Complex Problems Solution as a Service Based on Predictive Optimization and Tasks Orchestration in Smart Cities

作     者：Shabir Ahmad Jehad Ali Faisal Jamil Taeg Keun Whangbo DoHyeun Kim 

作者机构：Department of IT Convergence EngineeringGachon UniversitySujeong-GuSeongnam-SiGyeonggi-Do461-701Korea Department of Computer Engineeringand Department of AI Convergence NetworkAjou UniversitySuwonKorea Computer Engineering DepartmentJeju National UniversityJeju63243Korea 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2021年第69卷第10期

页      面：1271-1288页

核心收录：

学科分类：0831[工学-生物医学工程（可授工学、理学、医学学位）] 0401[教育学-教育学] 04[教育学] 0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 0805[工学-材料科学与工程（可授工学、理学学位）] 0701[理学-数学] 0801[工学-力学（可授工学、理学学位）] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：This research was supported by Energy Cloud R&D Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Science,ICT(2019M3F2A1073387) this research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(2018R1D1A1A09082919) this research was supported by Institute for Information&communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.2018-0-01456,AutoMaTa:Autonomous Management framework based on artificial intelligent Technology for adaptive and disposable IoT).Any correspondence related to this paper should be addressed to Dohyeun Kim 

主　　题：Internet of things complex problem solving task modeling embedded IoT systems predictive optimization artificial cognition task orchestration 

摘      要：Smart cities have different contradicting goals having no apparent *** selection of the appropriate solution,which is considered the best compromise among the candidates,is known as complex *** city administrators face different problems of complex nature,such as optimal energy trading in microgrids and optimal comfort index in smart homes,to mention a *** paper proposes a novel architecture to offer complex problem solutions as a service(CPSaaS)based on predictive model optimization and optimal task orchestration to offer solutions to different problems in a smart *** model optimization uses a machine learning module and optimization objective to compute the given problem’s *** task orchestration module helps decompose the complex problem in small tasks and deploy them on real-world physical sensors and *** proposed architecture is hierarchical and modular,making it robust against faults and easy to *** proposed architecture’s evaluation results highlight its strengths in fault tolerance,accuracy,and processing speed.