Energy Efficiency of Centralized and Distributed Computation in Unattended Multi-Hop Wireless Sensor Networks for Battlefield Monitoring

The energy efficiency trade-offs available between centralized and distributed solutions in unattended wireless sensor network deployments such as those that support remote battlefield monitoring remain an open research question. In this paper, we compare the relative energy efficiency of these two approaches in multi-hop wireless sensor networks. We develop a framework that includes both total and per node energy efficiency expressions and apply it to the beamforming class of unattended battlefield monitoring solutions using Mica2, MicaZ and the latest generation Telos sensor motes. A performance threshold is shown to exist between these approaches which can be exploited through the use of preamble sampling.

[1]  John C. McEachen,et al.  A Method for Emphasizing Signal Detection in Wireless Sensor Network Radio Frequency Array Operation , 2009, 2009 42nd Hawaii International Conference on System Sciences.

[2]  David E. Culler,et al.  Telos: enabling ultra-low power wireless research , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[3]  Raghuraman Mudumbai,et al.  On the Feasibility of Distributed Beamforming in Wireless Networks , 2007, IEEE Transactions on Wireless Communications.

[4]  Gene H. Golub,et al.  Matrix computations , 1983 .

[5]  Kung Yao,et al.  Source localization and beamforming , 2002, IEEE Signal Process. Mag..

[6]  H. Vincent Poor,et al.  Collaborative beamforming for distributed wireless ad hoc sensor networks , 2005, IEEE Transactions on Signal Processing.

[7]  John C. McEachen,et al.  Connectivity in Sensor Networks , 2007, 2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07).

[8]  Dragos Niculescu.  Communication paradigms for sensor networks , 2005, IEEE Communications Magazine.

[9]  Sayandev Mukherjee,et al.  Connectivity and Transmit-Energy Considerations Between Any Pair of Nodes in a Wireless Ad Hoc Network Subject to Fading , 2008, IEEE Transactions on Vehicular Technology.

[10]  M. Tummala,et al.  A Distributed Approach to Beamforming in a Wireless Sensor Network , 2007, 2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers.

[11]  J. Eberspacher,et al.  Hop distances in homogeneous ad hoc networks , 2003, The 57th IEEE Semiannual Vehicular Technology Conference, 2003. VTC 2003-Spring..

[12]  Dimitrios D. Vergados,et al.  A survey on power control issues in wireless sensor networks , 2007, IEEE Communications Surveys & Tutorials.

[13]  G.B. Giannakis,et al.  Distributed compression-estimation using wireless sensor networks , 2006, IEEE Signal Processing Magazine.

[14]  M. Tummala,et al.  An energy-efficient and distributed approach to beamforming in a wireless sensor network , 2008, 2008 42nd Asilomar Conference on Signals, Systems and Computers.

[15]  Amre El-Hoiydi,et al.  Aloha with preamble sampling for sporadic traffic in ad hoc wireless sensor networks , 2002, 2002 IEEE International Conference on Communications. Conference Proceedings. ICC 2002 (Cat. No.02CH37333).

[16]  John C. McEachen,et al.  A new method for distributing power usage across a sensor network , 2008, Ad Hoc Networks.

[17]  John W. Auer,et al.  Linear algebra with applications , 1996 .

[18]  M. Tummala,et al.  Distributed Beamforming in Wireless Sensor Networks , 2005, Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005..

[19]  John C. McEachen,et al.  Distributed Medium Access Control with Flow-Based Priority for Cooperative Multi-hop Wireless Sensor Networks , 2008, Proceedings of the 41st Annual Hawaii International Conference on System Sciences (HICSS 2008).

[20]  A.S. Willsky,et al.  Distributed fusion in sensor networks , 2006, IEEE Signal Processing Magazine.