• Title of article

    INR: A Programming Model for Developing APPs of Insect Intelligent Building

  • Author/Authors

    Zhao, Shuo College of Defense Engineering - Army Engineering University of PLA, China , Yang, Qiliang College of Defense Engineering - Army Engineering University of PLA, China , Xing, Jianchun College of Defense Engineering - Army Engineering University of PLA, China , Zhou, Qizhen College of Defense Engineering - Army Engineering University of PLA, China , Xue, Guangtong College of Defense Engineering - Army Engineering University of PLA, China , Chen, Wenjie College of Defense Engineering - Army Engineering University of PLA, China

  • Pages
    18
  • From page
    1
  • To page
    18
  • Abstract
    Insect Intelligent Building (I2B) is a novel platform of intelligent buildings. The outstanding feature of I2B is the decentralized network structure connected by smart nodes. I2B can employ APPs (applications) developed by various practitioners or programming fans to manage and control buildings. However, due to the unique parallel operation of I2B platform and the popularization of APP developers, there still exists no effective approach to supporting I2B APP development. To deal with the challenges and provide meaningful guidance for describing and developing I2B APP and motivating the prospective programming language design, we propose INR, a programming model for I2B APP development. Three submodels in INR, namely, Individual, Neighborhood, and Region, are defined and implemented, respectively, for describing different task requirements. Moreover, new mechanisms of Tag-based programming and Clustering operation are established to support the plug-and-play and parallel abilities of APPs in I2B. Finally, we apply the programming model into an application case to illustrate the developing pattern of the I2B APP and verify the effectiveness of our approach.
  • Keywords
    INR , Programming Model , Intelligent Building , Developing APPs
  • Journal title
    Scientific Programming
  • Serial Year
    2020
  • Record number

    2611120