Cloud-based ubiquitous object sharing platform for heterogeneous logistics system integration. (October 2018)

• Record Type: Journal Article
• Authors: Li, Ming; Lin, Peng; Xu, Gangyan; Huang, George Q.
• Is Part Of: Advanced engineering informatics. Volume 38(2018)
• Page Start: 343
• Page End: 356
• Publication Date: 2018-10
• Subjects: Kernel-based agent -- Computing gateway -- Heterogeneous system integration -- Intelligent infrastructure; Computer-aided engineering -- Periodicals; Engineering -- Data processing -- Periodicals; 620.00285
• DOI: 10.1016/j.aei.2018.08.010
• Languages: English
• ISSNs: 1474-0346

Abstract

Abstract: The intelligence of infrastructure gradually becomes the straw for logistics enterprises to make data-based or date-driven optimization. The integration of heterogeneous logistics systems with existing enterprise information systems is one of the most critical steps to achieve the intelligent infrastructure. Unfortunately, the integration is always a time-consuming process with heavy investment, which suppresses the longings of enterprises, especially for small and medium enterprises (SMEs). Aiming at simplifying the system integration, this paper proposed a cloud-based ubiquitous object sharing platform (CUOSP) to share the integration across SMEs based on the concept of sharing economy. CUOSP acts as a middleware system to make heterogeneous logistics systems universal plug-and-play (UPnP) for enterprise information systems. A kernel-based agent (KBA) is designed as the sharing entity of physical systems. It maintains the features of physical systems and is scalable for different application scenarios. A series of cloud gateway services are emerged not only to provide the basic running and sharing environment, but also to remedy KBA's weaknesses in computing capacity. A prototype system is developed and implemented based on the framework of CUOSP and a laboratory case according to the consolidation scenario in E-commerce logistics is demonstrated. Comparison experiments are also conducted to explore the real-time and multitasking capacity of KBAs with different kernel characteristics and different computing resources.