The next generation operational data historian for IoT based on informix

In the era of the Internet of Things (IoT), increasing numbers of applications face the challenge of using current data management systems to manage the massive volume of operational data gener-ated by sensors and devices. Databases based on time series data model, like PI Server, are developed to handle such data with operational technology (OT) characteristics (high volume, long lifecycle, and simple format). However, while achieving excellent write performance, these database systems provide limited query capabilities. In this paper, we present the next-generation Opera-tional Data Historian (ODH) system that is based on the IBM© Informix© system architecture. The system combines the write advantages of the existing time series databases and the ability to run complex queries in SQL. We demonstrate the high efficiency of our system for both writing and querying data with a variety of case studies in the industries of Energy and Utilities and con-nected vehicles. In addition, we present the first benchmark, IoT-X, to evaluate technologies on operational data management for IoT.

[1]  Amit P. Sheth,et al.  Linked sensor data , 2010, 2010 International Symposium on Collaborative Technologies and Systems.

[2]  G. Clark,et al.  Reference , 2008 .

[3]  J. C. Hale,et al.  Historical data recording for process computers , 1981 .

[4]  Abraham Silberschatz,et al.  HadoopDB: An Architectural Hybrid of MapReduce and DBMS Technologies for Analytical Workloads , 2009, Proc. VLDB Endow..

[5]  Michael Stonebraker,et al.  A comparison of approaches to large-scale data analysis , 2009, SIGMOD Conference.