Improving the Area Efficiency of ACO-Based Routing by Directional Pheromone in Large-Scale NoCs

• The concept of Directional Pheromone (DP) is proposed.
• There are two techniques used in the DP routing algorithm for improving performance.
• Detailed hardware architecture of ACO-DP routing is presented.

Ant Colony Optimization (ACO) is a distributed collective-intelligence algorithm. Several adaptive routing algorithms based on ACO have been proposed in the domain of Network-on-Chip (NoC) design for balancing traffic load. However, when network size becomes large, the conventional ACO requires quite a lot of pheromones for predicting network load distribution, which results in large hardware cost and low cost-efficiency. In this paper, an ACO algorithm with directional pheromone (ACO-DP) is proposed for reducing the size of pheromone table in large-scale networks. Moreover, by using a distance-sensitive backward pheromone updating scheme, the performance of ACO-DP is also improved. Finally, we introduce the detailed architecture and hardware implementation of ACO-DP routing. Experimental results show that ACO-DP routing achieves the highest area efficiency in large-scale NoC systems compared to other ACO-based routing algorithms.