Dynamic Cloud Service Composition Based on Context Temporal Information and Fuzzy Entropy Weight TOPSIS

Many non-functional attributes of QoS will change dynamically with the location and time of users, which makes QoS present uncertainty. In this paper, context temporal information is used to obtain historical and real-time QoS information. On the basis of this, the fuzzy entropy weight TOPSIS method is used to solve the fuzziness of user's personal preference and the uncertainty of QoS. A context TOPSIS algorithm based on temporal context information QoS and integrating user's preference is designed. The simulation results show that the designed context TOPSIS algorithm can obtain the QoS context timing information timelier, and obtain the user's preference weight more accurately, so that the web service can be selected to meet the user's personal needs.