Semantic Service Matchmaking(SSM)can be leveraged for mining the most suitable service to accommodate a diversity of user demands.However,existing research on SSM mostly involves logical or non-logical matching,leadin...Semantic Service Matchmaking(SSM)can be leveraged for mining the most suitable service to accommodate a diversity of user demands.However,existing research on SSM mostly involves logical or non-logical matching,leading to unavoidable false-positive and false-negative problems.Combining different types of SSM methods is an effective way to improve this situation,but the adaptive combination of different service matching methods is still a difficult issue.To conquer this difficulty,a hybrid SSM method,which is based on a random forest and combines the advantages of existing SSM methods,is proposed in this paper.The result of each SSM method is treated as a multi-dimensional feature vector input for the random forest,converting the service matching into a two classification problem.Therefore,our method avoids the flaws found in manual threshold setting.Experimental results show that the proposed method achieves an outstanding performance.展开更多
Distributed virtualization changes the pattern of building software systems. However, it brings some problems on dependability assurance owing to the complex social relationships and interactions between service compo...Distributed virtualization changes the pattern of building software systems. However, it brings some problems on dependability assurance owing to the complex social relationships and interactions between service components. The best way to solve the problems in a distributed virtualized environment is dependable service components selection. Dependable service components selection can be modeled as finding a dependable service path, which is a multiconstrained optimal path problem. In this paper, a service components selection method that searches for the dependable service path in a distributed virtualized environment is proposed from the perspective of dependability assurance. The concept of Quality of Dependability is introduced to describe and constrain software system dependability during dynamic composition. Then, we model the dependable service components selection as a multiconstrained optimal path problem, and apply the Adaptive Bonus-Penalty Microcanonical Annealing algorithm to find the optimal dependable service path. The experimental results show that the proposed algorithm has high search success rate and quick converges.展开更多
基金the National Natural Science Foundation of China(Nos.61872104 and 61502118)the National Science and Technology Major Project of China(No.2016ZX03001023-005)the Natural Science Foundation of Heilongjiang Province in China(No.F2016009)。
文摘Semantic Service Matchmaking(SSM)can be leveraged for mining the most suitable service to accommodate a diversity of user demands.However,existing research on SSM mostly involves logical or non-logical matching,leading to unavoidable false-positive and false-negative problems.Combining different types of SSM methods is an effective way to improve this situation,but the adaptive combination of different service matching methods is still a difficult issue.To conquer this difficulty,a hybrid SSM method,which is based on a random forest and combines the advantages of existing SSM methods,is proposed in this paper.The result of each SSM method is treated as a multi-dimensional feature vector input for the random forest,converting the service matching into a two classification problem.Therefore,our method avoids the flaws found in manual threshold setting.Experimental results show that the proposed method achieves an outstanding performance.
文摘Distributed virtualization changes the pattern of building software systems. However, it brings some problems on dependability assurance owing to the complex social relationships and interactions between service components. The best way to solve the problems in a distributed virtualized environment is dependable service components selection. Dependable service components selection can be modeled as finding a dependable service path, which is a multiconstrained optimal path problem. In this paper, a service components selection method that searches for the dependable service path in a distributed virtualized environment is proposed from the perspective of dependability assurance. The concept of Quality of Dependability is introduced to describe and constrain software system dependability during dynamic composition. Then, we model the dependable service components selection as a multiconstrained optimal path problem, and apply the Adaptive Bonus-Penalty Microcanonical Annealing algorithm to find the optimal dependable service path. The experimental results show that the proposed algorithm has high search success rate and quick converges.
