Proposed ProFlow, a proactive flow-placement framework using distributed telemetry signals and offline-trained RL for identifying precursor congestion conditions and rerouting protected flows in multi…

This paper compares Google's BBR-v3 Congestion Control Algorithm to eight others over SpaceX's Starlink network, demonstrating its fairness and throughput maximization in high-latency, variable satell…

This paper characterizes the impact of ETSI Decentralized Congestion Control (DCC) on age of information (AoI) for vehicle-to-infrastructure updates, revealing a hyperbolic density dependence and prop…

The paper introduces CCLab, an adversarial testing framework, to systematically evaluate the robustness of both learning-based and traditional congestion controllers, finding that learning-based contr…

This paper proposes CAPS, a scheduling layer for data centers that separates rate computation and packet scheduling, reducing queue occupancy by up to 10x without throughput loss.

This paper introduces Stigmergic Graph Memory (SGM), a method to improve warehouse throughput in many-to-many Multi-Agent Pickup and Delivery (MAPD) by using a bounded, decaying memory layer to record…

This paper proposes a value-based DCC method for Intelligent Transport Systems to maintain channel load while retaining more high-value objects.

This paper presents AlphaRoute, a multi-objective adaptive search framework for VLSI global routing using Large Language Models as semantic policy optimizers.

This paper presents a dynamic multi-layer equilibrium attractor for disrupted urban mobility, establishes conditions for exact and approximate projectability of the attractor, and shows that two obser…

This paper proposes ARTSN, a scheduling paradigm for autonomous real-time systems using time-sensitive networking, addressing volatility and absence challenges of self-triggered traffic.

This paper compares the efficiency of different routing algorithms for collectively routed fleets of autonomous vehicles and proposes a market design to encourage social welfare oriented cooperation.

This paper demonstrates that autonomous aircraft can self-organize into efficient corridor flows in decentralized settings.

This survey reviews how Large and Multi-modal Language Models (LLMs/MM-LLMs) are being applied to integrate diverse data sources for enhanced decision support in transportation systems management and…

This paper analyzes the synchronization of power usage in large-scale AI training facilities and identifies the coupling channel in load-dependent throttling.

AlphaTransit introduces a novel search-based planning framework that combines Monte Carlo Tree Search (MCTS) with a neural policy-value network to efficiently design high-quality, city-scale bus trans…

This paper introduces FORESEE, a cooperative lane change model for connected and automated driving that utilizes V2X data to organize vehicles and improve traffic flow, enhancing average vehicle speed…