.1007/11841036_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-38875-3
Online ISBN: 978-3-540-38876-0
eBook Packages: Computer ScienceComputer Science (R0)