Song, H., Huang, G., Xiong, Y.F., Chauvel, F., Sun, Y.C. and Mei, H. (2010) Inferring Meta-Models for Runtime System Data from the Clients of Management APIs. Proceedings of the 13th International Conference on Model Driven Engineering Languages and Systems, Oslo, 3-8 Norway 2010, 168-182.
http://dx.doi.org/10.1007/978-3-642-16129-2_13

has been cited by the following article:

• TITLE: Management of Intelligent Campus Wireless Sensor Networks Based on Runtime Model

  AUTHORS: Ping Zhang, Jianzhong Wang

  KEYWORDS: Wireless Sensor Networks, Intelligent Campus, Runtime Model, Intelligent Campus Internet of Things, Software Architecture

  JOURNAL NAME: Journal of Computer and Communications, Vol.3 No.7, July 17, 2015

  ABSTRACT: To quick customize and develop intelligent campus internet of things (ICIOT) system more efficiently, in this paper an approach based on runtime model to managing intelligent campus wireless sensor networks is proposed. Firstly, manageability of intelligent campus wireless sensors is abstracted as runtime models which automatically and immediately propagate any observable runtime changes of target resources to corresponding architecture models. Then, a composite model of intelligent campus wireless sensors is constructed through merging their runtime models in order to manage different kinds of devices in a unified way. Finally, a customized model is constructed according to the personalized management requirement and the synchronization between the customized model and the composite model is ensured through model transformation. Thus, all the management tasks can be carried through executing operating programs on the customized model. In the part of the teaching area schools conducted experiments and compared with the traditional method, this method can be more effective management of campus facilities, more energy efficient and orderly, which can reach a 16.7% energy saving.