SWoT Service Composition And Selection Of Context Adaptation Under Hierarchical Semantics

Semantic Web of Things(SWoT)is a solution to the internal contradictions of Internet of Things(IoT).It is not a simple superposition of IoT and Semantic Web,but an improvement on IoT.Semantic interoperability(semantic collaboration)is information exchange and information sharing at semantic level.SWoT services and other services are not completely split.Once the services in IoT are annotated with semantics and binded together with the mappings to their physical entity devices,which means,these services are possessed of the characteristics of SWoT services.Faced with massive and cumbersome network data,to respond quickly and accurately to dynamic and complex service requirements in IoT,some key correlated techniques on semantic interoperability based SWoT Services should necessarily be investigated.At present,some progress has been made on semantic interoperability based SWoT Services,but many key issues have still been unsolved,such as how to effectively solve the link prediction of semantic relationship,how to solve automatic extraction of service situation rules,how to efficiently and accurately obtain dynamic service combinations,and so on.To solve these closely related hot issues,this dissertation will systematically focus on the following three aspects,and the main research results are as follows:(1)To solve the problems of link prediction and automatic collaboration on semantic relationship between SWoT services in distributed environment,the corresponding solutions are proposed.The specific contents include:1)A three-level semantic service structured network model SNM4SS is proposed based on Semantic Link Network,which can express and reason rich semantic relations to collaborate SWoT services automatically.2)In order to construct this model,based on Markov Network,semantic relationship matrix between service events and edge deletion algorithm,a Markov Network construction algorithm SSEN and a dynamic update algorithm SSEN_U based on conditional mutual information for semantic service events are proposed respectively.3)Since the dynamic construction of semantic service event network needs to infer on service event link,a service event link inference algorithm SELR is proposed based on Markov Logic Networks and random walk strategy.This inference algorithmnot only can reduce the node number in inference operation,which avoids huge space-time overhead caused by closed Markov Logic Networks modeling,but also can more effectively predict the links on service event relationship in the multi-level semantic service structured network.Finally,the effectiveness of the proposed algorithm is verified by a series of experiments.(2)To provide more accurate semantic services and promote the efficiency and accuracy of service context rule extraction,a method on complex adaptive context rule extraction for semantic services is proposed,including:1)A rough set reduction algorithm DecDep_Red based on decision dependency degree is designed,which turns traditional logic knowledge granulation process into matrix calculation,and completes fast reduction of context redundancy attributes based on distinguishable relation and distinguishable reduction.2)A rule extraction algorithm DecDep_Rul based on decision dependency degree is proposed,which can quickly reduce the redundant value of context attributes and automatically convert the reduction results into decision rules.Finally,the simplicity and effectiveness of new method generated rules are verified by experiments.(3)To meet semantic service requirements in real-time and dynamically,and to obtain dynamic service combinations efficiently and precisely,a combination and discovery method for semantic services in intelligent manner is proposed.The specific contents include:1)Qos(CS)a novle model based on semantic matching degree and combined service quality is proposed and its related solving algorithm is designed.In this model,the local semantic matching between the sub-services of the composite service,the global matching between the demand and the service,the dependence between the input and output parameters of the service,and the QoS quality model of the composite service are all taken into account comprehensively.2)Then,based on model Qos(CS)and genetic algorithm,an intelligent composition and selection algorithm IC&S SWTS for Semantic Web of Things services is designed.The experiments reveal that the proposed algorithm can give a reasonable approximate optimal solution at lower cost.