- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
Service social network is an umbrella term used to describe several interaction and collaboration phenomena that are shaping the future of how services are provided on the cloud manufacturing platform. Social relationship plays an important role when services are orchestrated with each other to build manufacturing business process, a role which has not been adequately investigated in previous research. The existing manufacturing service composition methods consider functional qualifications and Quality of Service (QoS) as major competitiveness factors. It is difficult to adopt them to situations where synergy effect is required and social relationships have significant impact on ensuring effective resources, information and knowledge hand-off in the complex task process. Focusing on the social collaboration feature of manufacturing services, a service composition method based on synergy effect is proposed. According to the data of service interaction and cooperation on the cloud platform, we extract and describe service social network and five kinds of relationships, namely interactive transaction, co-community, physical distance, resource-related, social similarity relationship. Based on the calculation of these relationships strength, the service synergy network is derived through the weighted aggregation. A service selection model that maximizes the overall synergy effect based on collaboration requirement is presented. The validity and advantages of our model and algorithm is validated through simulation experiment of intelligent automobile cloud manufacturing. The results show that our approach is not only efficient, but also finds better service scheme in line with the actual manufacturing scenario.
This paper presents an approach for composing services that considers social relationships between services. Successful completion of complex tasks requires building dynamic alliances between manufacturing services as all the providers need to work as a team, where selected services corresponding to sub-tasks must make sure that resource hand off, information and knowledge delivery are smooth and efficient. Hence, not only the individual competitiveness but the synergy effect between candidate services should be considered as important criterion for service composition. In cloud platform where services have social relationships, which can create synergy effect, and social network analysis is critical for finding appropriate services for creating dynamic alliance. Since this area has not been thoroughly researched before, the approach presented in this paper improves the quality of service composition and significantly contribute to literature in this area. The major contributions of the proposed method are described below.
First, we provide new insight into IoS that integrates social network and synergy theory and adapts them to the new context. A new framework for service selection that considers the service synergy has been proposed. Based on the analysis of social interaction behavior, we defined five dimensions, namely, interactive transaction, co-community, physical distance, resource related, social similarity relationships and constructed multidimensional SSN, which can provide a basis for research in IoT, cloud manufacturing and service orchestration in the future. Second, present a service weight synergy network model to calculate the comprehensive synergy effect based on aggregation five relations strength: this model can serve as a basis for quantitative research on service assets. Third, a novel service composition model based on synergy effect that emphasizes collaboration factor is proposed. It overcomes the limitations of existing methods that only consider the functional and QoS attributes, and enhances the probability of successful collaboration among potential partners in SSN. Additionally, using an intelligent automobile manufacturing case experiment, the results reveal that our approach considering collaboration factor generate more efficient solution when organizing a business process with many services.