Constrained Clustering as an Optimization Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Matrix Perturbation View of the Small World Phenomenon
SIAM Journal on Matrix Analysis and Applications
Could any graph be turned into a small-world?
Theoretical Computer Science - Complex networks
A scheme for robust distributed sensor fusion based on average consensus
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
IEEE/ACM Transactions on Networking (TON) - Special issue on networking and information theory
Complex Graphs and Networks (Cbms Regional Conference Series in Mathematics)
Complex Graphs and Networks (Cbms Regional Conference Series in Mathematics)
Backbone construction in selfish wireless networks
Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Cooperative Control of Distributed Multi-Agent Systems
Cooperative Control of Distributed Multi-Agent Systems
The university of Florida sparse matrix collection
ACM Transactions on Mathematical Software (TOMS)
Gibbs sampler-based coordination of autonomous swarms
Automatica (Journal of IFAC)
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We consider two closely related dynamic self-organization problems in networked control systems. Both are forms of dynamic clustering of nodes. The structure of networked control systems is often abstracted using graph theory. In this abstraction, the nodes of the graph represent the agents and the edges between them represent the relation(s) or the possibility of communication between the corresponding agents. The topology of the communication network supporting a networked control system has critical consequences for its performance. The first problem we address is the development of a distributed self-organization algorithm, resulting into a dynamic two level hierarchy of leader and regular agents, which substantially improves the convergence speed of distributed algorithms utilized by the networked control system. For the second problem, we consider the collaborative control of a group of autonomous mobile agents (e.g. vehicles, robots) supported by a mobile wireless network, consisting of many ground and a few aerial nodes. The agents collaborate to achieve a common goal or objective, like to move in a particular area and cover it, while avoiding obstacles and collisions. Building upon our earlier work on deterministic, randomized and hybrid distributed coordination algorithms we consider the communication needs of the agents, and in particular the connectivity of their communication network as they move. We develop distributed algorithms that automatically select some agents and move them appropriately so as to maintain certain degree of desired connectivity among the moving agents. We characterize the trade-off between the gain from maintaining a certain degree of connectivity vs. the combined cost of communications and the associated dynamic re-positioning of agents. We also describe classes of efficient communication topologies and in particular their similarity to dynamic small world topologies and extensions.