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Independent quality of service(QoS)registration center is difficult to monitor QoS with lots of requests in Internet environment with a large number of services and lots of service requests.It is able to reduce the load and decrease the failure rate by using multiple QoS registration centers to monitor QoS of some services with lots of requests.In addition,the heterogeneous QoS data close to user’s habitual expression and adapts to the environment with complexity and uncertainty.This paper introduces a novel Web service composition algorithm based on technique for order preference by similarity to an ideal solution(TOPSIS)(WSCA_TOPSIS)to solve the above difficulties for the first time.WSCA_TOPSIS can support multiple decision-makers and heterogeneous QoS data.It includes three main steps:normalizing decision matrix,evaluating alternatives synthetically and evaluating group alternatives synthetically.Other contributions of the paper include a novel algorithm of aggregating QoS and a set of experiments that demonstrate the benefits and effectiveness of our approach.Experimental results show that the proposed algorithm can better support Web service composition with heterogeneous QoS data and multiple decision-makers.
Independent quality of service (QoS) registration center is difficult to monitor QoS with lots of requests in Internet environment with a large number of services and lots of service requests. It is able to reduce the load and decrease the failure rate by using multiple QoS registration centers to monitor QoS of some services with lots of requests. In addition, the heterogeneous QoS data close to user’s habitual expression and adapts to the environment with complexity and uncertainty. This paper introduces a novel Web service composition algorithm based on technique for order preference by similarity to an ideal solution (TOPSIS) (WSCA_TOPSIS) to solve the above difficulty for the first time. WSCA_TOPSIS can support multiple decision-makers and heterogeneous QoS data. It includes three main steps: normalizing decision matrix, addressing alternatives synthetically and evaluating group alternatives synthetically. Other contributions of the paper include a novel algorithm of aggregating QoS and a set of experiments that demonstrate the benefits and effectiveness of our approach. Experimental results show that the proposed algorithm can better support Web service composition with heterogeneous QoS data and multiple decision-maker.