A Two-Phase Context-Sensitive Service Composition Method with the Workflow Model in Cyber-Physical Systems

The requirement of integrating a large number of heterogeneous cyber and physical entities in cyber-physical systems (CPSs) motivates the use of a service-oriented architecture (SOA), which can support the composition of two or more available functionalities to form a complex service. This paper pre...

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Bibliographic Details
Published in:2014 IEEE 17th International Conference on Computational Science and Engineering pp. 1475 - 1482
Main Authors: Tao Wang, Chongli Niu, Lianglun Cheng
Format: Conference Proceeding
Language:English
Published: IEEE 01.12.2014
Subjects:
Abstracts
Conferences
context-sensitive
Cyber-physical system
Integrated circuits
Optimization
Quality of service
Scientific computing
service combination optimization
service composition
service discovery
Silicon
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Summary:The requirement of integrating a large number of heterogeneous cyber and physical entities in cyber-physical systems (CPSs) motivates the use of a service-oriented architecture (SOA), which can support the composition of two or more available functionalities to form a complex service. This paper presents a context-sensitive service composition framework in CPS with dependability requirements. Firstly, an ontology model is proposed for context-sensitive specification of the service capabilities of physical entities. Then we propose a service spanning tree (SST) based hierarchical service management scheme for efficient atomic service clustering and management, and a service workflow spanning graph (SWSG) is used to map the workflow-based abstract process model of a given task to multiple sets of atomic service instances. Finally, we present a two-phase context-sensitive service composition optimization mechanism, which is able to select out the optimal service providers to implement the task effectively and dependably. The experiment results show that the precision and efficiency of service discovery, the success ratio of workflow execution, as well as the performance of service combination optimization algorithm have been greatly improved with our proposed method.
DOI:10.1109/CSE.2014.275