3 papers
cs.DC2026
Deep Reinforcement Learning for Fault-Adaptive Routing in Eisenstein-Jacobi Interconnection Topologies
Mohammad Walid Charrwi, Zaid Hussain
The increasing density of many-core architectures necessitates interconnection networks that are both high-performance and fault-resilient. Eisenstein-Jacobi (EJ) networks, with th…
cs.DC2025
Resilient Packet Forwarding: A Reinforcement Learning Approach to Routing in Gaussian Interconnected Networks with Clustered Faults
Mohammad Walid Charrwi, Zaid Hussain
As Network-on-Chip (NoC) and Wireless Sensor Network architectures continue to scale, the topology of the underlying network becomes a critical factor in performance. Gaussian Inte…
cs.DC2025
Toward Self-Healing Networks-on-Chip: RL-Driven Routing in 2D Torus Architectures
Mohammad Walid Charrwi, Zaid Hussain
We investigate adaptive minimal routing in 2D torus networks on chip NoCs under node fault conditions comparing a reinforcement learning RL based strategy to an adaptive routing ba…