Context: Data Distribution Service (DDS) is a standard data-centric publish–subscribe programming model and specification for distributed systems. DDS has been applied for the development of high performance distributed systems such as in the defense, finance, automotive, and simulation domains. Various papers have been written on the application of DDS, however, there has been no attempt to systematically review and categorize the identified obstacles. Objective: The overall objective of this paper is to identify the state of the art of DDS, and describe the main lessons learned and obstacles in applying DDS. In addition, we aim to identify the important open research issues. Method: A systematic literature review (SLR) is conducted by a multiphase study selection process using the published literature since the introduction of DDS in 2003. Results: We reviewed 468 papers that are discovered using a well-planned review protocol, and 34 of them were assessed as primary studies related to our research questions. Conclusions: We have identified 11 basic categories for describing the identified obstacles and the corresponding research challenges that can be used to depict the state-of-the-art in DDS and provide a vision for further research.
- Data Distribution Service (DDS)
- Systematic literature review