Recently, data-based services have played a significant role in satisfying various of requirements of people in social IoT. Since data is the basis of data-based service, therefore, it is significant to obtain trust data to enhance trust services. Few researches optimized trust issue of services from this point of view before. Therefore, based on this domain, this paper proposes a novel service computing framework to fundamentally form trust-based services via trust-based data in the social IoT, which mainly consists of two schemes. Data trustworthy is relevant to trustworthy of data providers in the social networks, therefore, we propose a trust evaluation scheme to compute trustworthy for data providers with assistance of trusted static sensor devices in edge computing, that comprehensively computes trustworthy by considering both temporal and quality factors. This process ensures to generate trust services from data source. Then, to improve precision of service evaluation in the updating process, a trust-based service evaluation scheme is proposed to compute service evaluation by fully considering trustworthy of users, which consists of two evaluation phases, local and global evaluation respectively. Finally, extensive experiment is conducted to validate efficiencies of the proposed scheme. Compared to traditional scheme, data trustworthiness can be improved by 26.4% and thus service trustworthy is improved by 26.4% accordingly. The precision of service evaluation is improved by 20.79%.

最近，基于数据的服务在满足人们在社交物联网中的各种需求方面发挥了重要作用。由于数据是数据化服务的基础，因此获取信任数据对于增强信任服务具有重要意义。以前很少有研究从这个角度优化服务的信任问题。因此，基于该领域，本文提出了一种新的服务计算框架，从根本上通过社交物联网中基于信任的数据形成基于信任的服务，该框架主要由两种方案组成。数据可信与社交网络中数据提供者的可信度相关，因此，我们提出了一种信任评估方案，在边缘计算中借助可信静态传感器设备计算数据提供者的可信度，通过考虑时间和质量因素来综合计算可信度。此过程确保从数据源生成信任服务。然后，为了提高更新过程中服务评价的精度，提出了一种基于信任的服务评价方案，充分考虑用户的可信度来计算服务评价，该方案由局部评价和全局评价两个评价阶段组成。最后，进行了广泛的实验以验证所提出方案的效率。与传统方案相比，数据可信度可提高26.4%，服务可信度相应提高26.4%。服务评价精度提高20.79%。为了提高更新过程中服务评价的精度，提出了一种基于信任的服务评价方案，充分考虑用户的可信度来计算服务评价，该方案包括两个评价阶段，分别是局部评价和全局评价。最后，进行了广泛的实验以验证所提出方案的效率。与传统方案相比，数据可信度可提高26.4%，服务可信度相应提高26.4%。服务评价精度提高20.79%。为了提高更新过程中服务评价的精度，提出了一种基于信任的服务评价方案，充分考虑用户的可信度来计算服务评价，该方案包括两个评价阶段，分别是局部评价和全局评价。最后，进行了广泛的实验以验证所提出方案的效率。与传统方案相比，数据可信度可提高26.4%，服务可信度相应提高26.4%。服务评价精度提高20.79%。进行了广泛的实验以验证所提出方案的效率。与传统方案相比，数据可信度可提高26.4%，服务可信度相应提高26.4%。服务评价精度提高20.79%。进行了广泛的实验以验证所提出方案的效率。与传统方案相比，数据可信度可提高26.4%，服务可信度相应提高26.4%。服务评价精度提高20.79%。