GASANT: An ant-inspired least-cost QoS multicast routing approach based on genetic and simulated annealing algorithms | Zendy

Morteza Damanafshan | Zendy; Ehsan KhosrowshahiAsl | Zendy; Maghsoud Abbaspour | Zendy

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GASANT: An ant-inspired least-cost QoS multicast routing approach based on genetic and simulated annealing algorithms

Author(s) -

Morteza Damanafshan,

Ehsan KhosrowshahiAsl,

Maghsoud Abbaspour

Publication year - 2014

Publication title -

international journal of computers communications and control

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.422

H-Index - 33

eISSN - 1841-9844

pISSN - 1841-9836

DOI - 10.15837/ijccc.2012.3.1384

Subject(s) - multicast , ant colony optimization algorithms , computer science , simulated annealing , distributed computing , routing (electronic design automation) , quality of service , genetic algorithm , mathematical optimization , population , computer network , algorithm , mathematics , machine learning , medicine , environmental health

Computing least-cost multicast routing tree while satisfying QoS constraints has become a key issue especially by growing communication networks. To solve this problem, a triplex algorithm called GASANT which is based on Ant Colony Optimization (ACO), Genetic Algorithm (GA), and Simulated Annealing (SA) has been proposed in this paper. Through ACO, we have both provided improved initial population to feed GA and reduced search process. Besides, SA has been deployed to refrain GA from getting stuck into local optimum solutions. Simulation results assert that GASANT not only has high speed convergence time, but also generates least-cost multicast routing trees of high QoS.

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