Paper Info
Title
Regional ACO-based routing for load-balancing in NoC systems
Abstract
Ant Colony Optimization (ACO) is a problem-solving technique that was inspired by the related research on the behavior of real-world ant colony. In the domain of Network-on-chip (NoC), ACO-based adaptive routing has been applied to achieve load-balancing effectively with historical information. However, the cost of the ACO network pheromone table is too high, and this overhead grows fast with the scaling of NoC. In order to fix this problem, it is essential to model the ACO algorithm in more careful consideration of the system architecture, available hardware resource, and appropriate transformation from the ant colony metaphor. In this paper, we analyzed the NoC network characteristic and bring about the corresponding issues of implementing ACO on NoC. We proposed a Regional ACO-based routing (RACO) with static and dynamic regional table forming technique to reduce the cost of table, share pheromone information, and adopt look-ahead model for further load-balancing. The experimental results show that RACO can be implemented with less memory, less cost increase on scaling, and better performance of load-balancing compared to traditional ACO-based routing.
Year
DOI
Venue
2010
10.1109/NABIC.2010.5716323
NaBIC
Keywords
Field
DocType
optimisation,ant colony metaphor,network routing,regional ant colony optimization-based routing,static regional table forming technique,problem-solving technique,adaptive routing,load-balancing,ant colony optimization (aco),ant colony optimization network pheromone table,dynamic regional table forming technique,network-on-chip,look-ahead model,network-on-chip (noc),cost reduction,look ahead,network on chip,load balance,ant colony,ant colony optimization,system architecture,load balancing
Ant colony optimization algorithms,Load balancing (computing),Network routing,Computer science,Network on a chip,Systems architecture,Ant colony,Adaptive routing,Distributed computing
Conference
ISBN
Citations 
PageRank 
978-1-4244-7377-9
10
0.55
References 
Authors
13
4
Name
Order
Citations
PageRank
Hsien-Kai Hsin1785.90
En-Jui Chang21018.76
Chih-Hao Chao31829.90
An-Yeu Wu480181.68