Wenyang Jia

NI
4papers
2citations
Novelty59%
AI Score54

4 Papers

97.8NIMay 23Code
ReclaimNet: Reclaim-Aware Network Protocols for Voluntary GPU Sharing on Campus

Wenyang Jia, Jingjing Wang, Xianneng Zou et al.

University campuses host abundant but fragmented GPU resources whose voluntary sharing is blocked by a mismatch between revocable, autonomous ownership and migration mechanisms that assume stationary failure hazards, homogeneous interconnects, and unbounded transfer windows. We present ReclaimNet, a network-layer migration protocol suite that treats provider reclaim as a first-class contract rather than a failure case, combining three mechanisms: (i) reclaim-aware checkpoint scheduling that jointly adapts to time-varying departure hazards and contended bandwidth across co-resident jobs; (ii) volatility-aware destination selection integrating topology, survival probability, and notice-window feasibility; and (iii) deadline-aware migration traffic control with edge enforcement and a submillisecond TC BPF kill-switch. A two-month deployment on a 54-node heterogeneous campus testbed reduces work loss by 66% over Slurm preempt-and-requeue and 38% over pipeline-redundancy checkpointing, with 38% shorter downtime and under 3% degradation of background research traffic. The prototype is open-sourced at the anonymous repository https://anonymous.4open.science/r/ICNP2026-ReclaimNet/.

93.4NIMay 10Code
PolicyCache-SDN: Hierarchical Intra-Path Learning for Adaptive SDN Traffic Control

Wenyang Jia, Jingjing Wang, Ziwei Yan et al.

Software defined networks offer global visibility, yet centralized control loops are too slow for transient congestion and bursty traffic dynamics. Existing learned traffic control schemes often rely on offline training, making them fragile under distribution shifts. We present PolicyCache-SDN, a hierarchical SDN traffic control framework that enables local online adaptation under centralized policy control. Its key abstraction is a policy envelope: the controller compiles network wide intent into bounded per path action spaces, while edge agents learn and execute metering, queueing, and rerouting decisions only within those bounds. Policy envelopes also make local actions auditable and reversible when they affect shared bottlenecks. Evaluation on a 1,024 host software SDN testbed shows that PolicyCache-SDN improves average core link utilization by 35.5% over Static ECMP and 18.3% over Centralized TE. It reduces elephant flow P99 FCT by 34.3% over end host congestion control, lowers SLA violations from 18.2% to 6.8%, and uses less than 2% CPU and 12 MB memory per edge agent. The source code is available in an anonymized repository at https://anonymous.4open.science/r/JCC2026-PolicyCache-SDN/.

63.8NIApr 26
OpenCLAW-Nexus: A Self-Reinforcing Trust Framework for Byzantine-Resilient Decentralized Federated Learning

Wenyang Jia, Qiankang Xu, Ziwei Yan et al.

Decentralized Federated Learning (DFL) eliminates the central aggregator but introduces a severe 'trust gap': without a trusted coordinator, the system becomes vulnerable to Byzantine and Sybil attacks, while existing solutions treat node selection, aggregation, and consensus as isolated modules, often relying on a trusted root dataset unavailable in truly decentralized settings.We propose OpenCLAW-Nexus, a self-reinforcing trust framework that bridges this gap through a single primitive, a discounted Beta-reputation model, that unifies reputation-based node selection, reputation-weighted aggregation Rep-FedAvg, and reputation-aware BFT consensus. Rep-FedAvg eliminates the trusted root dataset requirement; we formally prove reputation separation between honest and Byzantine nodes under non-IID data with noisy evaluations.On a 1,000-node global testbed spanning three cloud providers and nine regions, Rep-FedAvg achieves 72.6% accuracy on non-IID CIFAR-10 with 20% Byzantine nodes and record-level differential privacy, within 0.5,pp of centralized FLTrust.Under a 300-node Sybil attack, reputation-weighted consensus maintains 84.2% validation correctness versus 62.8% (PoW) and 47.6% (PoS).

10.6NIMar 29
Adaptive Intent-Aware PoW Mechanism in SDN for Multi-Domain SYN Flood Mitigation

Wenyang Jia

The stability of Internet services is persistently challenged by the escalating scale of volumetric TCP SYN floods, as conventional defenses like SYN Cookies fail by exacerbating bandwidth depletion under modern attacks. This paper introduces SDN-SYN PoW, a novel defense architecture that synergizes non-interactive Proof-of-Work with a Software-Defined Networking (SDN) control plane, an approach particularly effective for securing the network edge in modern SD-WAN deployments. The core innovation is its ability to perform global network sensing; the SDN controller monitors real-time traffic to dynamically adjust PoW difficulty, transforming the defense from a static mechanism into an intelligent, adaptive system that surgically applies computational costs only to anomalous sources. Through rigorous experiments on a custom-built testbed, we demonstrate that SDN-SYN PoW provides substantially superior protection and, critically, that the PoW overhead remains negligible for legitimate clients, ensuring compatibility even with low-power devices.