Xiaocheng Wang | Searcharxiv

arXiv2025

Resilient Event-Triggered Control of Vehicle Platoon Under DoS Attacks and Parameter Uncertainty

This paper investigates the problem of dynamic event-triggered platoon control for intelligent vehicles (IVs) under denial of service (DoS) attacks and parameter uncertainty. DoS attacks disrupt vehicle-to-vehicle (V2V) communications, leading to the destabilization of vehicle formations. To alleviate the burden of the V2V communication network and enhance the tracking performance in the presence of DoS attacks and parameter uncertainty, a resilient and dynamic event-triggered mechanism is proposed. In contrast to the static event-triggering mechanism (STEM), this approach leverages the internal dynamic variable to further save communication resources. Subsequently, a method is developed for designing the desired triggering mechanism. Following this, a co-design framework is constructed to guarantee robust and resilient control against DoS attacks, with the analysis of eliminating Zeno behavior. Lastly, extensive simulations are presented to show the superiority of the proposed method in terms of enhancing platoon resilience and robustness and improving communication efficiency.

eess.SY↗

arXiv2016

Backhaul-Aware User Association and Resource Allocation for Energy-Constrained HetNets

Growing attentions have been paid to renewable energy or hybrid energy powered heterogeneous networks (HetNets). In this paper, focusing on backhaul-aware joint user association and resource allocation for this type of HetNets, we formulate an online optimization problem to maximize the network utility reflecting proportional fairness. Since user association and resource allocation are tightly coupled not only on resource consumption of the base stations (BSs), but also in the constraints of their available energy and backhaul, the closed-form solution is quite difficult to obtain. Thus, we solve the problem distributively via employing some decomposition methods. Specifically, at first, by adopting primal decomposition method, we decompose the original problem into a lower-level resource allocation problem for each BS, and a higher-level user association problem. For the optimal resource allocation, we prove that a BS either assigns equal normalized resources or provides equal long-term service rate to its served users. Then, the user association problem is solved by Lagrange dual decomposition method, and a completely distributed algorithm is developed. Moreover, applying results of the subgradient method, we demonstrate the convergence of the proposed distributed algorithm. Furthermore, in order to efficiently and reliably apply the proposed algorithm to the future wireless networks with an extremely dense BS deployment, we design a virtual user association and resource allocation scheme based on the software-defined networking architecture. Lastly, numerical results validate the convergence of the proposed algorithm and the significant improvement on network utility, load balancing and user fairness.

cs.NI↗