In order to make cloud users get credible, high-quality composition of services, the trust quality of service aware(TQoS-aware) based parallel ant colony algorithm is proposed. Our approach takes the service credibili...In order to make cloud users get credible, high-quality composition of services, the trust quality of service aware(TQoS-aware) based parallel ant colony algorithm is proposed. Our approach takes the service credibility as the weight of the quality of service, then calculates the trust service quality T-QoS for each service, making the service composition situated in a credible environment. Through the establishment on a per-service T-QoS initialization pheromone matrix, we can reduce the colony's initial search time. By modifying the pheromone updating rules and introducing two ant colonies to search from different angles in parallel,we can avoid falling into the local optimal solution, and quickly find the optimal combination of global solutions. Experiments show that our approach can combine high-quality services and the improvement of the operational success rate. Also, the convergence rate and the accuracy of optimal combination are improved.展开更多
基金supported by the National Natural Science Foundation of China(6140224161170065+13 种基金61373017611710536110319561203217612011636120200461202354)Scientific&Technological Support Project(Industry)of Jiangsu Province(BE2012183BE2012755)Natural Science Key Fund for Colleges and Universities of Jiangsu Province(11KJA52000112KJA520002)the Natural Science Fund for Colleges and Universities of Jiangsu Province(13KJB520017)Scientific Research&Industry Promotion Project for Higher Education Institutions(JHB2012-7)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)(yx002001)
文摘In order to make cloud users get credible, high-quality composition of services, the trust quality of service aware(TQoS-aware) based parallel ant colony algorithm is proposed. Our approach takes the service credibility as the weight of the quality of service, then calculates the trust service quality T-QoS for each service, making the service composition situated in a credible environment. Through the establishment on a per-service T-QoS initialization pheromone matrix, we can reduce the colony's initial search time. By modifying the pheromone updating rules and introducing two ant colonies to search from different angles in parallel,we can avoid falling into the local optimal solution, and quickly find the optimal combination of global solutions. Experiments show that our approach can combine high-quality services and the improvement of the operational success rate. Also, the convergence rate and the accuracy of optimal combination are improved.
