关键词: 物联网, 海量设备, 描述文件, 分布式, 优化, 聚类

Abstract:

Service description file, which is fundamental for the service-oriented architecture, can be used by the IoT sensing devices to accelerate resource discovery and searching processes.Currently, these files are mostly written manually by the device developers, this process is inefficient and fallible.The state-of-art method SPITFIRE can generate the devices' description in a semi-automatic way, but its configuration can be trivial and its accuracy still can be improved.In this paper, we proposed a novel automatic device description method, with which devices can automatically generate their individual description.We designed a clustering algorithm based on DBSCAN to infer the description of sensing device, taking advantages of existing descriptions and the data features of series gained by data sampling.A metric learning algorithm is also implemented to optimize the parameter used by the clustering algorithm.All the routines run independently on different devices, and no manual intervention is needed during the self-description process.Through simulation, we show that this method has a prominent advantage of precision over other state-of-art methods, making our method more suitable for the massive IoT devices.

Key words: internet of things, massive device, description file, distributed, optimization, clustering