Performance Analysis of Kubernetes-Based Data Distribution Service

Kubernetes has risen as a de-facto standard solution for the efficient deployment, administration, and resource allocations of containers. Concurrently, the data distribution service (DDS) serves as a critical middleware technology for real-time data dissemination and transmission using publisher-subscriber pattern. DDS has been adopted in mission critical applica- tions across a range of internet of things (IoT) applications, where ensuring data integrity and reliability is crucial. Given the increasing interest in utilizing container virtualization for IoT application deployment and management, this study aims to optimize DDS application architecture within a Kubernetes framework. To achieve this goal, this study evaluated the performance by implementing containerized versions of OpenDDS, an open-source DDS solution, and RTI Connext DDS, another DDS implementation. The findings of this investigation serve as a benchmark to assist users in selecting an ap- propriate DDS solution and configuring an optimal DDS environment for DDS application execution within a Kubernetes framework.