Characteristics of Autonomously Configured Structure Formation Based on Power Consumption and Data Transfer Efficiency

In MANETs (mobile ad hoc networks), mobile terminals can connect with each other directly and constitute communication networks without network infrastructure such as base stations and access points of wireless LANs that are connected to wired backbone networks. Therefore, MANETs are expected to be tolerant networks in an emergency situation (e.g., large earthquake) in which most infrastructure is destroyed. We have proposed an autonomous decentralized structure formation technology based on local interaction as the terminals' action method and, moreover, have applied the proposed structure formation technology to the autonomous decentralized clustering method of MANETs. In addition, we have evaluated the characteristics of this technology from the point of view of the power consumption during "cluster configuration." However, this technology has previously not been evaluated in terms of the characteristics of the power consumption and data transfer efficiency at the time of packet routing. In this paper, we compare the proposed clustering model with a bio-inspired model that is based on the reaction diffusion equation in the routing of the data.

[1]  Deborah Estrin,et al.  Networking issues in wireless sensor networks , 2003, J. Parallel Distributed Comput..

[2]  M. S. Corson,et al.  A highly adaptive distributed routing algorithm for mobile wireless networks , 1997, Proceedings of INFOCOM '97.

[3]  Kenichi Yamazaki,et al.  A Sensor Networking Middleware for Clustering Similar Things , 2005 .

[4]  Yoshiaki Kakuda,et al.  Hi-TORA: a hierarchical routing protocol in ad hoc networks , 2002, 7th IEEE International Symposium on High Assurance Systems Engineering, 2002. Proceedings..

[5]  Masayuki Murata,et al.  Proposal for Autonomous Decentralized Structure Formation Based on Local Interaction and Back-Diffusion Potential , 2012, IEICE Trans. Commun..

[6]  Visakan Kadirkamanathan,et al.  Parameter estimation and inference for stochastic reaction-diffusion systems: application to morphogenesis in D. melanogaster , 2009, BMC Systems Biology.

[7]  K. Ishida,et al.  Power Consumption Characteristics by Autonomous Decentralized Structure Formation Technology , 2012, 2012 9th Asia-Pacific Symposium on Information and Telecommunication Technologies (APSITT).

[8]  Chai-Keong Toh,et al.  Ad Hoc Mobile Wireless Networks , 2002 .

[9]  Giovanni Neglia,et al.  Evaluating activator-inhibitor mechanisms for sensors coordination , 2007, 2007 2nd Bio-Inspired Models of Network, Information and Computing Systems.

[10]  T. Ohta Maintenance Algorithm for Hierarchical Structure in Large Ad Hoc Networks , 2002 .

[11]  Hideki Tode,et al.  A Clustering Method for Wireless Sensor Networks with Heterogeneous Node Types , 2009, 2009 Proceedings of 18th International Conference on Computer Communications and Networks.

[12]  Masayuki Murata,et al.  Robust and Resilient Data Collection Protocols for Multihop Wireless Sensor Networks , 2012, IEICE Trans. Commun..

[13]  Masaki Aida,et al.  On Convergence Rate of Autonomous Decentralized Structure Formation Technology for Clustering in Ad Hoc Networks , 2012, 2012 32nd International Conference on Distributed Computing Systems Workshops.

[14]  P.H.J. Chong,et al.  A survey of clustering schemes for mobile ad hoc networks , 2005, IEEE Communications Surveys & Tutorials.

[15]  Naoki Wakamiya,et al.  Reaction-diffusion based autonomous control of wireless sensor networks , 2010, Int. J. Sens. Networks.

[16]  Chai-Keong Toh,et al.  Ad Hoc Mobile Wireless Networks , 2002 .

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