Title :
Improved ant colony algorithm with multi-strategies for QoS routing problems
Author :
Ding, Genhong ; Shi, Lei ; Wu, Xingliang ; Zhang, Yan
Author_Institution :
Coll. of Sci., Hohai Univ., Nanjing, China
Abstract :
The stochastic state of the network should be given full consideration when a QoS routing algorithm is designed. This paper proposed an improved ant colony algorithm with multi-strategies for solving QoS routing problems by changing pheromone update rule and substituting the piecewise function for the probability constant which is chosen by ants when a route is selected. By instance simulation the experimental results show that the success rate of the improved ant colony algorithm in solving QoS routing problems and the ratio to obtain the optimal solution reach up to 99.81% and 99.65% respectively. The results are much better than those obtained by the basic ant colony algorithm. The improved algorithm can solve the probabilistic QoS network routing problem effectively.
Keywords :
ant colony optimisation; probability; quality of service; stochastic processes; telecommunication network routing; QoS network routing problem; ant colony algorithm; pheromone update rule; piecewise function; probability constant; stochastic state; Algorithm design and analysis; Bandwidth; Cities and towns; Delay; Educational institutions; Quality of service; Routing; QoS; ant colony algorithm; routing algorithm; simulation;
Conference_Titel :
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4577-2130-4
DOI :
10.1109/ICNC.2012.6234536