The turn model for adaptive routing
ISCA '92 Proceedings of the 19th annual international symposium on Computer architecture
Proceedings of the 6th international workshop on Hardware/software codesign
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
The Odd-Even Turn Model for Adaptive Routing
IEEE Transactions on Parallel and Distributed Systems
IEEE Computational Intelligence Magazine
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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Networks-on-Chip (NoC) have been used as an interesting option in design of communication infrastructures for embedded systems, providing a scalable structure and balancing the communication between cores. Because several data packets can be transmitted simultaneously through the network, an efficient routing strategy must be used in order to avoid congestion delays. In this paper, ant colony algorithms were used to find and optimize routes in a mesh-based NoC, where several randomly generated applications have been mapped. The routing optimization is driven by the minimization of total latency in packets transmission between tasks. The simulation results show the effectiveness of the ant colony inspired routing by comparing it with general purpose algorithms for deadlock free routing.