With the rapid growth of service scale, there are many services with the same functional properties but different non-flmctional properties on the Internet. There have been some global optimizing service selection alg...With the rapid growth of service scale, there are many services with the same functional properties but different non-flmctional properties on the Internet. There have been some global optimizing service selection algorithms for service selection. However, most of those approaches cannot fully reflect users＇ preferences or are not fully suitable for large-scale services selection. In this paper, an ant colony optimization （ACO） algorithm for the model of global optimizing service selection with various quality of srevice （QoS） properties is employed, and a user-preference based large-scale service selection algorithm is proposed. This algorithm aims at optimizing user-preferred QoS properties and selecting services that meet all user-defined QoS thresholds. Experiment results prove that this algorithm is very efficient in this regard.展开更多
基金Project supported by the Shanghai Leading Academic Discipline Project(Grant No.J50103)the Natural Science Foundation of Shanghai Municipality(Grant No.10ZR1411600)+1 种基金the Innovation Program of Education Commission of Shanghai Municipality(Grant No.10TX18)the New Generation Broadband Wireless Mobile Communication Network Key Technologies Research and Development Program of China 2010
文摘With the rapid growth of service scale, there are many services with the same functional properties but different non-flmctional properties on the Internet. There have been some global optimizing service selection algorithms for service selection. However, most of those approaches cannot fully reflect users＇ preferences or are not fully suitable for large-scale services selection. In this paper, an ant colony optimization （ACO） algorithm for the model of global optimizing service selection with various quality of srevice （QoS） properties is employed, and a user-preference based large-scale service selection algorithm is proposed. This algorithm aims at optimizing user-preferred QoS properties and selecting services that meet all user-defined QoS thresholds. Experiment results prove that this algorithm is very efficient in this regard.
