Constructing data gathering tree to maximize the lifetime of unreliable Wireless Sensor Network under delay constraint

In a Wireless Sensor Network (WSN), energy saving is a key issue for prolonging its runtime. Usually, a real-time application of WSN requires that data be collected within a delay constraint. There exists a tradeoff between energy saving and delay satisfaction. In this paper, a Tree-based Energy and Delay Aware Scheme (TEDAS) is proposed, which is able to maximize the lifetime of WSN while delay bound is satisfied. Based on Expected Transmission Count (ETX) of link, the TEDAS initially creates the Minimum ETX Spanning Tree (MEST) of the WSN and then the MEST is gradually improved by the proposed Adjusting Tree Algorithm (ATA) so that the optimal data gathering tree is obtained. In addition, the lifetime optimization problem (LOP) is developed for the ATA to maximize network lifetime. Moreover, the complexity of the ATA is O(N3), where N is the number of the nodes in the WSN. Simulation results show that the proposed TEDAS outperforms some existing schemes in terms of network lifetime and the volume of valid data.

[1]  Wendi Heinzelman,et al.  Energy-efficient communication protocol for wireless microsensor networks , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[2]  Guihai Chen,et al.  Maximizing lifetime for the shortest path aggregation tree in wireless sensor networks , 2011, 2011 Proceedings IEEE INFOCOM.

[3]  V.W.S. Wong,et al.  An energy-aware spanning tree algorithm for data aggregation in wireless sensor networks , 2005, PACRIM. 2005 IEEE Pacific Rim Conference on Communications, Computers and signal Processing, 2005..

[4]  Christos Douligeris,et al.  Energy efficiency in wireless sensor networks using sleep mode TDMA scheduling , 2009, Ad Hoc Networks.

[5]  Deborah Estrin,et al.  Statistical model of lossy links in wireless sensor networks , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[6]  Yi-hua Zhu,et al.  An energy-efficient data gathering algorithm to prolong lifetime of wireless sensor networks , 2010, Comput. Commun..

[7]  Ness B. Shroff,et al.  Maximizing aggregated revenue in sensor networks under deadline constraints , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

[8]  Hongwei Zhang,et al.  Reliable bursty convergecast in wireless sensor networks , 2007, Comput. Commun..

[9]  Ness B. Shroff,et al.  On optimal energy efficient convergecasting in unreliable sensor networks with applications to target tracking , 2011, MobiHoc '11.

[10]  Hongwei Zhang,et al.  Reliable bursty convergecast in wireless sensor networks , 2005, MobiHoc '05.

[11]  Andreas Terzis,et al.  RACNet: a high-fidelity data center sensing network , 2009, SenSys '09.

[12]  Victor C. M. Leung,et al.  Energy-efficient Tree-based Message Ferrying Routing Schemes for Wireless Sensor Networks , 2008, 2008 Third International Conference on Communications and Networking in China.

[13]  Hongwei Zhang,et al.  On exploiting asymmetric wireless links via one-way estimation , 2007, MobiHoc '07.

[14]  Marco Zuniga,et al.  Analyzing the transitional region in low power wireless links , 2004, 2004 First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2004. IEEE SECON 2004..

[15]  Ibrahim Korpeoglu,et al.  Power efficient data gathering and aggregation in wireless sensor networks , 2003, SGMD.

[16]  Ness B. Shroff,et al.  On the Construction of a Maximum-Lifetime Data Gathering Tree in Sensor Networks: NP-Completeness and Approximation Algorithm , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[17]  Edward W. Knightly,et al.  Denial of service resilience in ad hoc networks , 2004, MobiCom '04.