Motif-based Communication Network Formation for Task Specific Collaboration in Complex Environments

John S. Baras, Pedram Hovareshti and Hua Chen

Asilomar Conference on Signals, Systems, and Computers, Asilomar Hotel & Conference Grounds Pacific Grove, CA, November 6-9, 2011.

Abstract:

Networks of mobile autonomous vehicles rely
heavily on wireless communications as well as sensing devices
for distributed path planning and decision making. Designing
energy efficient distributed decision making algorithms in these
systems is challenging and requires that different task-oriented
information becomes available to the corresponding agents in a
timely and reliable manner. We develop a systems engineering
oriented approach to the design of networks of mobile autonomous
systems, in which a cross-layer design methodology
determines what structures are to be used to satisfy different
task requirements.We identify a three-tier organization of these
networks consisting of connectivity, communication, and action
graphs and study the interaction between them. It is expected
that in each functionality of a network, there are certain
topologies that facilitate better achievement of the agents’
objectives. Inspired from biological complex networks, we
propose a bottom-up approach in network formation, in which
small efficient subgraphs (motifs) for different functionalities of
the network are determined. The overall network is then formed
as a combination of these sub-graphs.We show that the bottomup
approach to network formation is capable of generating
efficient topologies for multi-tasking complex environments.