Abstract
Energy-efficient wireless networks are essential to reduce the effect of global warming and to minimize the operational costs of future networks. In this paper we investigate approaches exploiting spatial correlations that offer a high potential to significantly decrease the total energy consumption thus enabling “green” wireless networks. In particular, we analyze the impact of distributed compression and optimized node deployments on the energy-efficiency of networks. Furthermore, we present results on the operational lifetime of networks which is often a major performance criterion from applications’ perspective.
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.
Similar content being viewed by others
References
Hansen, J., Sato, M., Kharecha, P., Russell, G., Lea, D., Siddal, M.: Climate change and Trace gases. Philosophical Transactions of Royal Society 365, 1925–1954 (2007)
McKinsey: The Impact of ICT on Global Emissions. Technical report, Note: on behalf of United Nations Environment Management Group (2007)
Fehske, A., Richter, F., Fettweis, G.P.: Energy Efficiency Improvements through Micro Sites in Cellular Mobile Radio Networks. In: Proceedings of Int. Workshop on Green Communications, in conjunction with GLOBECOM, Honolulu, USA, pp. 1–5 (2009)
Oldewurtel, F., Foks, M., Mähönen, P.: On a Practical Distributed Source Coding Scheme for Wireless Sensor Networks. In: Proceedings of the IEEE Vehicular Technology Conference (VTC spring), Marina Bay, Singapore, pp. 228–232 (2008)
Oldewurtel, F., Riihijärvi, J., Mähönen, P.: Efficiency of Distributed Compression and its Dependence on Sensor Node Deployments. In: Proceedings of the IEEE Vehicular Technology Conference (VTC spring), Taipei, Taiwan, pp. 1–5 (2010)
Baek, S.J., de Veciana, G., Su, X.: Minimizing Energy Consumption in Large-scale Sensor Networks through Distributed Data Compression and Hierarchical Aggregation. IEEE Journal on Selected Areas in Communications 22(6), 1130–1140 (2004)
Cristescu, R., Beferull-Lozano, B., Vetterli, M.: On Network Correlated Data Gathering. In: Proceedings of the INFOCOM, Hong Kong, pp. 2571–2582 (2004)
Oldewurtel, F., Mähönen, P.: Efficiency Analysis and Derivation of Enhanced Deployment Models for Sensor Networks. In: International Journal of Ad Hoc and Ubiquitous Computing, IJAHUC (2010) (note: accepted)
Oldewurtel, F., Mähönen, P.: Analysis of Enhanced Deployment Models for Sensor Networks. In: Proceedings of the IEEE Vehicular Technology Conference (VTC spring), Taipei, Taiwan, pp. 1–5 (2010)
Yang, S., Li, M., Wu, J.: Scan-Based Movement-Assisted Sensor Deployment Methods in Wireless Sensor Networks. IEEE Transactions on Parallel and Distributed Systems 18(8), 1108–1121 (2007)
Ganesan, D., Cristescu, R., Beferull-Lozano, B.: Power-efficient Sensor Placement and Transmission Structure for Data Gathering under Distortion Constraints. ACM Transactions on Sensor Networks (TOSN) 2(2), 155–181 (2006)
Pattem, S., Krishnamachari, B., Govindan, R.: The Impact of Spatial Correlation on Routing with Compression in Wireless Sensor Networks. ACM Transactions on Sensor Networks (TOSN) 4(4), 1–33 (2008)
Chou, J., Petrovic, D., Ramchandran, K.: Tracking and Exploiting Correlations in Dense Sensor Networks. In: Proceedings of the Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, USA, pp. 39–43 (2002)
Cover, T.M., Thomas, J.A.: Elements of Information Theory. Wiley, USA (2006)
Slepian, D., Wolf, J.: Noiseless Coding of Correlated Information Sources. IEEE Transactions on Information Theory 19(4), 471–480 (1973)
Xiong, Z., Liveris, A.D., Cheng, S.: Distributed Source Coding for Sensor Networks. IEEE Signal Processing 21(5), 80–94 (2004)
Jindal, A., Psounis, K.: Modeling Spatially Correlated Data in Sensor Networks. ACM Transactions on Sensor Networks (TOSN) 2(4), 466–499 (2006)
Stoyan, D., Kendall, W.S., Mecke, J.: Stochastic Geometry and its Applications. Wiley, USA (1995)
Thomas, M.: A Generalization of Poisson’s Binomial Limit for Use in Ecology. Biometrika 36, 18–25 (1949)
Gilbert, E.N.: Capacity of a Bursty-Noise Channel. Bell Systems Technical Journal 39(9), 1253–1265 (1960)
Ebert, J.-P., Willig, A., Wolisz, A.: A Gilbert-Elliot Bit Error Model and the Efficient Use in Packet Level Simulation. TKN technical report TKN-99-002 (1999)
Fasolo, E., Rossi, M., Widmer, J., Zorzi, M.: In-network Aggregation Techniques for Wireless Sensor Networks: a survey. IEEE Wireless Communications 14(2), 70–87 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Oldewurtel, F., Mähönen, P. (2012). Green Wireless Networks through Exploitation of Correlations. In: Tomkos, I., Bouras, C.J., Ellinas, G., Demestichas, P., Sinha, P. (eds) Broadband Communications, Networks, and Systems. BROADNETS 2010. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 66. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30376-0_38
Download citation
DOI: https://doi.org/10.1007/978-3-642-30376-0_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-30375-3
Online ISBN: 978-3-642-30376-0
eBook Packages: Computer ScienceComputer Science (R0)