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 ...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 scalefree 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.展开更多
基金supported in part by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(NRF2019R1A2C1006159)and(NRF-2021R1A6A1A03039493).
文摘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 scalefree 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.
