Intelligent Offloading for Collaborative Smart City Services in Edge Computing

• Published in: IEEE internet of things journal Vol. 7; no. 9; pp. 7919 - 7927
• Main Authors: Xu, Xiaolong, Huang, Qihe, Yin, Xiaochun, Abbasi, Mahdi, Khosravi, Mohammad Reza, Qi, Lianyong
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01-09-2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Collaboration; Collaborative service; Computer simulation; Edge computing; Entropy (Information theory); intelligent offloading; Internet of Things; Internet of Things (IoT); Privacy; Provisioning; Resource allocation; Smart cities; Time factors; Transport buildings, stations and terminals
• ISSN: 2327-4662; 2327-4662
• DOI: 10.1109/JIOT.2020.3000871

Smart city is a fast-developing system enabled by Internet of Things (IoT) with massive collaborative services (e.g., intelligent transportation and collaborative diagnosis). Generally, the terminals in the smart city are provided with limited computing ability, thus incapable of processing the diversified and cross-application services. Faced with insufficient resource provisioning for the collaborative smart city services, edge computing is emerged as a novel paradigm to provide city terminals with more processing capacity. Nevertheless, as there is a tremendous threat of disclosing private information in the offloading of collaborative services, it is imperative to improve privacy security in the edge computing. With the intention of addressing the privacy disclosure, an intelligent offloading method (IOM) for smart city, realizing privacy preservation, improving offloading efficiency, and promoting edge utility, is proposed. Technically, the information entropy mechanism is employed to be integrated with edge computing to obtain the balance between privacy preservation and collaborative service performance. Eventually, the simulation analysis is implemented to verify the effectiveness of IOM.