Study on Bottleneck Nodes in Wireless Sensor Networks

“Bottleneck Nodes” are those connecting two or more areas alone with the reason of the deployment. Compared to other nodes, this kind of nodes are more important to the lifetime of the whole network. How to find these nodes is a problem about how to find the minimum cut set in graph theory, and is difficult to implement in a distributed way. In this paper, a new kind of nodes named “quasi-Bottleneck Nodes” which have similar effect on the performance of the wireless sensor network and can be found out much more easily is introduced. Theoretical analysis and extensive simulation show that “quasi-Bottleneck Nodes” have a significant impact on the performance of the whole network (including the speed of energy consumption and packet lost ratio), and a distributed algorithm to find out all the “quasi-Bottleneck Nodes” and two effective solutions to eliminate the bad effect of these nodes are presented.

[1]  Ossama Younis,et al.  HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks , 2004, IEEE Transactions on Mobile Computing.

[2]  David E. Culler,et al.  System architecture directions for networked sensors , 2000, SIGP.

[3]  Edward J. Coyle,et al.  An energy efficient hierarchical clustering algorithm for wireless sensor networks , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[4]  Laurent Massoulié,et al.  Bandwidth sharing: objectives and algorithms , 2002, TNET.

[5]  Bhaskar Krishnamachari,et al.  Impact of energy depletion and reliability on wireless sensor network connectivity , 2004, SPIE Defense + Commercial Sensing.

[6]  Jia Wang,et al.  A measurement study of Internet bottlenecks , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[7]  Deborah Estrin,et al.  The impact of data aggregation in wireless sensor networks , 2002, Proceedings 22nd International Conference on Distributed Computing Systems Workshops.

[8]  Thomas F. La Porta,et al.  Sensor relocation in mobile sensor networks , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[9]  Gregory J. Pottie,et al.  Wireless integrated network sensors , 2000, Commun. ACM.

[10]  QUTdN QeO,et al.  Random early detection gateways for congestion avoidance , 1993, TNET.

[11]  Gaurav S. Sukhatme,et al.  Robomote: a tiny mobile robot platform for large-scale ad-hoc sensor networks , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[12]  Deborah Estrin,et al.  Directed diffusion for wireless sensor networking , 2003, TNET.

[13]  Wendi Heinzelman,et al.  Proceedings of the 33rd Hawaii International Conference on System Sciences- 2000 Energy-Efficient Communication Protocol for Wireless Microsensor Networks , 2022 .

[14]  Nathan Ickes,et al.  Physical layer driven protocol and algorithm design for energy-efficient wireless sensor networks , 2001, MobiCom '01.

[15]  Konstantinos Kalpakis,et al.  Efficient algorithms for maximum lifetime data gathering and aggregation in wireless sensor networks , 2003, Comput. Networks.