On Convergence Rate of Autonomous Decentralized Structure Formation Technology for Clustering in Ad Hoc Networks

Hierarchization by clustering is effective for scalable routing control in an ad hoc network. Due to a constraint from structural features of ad hoc networks, clustering in ad hoc networks should be autonomous decentralized algorithm based on local information. Bio-inspired approach gives a solution of such autonomous decentralized clustering mechanism and its well-known mechanism is based on reaction-diffusion equations. Apart from this, we have already proposed the autonomous decentralized clustering mechanism for ad hoc networks based on two concepts of renormalization transformation and back-diffusion potential. One of most important requirements to the clustering mechanism is faster convergence speed of clustering to adapt to dynamic environments. In this paper, we compare convergence speed of both mechanisms.