activity
20232026
most citedDistributed Link Sparsification for Scalable Scheduling Using Graph Neural Networks (Journal Version)

4 citations · 4 across the 13 of their papers we have counts for

collaborators

13 papers

cs.NI2026

Biased Backpressure Routing for Multihop Wireless Networks with Heterogeneous Interfaces

Yujun Ming, Zhongyuan Zhao, Fikadu Dagefu +5

Heterogeneous-interface multihop wireless networks (Het-MuNets) are emerging as a promising paradigm for tactical networks and for infrastructure-light applications such as vehicul…

cs.NI2026

Ant Backpressure Routing for Dynamic Wireless Multi-hop Networks with Mixed Traffic Patterns

Negar Erfaniantaghvayi, Zhongyuan Zhao, Kevin Chan +2

Backpressure (BP) routing and its shortest-path biased variant (SP-BP) provide powerful congestion-aware multipath resource allocation for wireless multi-hop networks, but they rel…

cs.NI2025

A Differentiable Digital Twin of Distributed Link Scheduling for Contention-Aware Networking

Zhongyuan Zhao, Yujun Ming, Kevin Chan +2

Many routing and flow optimization problems in wired networks can be solved efficiently using minimum cost flow formulations. However, this approach does not extend to wireless mul…

cs.NI2025

Link-Sharing Backpressure Routing In Wireless Multi-Hop Networks

Zhongyuan Zhao, Yujun Ming, Ananthram Swami +3

Backpressure (BP) routing and scheduling is an established resource allocation method for wireless multi-hop networks, noted for its fully distributed operation and maximum queue s…

cs.NI2025★ 4 cited

Distributed Link Sparsification for Scalable Scheduling Using Graph Neural Networks (Journal Version)

Zhongyuan Zhao, Gunjan Verma, Ananthram Swami +1

In wireless networks characterized by dense connectivity, the significant signaling overhead generated by distributed link scheduling algorithms can exacerbate issues like congesti…

cs.NI2025

SeLR: Sparsity-enhanced Lagrangian Relaxation for Computation Offloading at the Edge

Negar Erfaniantaghvayi, Zhongyuan Zhao, Kevin Chan +2

This paper introduces a novel computational approach for offloading sensor data processing tasks to servers in edge networks for better accuracy and makespan. A task is assigned wi…