Degree Constrained Topology Control for Very Dense Wireless Sensor Networks

We present a novel topology control algorithm for very dense wireless sensor networks that is constrained by a small maximum nodal degree k. Particularly, we limit k=4 which makes it challenging to formulate a connected network that possesses favorable properties such as a small diameter, short average path length and low energy consumption. Towards this goal, we introduce a graph theoretic approach that utilizes a Borel Cayley Graph as an underlying network topology. We call this approach Borel Cayley Graph Topology Control (BCG-TC). Simulation results for a network with 1081 nodes distributed over a 100m×100m area showed that BCG-TC can formulate connected networks for the radio range exceeding certain threshold. Furthermore, these connected networks generated by BCG-TC exhibit (i) a small nodal degree k≤4, (ii) a small diameter and short average path length, and (iii) fast information dissemination that leads to the least energy consumption among considered topology control protocols.

[1]  Rajmohan Rajaraman,et al.  Topology control and routing in ad hoc networks: a survey , 2002, SIGA.

[2]  Richard M. Murray,et al.  Consensus problems in networks of agents with switching topology and time-delays , 2004, IEEE Transactions on Automatic Control.

[3]  K. Wendy Tang,et al.  Dense and Symmetric Graph Formulation and Generation for Wireless Information Networks , 2009, 2009 International Conference on Wireless Networks and Information Systems.

[4]  K. Wendy Tang,et al.  Vertex-transitivity and routing for Cayley graphs in GCR representations , 1992, SAC '92.

[5]  Christian Bettstetter,et al.  On the Connectivity of Ad Hoc Networks , 2004, Comput. J..

[6]  K. Wendy Tang,et al.  A graph theoretic approach to ultrafast information distribution: Borel Cayley graph resizing algorithm , 2010, Comput. Commun..

[7]  K. Wendy Tang,et al.  Representations and routing for Cayley graphs [computer networks] , 1991, IEEE Trans. Commun..

[8]  R. Olfati-Saber Ultrafast consensus in small-world networks , 2005, Proceedings of the 2005, American Control Conference, 2005..

[9]  Mauro Leoncini,et al.  The k-Neighbors Approach to Interference Bounded and Symmetric Topology Control in Ad Hoc Networks , 2006, IEEE Transactions on Mobile Computing.

[10]  Stephen P. Boyd,et al.  A scheme for robust distributed sensor fusion based on average consensus , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[11]  K. Wendy Tang,et al.  Pseudo-Random Graphs for Fast Consensus Protocol , 2009, PDPTA.

[12]  Mehran Mesbahi,et al.  Agreement over random networks , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[13]  Lui Sha,et al.  Design and analysis of an MST-based topology control algorithm , 2003, IEEE Transactions on Wireless Communications.

[14]  Paramvir Bahl,et al.  A cone-based distributed topology-control algorithm for wireless multi-hop networks , 2005, IEEE/ACM Transactions on Networking.

[15]  Roger Wattenhofer,et al.  XTC: a practical topology control algorithm for ad-hoc networks , 2004, 18th International Parallel and Distributed Processing Symposium, 2004. Proceedings..

[16]  Mihaela Cardei,et al.  Using sink mobility to increase wireless sensor networks lifetime , 2008, 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks.

[17]  K. Wendy Tang,et al.  Representations of Borel Cayley Graphs , 1993, SIAM J. Discret. Math..

[18]  Paolo Santi Topology control in wireless ad hoc and sensor networks , 2005 .