Effective information flow over mobile adaptive networks

Collective motion is a remarkable phenomenon in biological systems. There have been several models in the literature to regenerate this type of motion, such as averaging consensus strategies where nodes continuously average the velocity vectors of their neighbors. While many models are able to generate forms of collective motion, they nevertheless neglect the important fact that the most informed nodes in a network tend to modulate their information into their speeds. In this work, we show how the speed information can be exploited and incorporated into the design of the combination rules for mobile networks. The analysis leads to a sigmoidal function construction, and the results show that the proposed combination rule leads to more effective information flow over networks of mobile agents.