Cultural distance for service composition in cyber–physical–social systems

Abstract

Cyber–physical–social systems can be organized as workflows that interconnect the resources in physical, cyber, and social worlds in real time. This integration of these worlds with various resource as services requires service composition approaches that can integrate essential components and share relevant information in these worlds. Although numerous service composition approaches have been proposed, there still exist many challenges in the representation of user preference of service composition in cyber–physical–social systems. In this paper, a service composition approach based on the cultural distance is proposed to improve the reliability and satisfaction. This approach employs the cultural distance to measure the user preference quantitatively in a simple mathematical form. The user preference degree and the user preference vector are defined to select the service from a global view and an accurate point separately. Then, a 0-1 mixed-integer programming algorithm is used to identify the most suitable services for composition. The experimental results based on two real-world datasets show that the proposed approach for representing the user preference quantitatively is more simple and effective than other approaches. In a word, the proposed approach yields satisfactory performance of service composition in CPSS with regard to the user preference and efficiency.