Motif-based Communication Network Formation for Task Specific Collaboration in Complex Environments
J. S. Baras, P. Hovareshti and H. Chen
Proceedings of the 2011 American Control Conference, pp. 1051-1056, San Francisco, CA, June 29-July 01, 2011.
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 systems of collaborative moving agents 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. To this end, we identify a three-tier organization of these networks consisting of connectivity, communication, and action graphs and we study the interaction between these graphs. It is expected that in each functionality of a network, there are certain topologies that facilitate better achievement of the agentsí objectives. Inspired from biological complex networks, we propose a bottom-up approach in network formation, in which small efficient subgraphs for different functionalities of the network are determined. The overall network is then formed as a combination of these sub-graphs.We utilize network motifs in the context of collaborative control of autonomous mobile agents and study the efficiency of the networks formed by combining these motifs. We show that the bottom-up approach to network formation in such scenarios is capable of generating efficient topologies for multi-tasking complex environments.