Self-Stabilizing and Efficient Robust Uncertainty Management

This report results from a contract tasking Ben Gurion University as follows: During the course of this research project we have examined various models of communication and UAVs coordination including simulating birds flocking behavior. We considered the situation when the members of the swarm may discover each other by exchanging messages; periodically collecting information concerning the position, speed and direction of other members. Next, we considered the situation where the means of communication are lost between the participants of the swarm. We have also presented information-theoretically secure schemes for sharing and modifying a secret among a dynamic swarm of computing devices. We studied the problem of topology control through power assignments so that the induced communication graph of UAVs is strongly connected under optimization objectives of energy efficiency, interference and stretch factor. We considered different models of aggregating information in mobile networks. We present the first set of swarm flocking algorithms that maintain connectivity while electing direction for flocking. We proposed a collaborative application monitoring infrastructure, that is capable of dramatically decreasing the susceptibility of mobile devices to malicious applications. We explored a polar representation of optical flow in which each element of the brightness motion field is represented by its magnitude and orientation instead of its Cartesian projections. Finally, we have proposed a fully automatic solver to reconstruct the complete image from a set of non-overlapping, unordered, square puzzle parts. AFRL-AFOSR-UK-TR-2012-0011. The original document contains color images.