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This paper investigates the average-consensus problem of first-order discrete-time multi-agent networks in uncertain communication environments. Each agent can only use its own and neighbors' information to design its control input. To attenuate the communication noises, a distributed stochastic approximation type protocol is used. By using probability limit theory and algebraic graph theory, consensus...
In this paper we study how the connectivity affects the performance of insular parallel genetic algorithms (PGAs). Seven topologies PGAs were proposed, with growing number of connections. We used three instances of the well-known traveling salesman problem as benchmark. Each island of the PGA had different parameters and we established a fixed migration policy for all islands. Experiments were done...
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...
This paper analyzes the rate of convergence of a distributed averaging scheme making use of memory at each node. In conventional distributed averaging, each node computes an update based on its current state and the current states of their neighbours. Previous work observed the trajectories at each node converge smoothly and demonstrated via simulation that a predictive framework can lead to faster...
The complexity and dynamics of Border Gateway Protocol (BGP), the only inter-domain routing protocol available for the Internet, is driving the need for efficient, scalable, realistic and meaningful network simulations. To properly simulate the behavior of BGP as currently deployed, one requires both a realistic topology and a realistic model of BGP. Although a large number of topology generators...
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