Ping Dong

Hongyuan Shi, Yilin Zhai, Ping Dong et al.

Reconstructing high-resolution regional significant wave height fields from sparse and uneven buoy observations remains a core challenge for ocean monitoring and risk-aware operations. We introduce AUWave, a hybrid deep learning framework that fuses a station-wise sequence encoder (MLP) with a multi-scale U-Net enhanced by a bottleneck self-attention layer to recover 32$\times$32 regional SWH fields. A systematic Bayesian hyperparameter search with Optuna identifies the learning rate as the dominant driver of generalization, followed by the scheduler decay and the latent dimension. Using NDBC buoy observations and ERA5 reanalysis over the Hawaii region, AUWave attains a minimum validation loss of 0.043285 and a slightly right-skewed RMSE distribution. Spatial errors are lowest near observation sites and increase with distance, reflecting identifiability limits under sparse sampling. Sensitivity experiments show that AUWave consistently outperforms a representative baseline in data-richer configurations, while the baseline is only marginally competitive in the most underdetermined single-buoy cases. The architecture's multi-scale and attention components translate into accuracy gains when minimal but non-trivial spatial anchoring is available. Error maps and buoy ablations reveal key anchor stations whose removal disproportionately degrades performance, offering actionable guidance for network design. AUWave provides a scalable pathway for gap filling, high-resolution priors for data assimilation, and contingency reconstruction.

Zongzheng Wang, Ping Dong

In vehicular communications, in-vehicle devices' mobile and multihoming characteristics bring new requirements for devicevsecurity authentication. On the one hand, the existing network layer authentication methods rely on the PKI system; on the other hand, key negotiation needs interaction. These two points determine that the traditional security authentication method requires bandwidth consumption and additional delay. It is unsuitable for heterogeneous wireless scenarios with a high packet loss rate and limited bandwidth resources. In addition, the establishment of a security association state is contrary to the original design that the network layer only provides a forwarding function. We proposed a non-interactive multihoming security authentication (NIMSA) scheme, a stateless network layer security authentication scheme triggered by data forwarding. Our scheme adopts an identity-based non-interactive key agreement strategy to avoid the interaction of signaling information, which is lightweight and has good support for mobile and multipath parallel transmission scenarios. The comparison with IKEv2 and its mobility and multihoming extension scheme (MOBIKE) shows that the proposed scheme has shorter authentication and handover delay and data transmission delay and can bring better bandwidth aggregation effect in the scenario of multipath parallel transmission.

Jiayang Song, Ping Dong, Huachun Zhou et al.

Driven by the primary requirement of emerging 5G mobile services, the demand for concurrent multipath transfer (CMT) is still prominent. Yet, multipath transport protocols are not widely adopted and TCP-based CMT schemes will still be in dominant position in 5G. However, the performance of TCP flow transferred over multiple heterogeneous paths is prone to the link quality asymmetry, the extent of which was revealed to be significant by our field investigation. In this paper, we present a performance analysis model for TCP over multiple heterogeneous paths in 5G scenarios, where both bandwidth and delay asymmetry are taken into consideration. The evaluation adopting parameters from field investigation shows that the proposed model can achieve high accuracy in practical environments. Some interesting inferences can be drawn from the proposed model, such as the dominant factor that affect the performance of TCP over heterogeneous networks, and the criteria of determining the appropriate number of links to be used under different circumstances of path heterogeneity. Thus, the proposed model can provide a guidance to the design of TCP-based CMT solutions for 5G mobile services.