| Title | An Adaptive Routing Scheme Based on Q-learning and Real-time Traffic Monitoring for Network-on-Chip |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Fan, Renshi, Du, Gaoming, Xu, Pengfei, Li, Zhenmin, Song, Yukun, Zhang, Duoli |
| Conference Name | 2019 IEEE 13th International Conference on Anti-counterfeiting, Security, and Identification (ASID) |
| Keywords | adaptive routing scheme, C-XY routing, Computer architecture, dynamical Q-learning routing approach, dynamical routing, dynamical routing schemes, DyXY routing, Heuristic algorithms, learning (artificial intelligence), Metrics, monitor, Monitoring, network congestion, network on chip security, network routing, network-on-chip, NoC, optimisation, packet transmission, Performance optimization, Prediction algorithms, q-learning, Real-time, Real-time Systems, resilience, Resiliency, Routing, Scalability, telecommunication traffic, traffic load congestion, traffic monitoring |
| Abstract | In the Network on Chip (NoC), performance optimization has always been a research focus. Compared with the static routing scheme, dynamical routing schemes can better reduce the data of packet transmission latency under network congestion. In this paper, we propose a dynamical Q-learning routing approach with real-time monitoring of NoC. Firstly, we design a real-time monitoring scheme and the corresponding circuits to record the status of traffic congestion for NoC. Secondly, we propose a novel method of Q-learning. This method finds an optimal path based on the lowest traffic congestion. Finally, we dynamically redistribute network tasks to increase the packet transmission speed and balance the traffic load. Compared with the C-XY routing and DyXY routing, our method achieved improvement in terms of 25.6%-49.5% and 22.9%-43.8%. |
| DOI | 10.1109/ICASID.2019.8924997 |
| Citation Key | fan_adaptive_2019 |
An Adaptive Routing Scheme Based on Q-learning and Real-time Traffic Monitoring for Network-on-Chip