Quick convergence algorithm of ACO based on convergence grads expectation Online publication date: Thu, 10-May-2018
by Zhongming Yang; Yong Qin; Yunfu Jia
International Journal of High Performance Computing and Networking (IJHPCN), Vol. 11, No. 3, 2018
Abstract: While the ant colony optimisation (ACO) can find the optimal path through a network, there are too many iterations and the convergence speed is also very slow. This paper proposes the Q-ACO QoSR based on convergence expectation to meet the requirement of OoS routing for a real-time and highly efficient network. This algorithm defines index expectation function of link, and proposes convergence expectation and convergence grads. As for the multi-constraint QoS routing model, the algorithm controls the iteration and searches the optimal path that meets the QoS restriction condition under the condition of the faster convergence. This algorithm can find the optimal path by comparing the convergence grads in a faster and larger probability. This algorithm improves the ability of routing and convergence speed.
Online publication date: Thu, 10-May-2018
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