Ant Colony Optimization-Based Adaptive Network-on-Chip Routing Framework Using Network Information Region

The network-on-chip (NoC) system can provide more scalable and flexible on-chip interconnection compared with system bus. The performance of on-chip adaptive routing algorithms greatly relies on the adopted network information. To the best our knowledge, previous routing algorithms utilize either spatial or temporal network information to improve performance. However, few works have established a framework on analyzing the network information nor showed how to integrate the spatial and temporal network information. In this paper, we define the network information region (NIR) framework for NoC systems. The NIR can indicate arbitrary combinations of network information and corresponding routing algorithms. We demonstrate how to apply NIR on analyzing the adaptive routing algorithms. To further demonstrate how NIR can help to integrate the spatial or temporal network information, we propose the ACO-based pheromone diffusion (ACO-PhD) adaptive routing framework based on the NIR. By diffusing the pheromone outward, spatial and temporal network information can be exchanged among adjacent routers. The range (i.e., size and shape) of the NIR is controllable by setting the parameters in the ACO-PhD algorithm. We show that we can reconfigure the ACO-PhD algorithm to each routing algorithm in its NIR subsets by adjusting the parameter settings. Finally, we implement and analyze the hardware design of corresponding router architecture. The results show an improvement of 4.86-16.93 percent on network performance and the highest area efficiency is achieved by the proposed algorithm.