22 Energy-Efficient Data Gathering in Wireless Sensor Networks with Asynchronous Sampling JING WANG, YONGHE LIU, and SAJAL K. DAS The University of Texas at Arlington A low sampling rate leads to reduced congestion and hence energy consumption in the resource- constrained wireless sensor networks. In this article, we propose asynchronous sampling that shifts the sampling time instances of sensor nodes from each other. For lossy data gathering scenarios, the proposed approach provides more information about the physical phenomena in terms of increased entropy at a low sampling rate. For lossless data gathering scenarios, on the other hand, the sampling rate is lowered without sacrificing critical knowledge required for signal reconstruction. As lower sampling rates lead to smaller energy consumption for processing and transmitting the collected sensory data, the proposed asynchronous sampling strategies are capable of achieving a better trade-off between the lifetime of the network and the quality of collected information. In addition to mathematical analysis, simulation results based on real data also verify the benefits of our asynchronous sampling. Categories and Subject Descriptors: C.2.4 [Computer-Communications Networks]: Distributed Systems—Distributed applications General Terms: Algorithms Additional Key Words and Phrases: Models, asynchronous sampling, temporal-spatial correlation, energy efficiency, data gathering, wireless sensor networks ACM Reference Format: Wang, J., Liu, Y., and Das, S. K. 2010. Energy-Efficient data gathering in wireless sensor networks with asynchronous sampling. ACM Trans. Sensor Netw. 6, 3, Article 22 (June 2010), 37 pages. DOI = 10.1145/1754414.1754418 http://doi.acm.org/10.1145/1754414.1754418 This work was in part presented in IEEE WCNC 2007 and INFOCOM 2008. This work is partially supported by NSF grants CNS-0721951 and IIS-0326505, AFOSR grant FA9550-08-1-0260, and Texas ARP grant No. 14-748779. The work of S. K. Das is also supported by (while serving at) the National Science Foundation. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. Authors’ addresses: J. Wang(corresponding author), Y. Liu and S. K. Das, Center for Research in Wireless Mobility and Networking (CReWMaN), Department of Computer Science and Engineer- ing, The University of Texas at Arlington, Arlington, TX; email: jingwang@uta.edu. Permission to make digital or hard copies of part or all 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 show this notice on the first page or initial screen of a display along with the full citation. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of this work in other works requires prior specific permission and/or a fee. Permissions may be requested from Publications Dept., ACM, Inc., 2 Penn Plaza, Suite 701, New York, NY 10121-0701 USA, fax +1 (212) 869-0481, or permissions@acm.org. C  2010 ACM 1550-4859/2010/06-ART22 $10.00 DOI 10.1145/1754414.1754418 http://doi.acm.org/10.1145/1754414.1754418 ACM Transactions on Sensor Networks, Vol. 6, No. 3, Article 22, Publication date: June 2010.