GDBApex: A graph‐based system to enable efficient transformation of enterprise infrastructures

Abstract

Summary Graph‐based database engines have been developed by different researchers and companies. Many optimization methods have been integrated within these engines to enable fast and efficient data processing. However, many small‐ and medium‐size organizations have not changed their database infrastructures and still rely on a relational management modeling approach. This limits their service performance, especially in today's large‐scale data processing requirements. Transformation to the use of graph‐based modeling and design is not a straightforward process. In order to make a successful transformation, correct process semantics as well as the design of vertices, edges, labels, and process relations are required. The goal of this article is to help small‐ and medium‐size organizations make this transformation successful in order to satisfy customers' expectations and meet the requirements of data‐intensive applications. The proposed graph‐based modeling approach uses a graph structure for semantic queries and applies software engineering design principles. Moreover, it provides a case study with many data transactions. The system outperformed relational database management systems by an order of magnitude. Scalability of the system is examined and compared with the regular relational‐based modeling. In addition, a load balancing solution is used to achieve high scalability.

A Semantic Model of Internet of Things for Intelligent Translation and Learning

“…Semantic technology is applied to the Internet of things. rough semantic annotation of the information of Internet of things devices, people, things, and devices in the Internet of things can have a unified recognition language [13]. rough the devices in the Internet of things and the semantic method based on ontology, we can accurately find the information on the network and make further reasoning on the information according to the existing knowledge, so as to effectively realize the network intelligence.…”