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Found 26 papers, 0 papers with code
MaxCUCL: Max-Consensus with Deterministic Convergence in Networks with Unreliable Communication
Our proposed algorithm is the first algorithm that achieves max-consensus in a deterministic manner (i. e., nodes always calculate the maximum of their states regardless of the nature of the probability distribution of the packet drops).
Distributed Estimation and Control for LTI Systems under Finite-Time Agreement
This paper considers a strongly connected network of agents, each capable of partially observing and controlling a discrete-time linear time-invariant (LTI) system that is jointly observable and controllable.
Distributed Optimization via Gradient Descent with Event-Triggered Zooming over Quantized Communication
Distributed methods in which nodes use quantized communication yield a solution at the proximity of the optimal solution, hence reaching an error floor that depends on the quantization level used; the finer the quantization the lower the error floor.
Distributed Optimization for Quadratic Cost Functions over Large-Scale Networks with Quantized Communication and Finite-Time Convergence
We prove that our algorithms converge in a finite number of iterations to the exact optimal solution depending on the quantization level, and we present applications of our algorithms to (i) optimal task scheduling for data centers, and (ii) global model aggregation for distributed federated learning.
Distributed Computation of Exact Average Degree and Network Size in Finite Number of Steps under Quantized Communication
We present two distributed algorithms which rely on quantized operation (i. e., nodes process and transmit quantized messages), and are able to calculate the exact solutions in a finite number of steps.
Distributed Optimization with Quantized Gradient Descent
For solving this distributed optimization problem, we combine a gradient descent method with a distributed quantized consensus algorithm (which requires the nodes to exchange quantized messages and converges in a finite number of steps).
ARQ-based Average Consensus over Unreliable Directed Network Topologies
In this paper, we address the discrete-time average consensus problem, where nodes exchange information over unreliable communication links.
Distributed CPU Scheduling Subject to Nonlinear Constraints
This paper considers a network of collaborating agents for local resource allocation subject to nonlinear model constraints.
DTAC-ADMM: Delay-Tolerant Augmented Consensus ADMM-based Algorithm for Distributed Resource Allocation
Every node locally updates its state toward optimizing a global allocation cost function via received information of its neighbouring nodes even when the data exchange over the network is heterogeneously delayed at different links.
Distributed Constraint-Coupled Optimization over Lossy Networks
This paper considers distributed resource allocation and sum-preserving constrained optimization over lossy networks, where the links are unreliable and subject to packet drops.
Linear TDOA-based Measurements for Distributed Estimation and Localized Tracking
We present the minimal conditions on the remaining sensor network (after link/node removal) such that the distributed observability is still preserved and, thus, the sensor network can track the (single) maneuvering target.
Distributed Anomaly Detection and Estimation over Sensor Networks: Observational-Equivalence and Q-Redundant Observer Design
Instead, only instantaneous deviation of the residuals raises the alarm in the stateless case without considering the history of the sensor outputs and estimation data.
Distributed Finite-Sum Constrained Optimization subject to Nonlinearity on the Node Dynamics
Motivated by recent development in networking and parallel data-processing, we consider a distributed and localized finite-sum (or fixed-sum) allocation technique to solve resource-constrained convex optimization problems over multi-agent networks (MANs).
Distributed Detection and Mitigation of Biasing Attacks over Multi-Agent Networks
First, for performance analysis in the attack-free case, we show that the proposed distributed estimation is unbiased with bounded mean-square deviation in steady-state.
1st-Order Dynamics on Nonlinear Agents for Resource Allocation over Uniformly-Connected Networks
A general nonlinear $1$st-order consensus-based solution for distributed constrained convex optimization is proposed with network resource allocation applications.
Machine learning based iterative learning control for non-repetitive time-varying systems
A machine learning (ML) based nominal model update mechanism, which utilizes the linear regression technique to update the nominal model at each ILC trial only using the current trial information, is proposed for non-repetitive TVSs in order to enhance the ILC performance.
Analysis of Contractions in System Graphs: Application to State Estimation
Observability and estimation are closely tied to the system structure, which can be visualized as a system graph--a graph that captures the inter-dependencies within the state variables.
Simultaneous Distributed Estimation and Attack Detection/Isolation in Social Networks: Structural Observability, Kronecker-Product Network, and Chi-Square Detector
This paper considers distributed estimation of linear systems when the state observations are corrupted with Gaussian noise of unbounded support and under possible random adversarial attacks.
A Survey on Reinforcement Learning-Aided Caching in Mobile Edge Networks
Mobile networks are experiencing tremendous increase in data volume and user density.
Multi-agent consensus with heterogeneous time-varying input and communication delays in digraphs
First, for all agents whose state matrix has no eigenvalues with positive real parts, a communication-delay-related observer, which is used to construct the controller, is designed for followers to estimate the leader's state information.
Effect of Computational Power of Sensors on Event-Triggered Control Mechanisms over a Shared Contention-Based Network
In this paper, we study distributed channel triggering mechanisms for wireless networked control systems (WNCSs) for conventional and smart sensors, i. e., sensors without and with computational power, respectively.
Consensus-Based Distributed Estimation in the Presence of Heterogeneous, Time-Invariant Delays
Classical distributed estimation scenarios typically assume timely and reliable exchanges of information over the sensor network.
Distributed support-vector-machine over dynamic balanced directed networks
In this paper, we consider the binary classification problem via distributed Support-Vector-Machines (SVM), where the idea is to train a network of agents, with limited share of data, to cooperatively learn the SVM classifier for the global database.
Distributed Channel Access for Control Over Unknown Memoryless Communication Channels
This property is then exploited for developing our distributed deterministic channel access scheme.
Fast-Convergent Dynamics for Distributed Allocation of Resources Over Switching Sparse Networks with Quantized Communication Links
The idea is to optimally allocate the resources among the group of agents by minimizing the overall cost function subject to fixed sum of resources.
Optimal Radio Frequency Energy Harvesting with Limited Energy Arrival Knowledge
While the idea of RF-EH is appealing, it is not always beneficial to attempt to harvest energy; in environments where the ambient energy is low, nodes could consume more energy being awake with their harvesting circuits turned on than what they can extract from the ambient radio signals; it is then better to enter a sleep mode until the ambient RF energy increases.
