Open AccessMulti-PaaS Oriented IoT Dual Middleware Model in 5G Era
Author(s) -
Shuai Huang,
Shejiao Hu,
Hou Zheng-feng,
Zhao Niu,
Lin Rong Chen Wu
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1646/1/012088
Subject(s) - computer science , middleware (distributed applications) , cloud computing , service layer , application layer , service (business) , distributed computing , layer (electronics) , protocol (science) , software , operating system , computer network , medicine , chemistry , alternative medicine , economy , organic chemistry , pathology , economics
The PaaS platform based on cloud computing technology provides a large number of professional and flexible services in the fields of intelligent voice and computer vision. The large-scale application of 5G technology enables the software and hardware of the Internet of Things to use the PaaS service to improve the intelligence level of the system and reduce development costs. However, the problem of service invocation and service selection in the process of combining the IoT system with multiple PaaS platforms directly affects the interaction between the IoT perception layer and the application layer. This paper proposes a 5G multi-PaaS-oriented IoT dual middleware model. The unified communication protocol DMCP is designed. DMCP implements unified parsing of messages based on variable-length data items, which reduces the protocol conversion between the perception layer terminal device and multiple PaaS platforms. Complexity and high communication efficiency. Designed the PaaS service selection algorithm DMPS, DMPS comprehensively according to the equipment demand preferences and the overall performance of PaaS services, to achieve accurate service selection in the multi-PaaS platform at the application layer. Finally, examples and comparative tests verify the feasibility and effectiveness of the proposed model, protocol and algorithm.