This paper presents a new framework for synchronization of complex network by introducing a mechanism of event-triggering distributed sampling information.
The trigger condition and event-triggered distributed subgradient optimization algorithm for each agent are completely decentralized and just rest with each agent's and its neighboring agents' individual states at the event-triggered sequence of themselves as well as each agent's local objective function.
On Wednesday morning, Operation Payback triggered a distributed denial of service (DDoS) attack against the Australian Federation Against Copyright Theft (AFACT) and the site was put out of action for a number of hours.
In this paper, the event-triggered distributed H∞ state estimation problem is investigated for a class of state-saturated systems with randomly occurring mixed delays over sensor networks.
In this paper, the event-triggered distributed multi-sensor data fusion algorithm is presented for wireless sensor networks (WSNs) based on a new event-triggered strategy.
According to the event-triggered protocol and the mean-square analysis, a suboptimal Kalman gain matrix is derived and a suboptimal event-triggered distributed filter is obtained.
In [23], the authors studied the event-triggered distributed average-consensus of discrete-time first-order multi-agent systems with limited communication data rate and general directed network topology.
In this communication environment, due to the limited wireless resources, the communication patterns of subsystems have changed fundamentally, and the design of time-triggered and event-triggered distributed controllers should be taken into account simultaneously.
This paper is concerned with the problem of event-triggered distributed state estimation for a class of discrete nonlinear stochastic systems with time-varying delays, randomly occurring uncertainties and randomly occurring nonlinearities.
Theoretical analysis shows that the event-triggered distributed subgradient algorithm is capable of steering the whole network of agents asymptotically converge to an optimal solution of the convex optimization problem.
