Privacy Preserving Distributed Bandit Residual Feedback Online Optimization Over Time-Varying Unbalanced Graphs

This paper considers the distributed online optimization(DOO) problem over time-varying unbalanced networks, where gradient information is explicitly unknown. To address this issue, a privacy-preserving distributed online one-point residual feedback(OPRF) optimization algorithm is proposed. This algorithm updates decision variables by leveraging one-point residual feedback to estimate the true gradient information. It can achieve the same performance as the two-point feedback scheme while only requiring a single function value query per iteration. Additionally, it effectively eliminates the effect of time-varying unbalanced graphs by dynamically constructing row stochastic matrices. Furthermore, compared to other distributed optimization algorithms that only consider explicitly unknown cost functions, this paper also addresses the issue of privacy information leakage of nodes. Theoretical analysis demonstrate that the method attains sublinear regret while protecting the privacy information of agents. Finally, numerical experiments on distributed collaborative localization problem and federated learning confirm the effectiveness of the algorithm.

Multi-Robot Cooperative Localization:Time-Varying Unobservable Subspace Analysis and Consistent Algorithm Design

This paper investigates the problem of cooperative localization(CL)for a multi-robot system(MRS)under dynamic measurement topology,which involves a group of robots collectively estimating their poses with respect to a common reference frame using ego-motion measurements and robot-to-robot relative measurements.The authors provide a theoretical analysis of the time-varying unobservable subspace and propose a consistent cooperative localization algorithm.First,the authors introduce the relative measurement graph(RMG)to represent the relative pose measurements obtained by the MRS at each instant.Then,the authors derive the local observability matrix over a time interval.An equivalent relationship is established between the local observability matrix and the spectral matrices of the RMG.Moreover,the authors present a method for constructing the unobservable subspace based on the RMG under different topology conditions.Based on this analysis,the authors design a consistent cooperative localization algorithm that satisfies the constraints of the time-varying unobservable subspace.An analytical optimal solution is derived for the constrained optimization problem.Monte Carlo numerical simulations are conducted to demonstrate the consistency and accuracy of the proposed method.

ROBUST CONSENSUS AND SOFT CONTROL OF MULTI-AGENT SYSTEMS WITH NOISES

This paper considers the problem of robust consensus for a basic class of multi-agent systems with bounded disturbances and with directed information flow. A necessary and sufficient condition on the robust consensus is first presented, which is then applied to the analysis, control and decision making problems in the noise environments. In particular, the authors show how a soft control technique will synchronize a group of autonomous mobile agents without changing the existing local rule of interactions, and without assuming any kind of connectivity conditions on the system trajectories.

A maximum flow algorithm for buffer-limited delay tolerant networks

Deep space networks,satellite networks,ad hoc networks,and the Internet can be modeled as DTNs(Delay Tolerant Networks).As a fundamental problem,the maximum flow problem is of vital importance for routing and service scheduling in networks.However,there exists no permanent end-to-end path since the topology and the characteristics of links are time-variant,resulting in a crucial maximum flow problem in DTNs.In this paper,we focus on the single-source-single-sink maximum flow problem of buffer-limited DTNs,followed by a valid algorithm to solve it.First,the BTAG(Buffer-limited Time Aggregated Graph)is constructed for modeling the buffer-limited DTN.Then,on the basis of BTAG,the two-way cache transfer series and the relevant transfer rules are designed,and thus a BTAG-based maximum flow algorithm is proposed to solve the maximum flow problem in buffer-limited DTNs.Finally,a numerical example is given to demonstrate the effectiveness of the proposed algorithm.

Formation Control of Underwater Mobile Sensing Networks

Formation control is essential for an underwater mobile sensing network(UMSN) ,and an ad hoc network which wirelessly connects underwater vehicles of sensing and/or observing types via acoustic communications,to fulfill mobile sensing tasks.The problem of formation control for a UMSN with varying topology is studied in this paper.The methodology of synthesizing distributed formation controller which stabilizes a UMSN with varying topology is proposed on the basis of the stability analysis of linear time-varying systems.