This Article 
 Bibliographic References 
 Add to: 
On Maximizing the Lifetime of Wireless Sensor Networks Using Virtual Backbone Scheduling
Aug. 2012 (vol. 23 no. 8)
pp. 1528-1535
Yaxiong Zhao, Temple University, Philadelphia
Jie Wu, Temple University, Philadelphia
Feng Li, Indiana University-Purdue University Indianapolis, Indianapolis
Sanglu Lu, Nanjing University, Nanjing
Wireless Sensor Networks (WSNs) are key for various applications that involve long-term and low-cost monitoring and actuating. In these applications, sensor nodes use batteries as the sole energy source. Therefore, energy efficiency becomes critical. We observe that many WSN applications require redundant sensor nodes to achieve fault tolerance and Quality of Service (QoS) of the sensing. However, the same redundancy may not be necessary for multihop communication because of the light traffic load and the stable wireless links. In this paper, we present a novel sleep-scheduling technique called Virtual Backbone Scheduling (VBS). VBS is designed for WSNs has redundant sensor nodes. VBS forms multiple overlapped backbones which work alternatively to prolong the network lifetime. In VBS, traffic is only forwarded by backbone sensor nodes, and the rest of the sensor nodes turn off their radios to save energy. The rotation of multiple backbones makes sure that the energy consumption of all sensor nodes is balanced, which fully utilizes the energy and achieves a longer network lifetime compared to the existing techniques. The scheduling problem of VBS is formulated as the Maximum Lifetime Backbone Scheduling (MLBS) problem. Since the MLBS problem is NP-hard, we propose approximation algorithms based on the Schedule Transition Graph (STG) and Virtual Scheduling Graph (VSG). We also present an Iterative Local Replacement (ILR) scheme as a distributed implementation. Theoretical analyses and simulation studies verify that VBS is superior to the existing techniques.

[1] V. Shnayder, M. Hempstead, B.-r. Chen, G.W. Allen, and M. Welsh, "Simulating the Power Consumption of Large-Scale Sensor Network Applications," Proc. Second Int'l Conf. Embedded Networked Sensor Systems (SenSys '04), pp. 188-200, 2004.
[2] C. Misra and R. Mandal, "Rotation of CDS via Connected Domatic Partition in Ad Hoc Sensor Networks," IEEE Trans. Mobile Computing, vol. 8, no. 4, pp. 488-499, Apr. 2009.
[3] W. Ye, J. Heidemann, and D. Estrin, "An Energy-Efficient MAC Protocol for Wireless Sensor Networks," Proc. IEEE INFOCOM, pp. 1567-1576, 2002.
[4] Q. Cao, T. Abdelzaher, T. He, and J. Stankovic, "Towards Optimal Sleep Scheduling in Sensor Networks for Rare-Event Detection," Proc. ACM Fourth Int'l Symp. Information Processing in Sensor Networks (IPSN '05), pp. 20-27, 2005.
[5] A. Keshavarzian, H. Lee, and L. Venkatraman, "Wakeup Scheduling in Wireless Sensor Networks," Proc. Seventh ACM Int'l Symp. Mobile Ad Hoc Networking and Computing (MobiHoc '06), pp. 322-333, 2006.
[6] R. Cohen and B. Kapchits, "An Optimal Wake-Up Scheduling Algorithm for Minimizing Energy Consumption while Limiting Maximum Delay in a Mesh Sensor Network," IEEE/ACM Trans. Networking, vol. 17, no. 2, pp. 570-581, Apr. 2009.
[7] Y. Li, W. Ye, and J. Heidemann, "Energy and Latency Control in Low Duty Cycle MAC Protocols," Proc. IEEE Wireless Comm. and Networking Conf. (WCNC '05), pp. 676-682, 2005.
[8] J.W. Hui and D.E. Culler, "IP is Dead, Long Live IP for Wireless Sensor Networks," Proc. Sixth ACM Conf. Embedded Network Sensor Systems (SenSys '08), pp. 15-28, 2008.
[9] L. Doherty, W. Lindsay, and J. Simon, "Channel-Specific Wireless Sensor Network Path Data," Proc. Int'l Conf. Computer Comm. and Networks (ICCCN '07), pp. 89-94, 2007.
[10] F. Dai and J. Wu, "An Extended Localized Algorithm for Connected Dominating Set Formation in Ad Hoc Wireless Networks," IEEE Trans. Parallel Distributed Systems, vol. 15, no. 10, pp. 908-920, Oct. 2004.
[11] "Wireless Routing Simulation Suite," projectswrss/, 2012.
[12] F. Dai and J. Wu, "On Constructing K-Connected K-Dominating Set in Wireless Ad Hoc and Sensor Networks," J. Parallel Distributed Computing, vol. 66, no. 7, pp. 947-958, 2006.
[13] B.N. Clark, C.J. Colbourn, and D.S. Johnson, "Unit Disk Graphs," Discrete Math., vol. 86, nos. 1-3, pp. 165-177, 1990.

Index Terms:
Wireless sensor networks (WSNs), backbone scheduling, sleep scheduling, virtual backbone, energy-delay tradeoff, connected dominating set, complexity analysis.
Yaxiong Zhao, Jie Wu, Feng Li, Sanglu Lu, "On Maximizing the Lifetime of Wireless Sensor Networks Using Virtual Backbone Scheduling," IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 8, pp. 1528-1535, Aug. 2012, doi:10.1109/TPDS.2011.305
Usage of this product signifies your acceptance of the Terms of Use.