Intelligent Service Search Model Using Emerging Technologies

Farhan Amin, Gyu Sang Choi
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Abstract

In recent years, the Internet of Things (IoT) has played a vital role in providing various services to users in a smart city. However, searching for services, objects, data, and frameworks remains a concern. The technological advancements in Cyber-Physical Systems (CPSs) and the Social Internet of Things (SIoT) open a new era of research. Thus, we propose a Cyber-Physical-Social Systems (CPSs) for service search. Herein, service search and object discovery operation carries with the suitable selection of friends in the network. Our proposed model constructs a graph and performs social network analysis (SNA). We suggest degree centrality, clustering, and scale-free emergence and show that a rational selection of friends per service exploration increases the overall network navigability. The efficiency of our proposed system is verified using real-world datasets based on service processing time, path length, giant component, and network diameter. The simulation results proved that our proposed system is efficient, robust, and scalable.
利用新兴技术的智能服务搜索模型
近年来,物联网(IoT)在为智慧城市用户提供各种服务方面发挥了至关重要的作用。然而,搜索服务、对象、数据和框架仍然是一个问题。网络物理系统(cps)和社会物联网(SIoT)的技术进步开启了一个新的研究时代。因此,我们提出了一个用于服务搜索的网络-物理-社会系统(cps)。其中,服务搜索和对象发现操作伴随着网络中朋友的适当选择。我们提出的模型构建一个图并执行社会网络分析(SNA)。我们提出了度中心性、聚类和无标度涌现,并表明每个服务探索的合理朋友选择增加了整体网络的可导航性。使用基于服务处理时间、路径长度、巨型组件和网络直径的真实数据集验证了我们提出的系统的效率。仿真结果证明了系统的有效性、鲁棒性和可扩展性。
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