Generation of feasible deployment configuration alternatives for Data Distribution Service based systems

Abstract

(DDS) has been defined by the OMG to provide 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. To support the analysis and design of a DDS-based distributed system, the OMG has proposed the DDS UML Profile. A DDS-based system usually consists of multiple participant applications each of which has different responsibilities in the system. These participants can be allocated in different ways to the available resources, which leads to different configuration alternatives. Usually, each configuration alternative will perform differently with respect to the execution and communication cost of the overall system. In general, the deployment configuration is selected manually based on expert knowledge. This approach is suitable for small to medium scale applications but for larger applications this is not tractable. In this paper, we provide a systematic approach for deriving feasible deployment alternatives based on the system design and the available physical resources. The system design is supported by the DDS UML profile that we have extended to support the generation of feasible deployment alternatives. Based on the modeled system design and physical resources, the feasible deployment alternatives can be algorithmically derived and automatically generated using the developed tools. We illustrate the approach for deriving feasible deployment alternatives of smart city parking system.

Systematic Approach for Generation of Feasible Deployment Alternatives for Microservices

“…In [10], conducted by an author involved in our study, a deployment approach has been proposed for parallel and distributed systems, and tool support [9] to examine this approach has been developed. This approach has also been implemented for Data Distribution Service-based systems [34].…”

Model-Driven Approach for Realization of Data Collection Architectures for Cyber-Physical Systems of Systems to Lower Manual Implementation Efforts

“…Some examples of model-driven development of system architectures in general and specifically for data collection can be found in literature. Tekinerdogan et al [ 29 ] developed an approach for the simulation and deployment optimization of DDS systems. Therefore, based on an abstract model of the systems, feasible deployment scenarios are derived automatically and simulated for their feasibility.…”

Distributed System Simulation Application Considering Data Distribution Service

“…DDS is a publish / subscribe message middleware, which provides a one to many real-time communication architecture and realizes information exchange in a distributed environment. DDS is regulated by the object management organization and defines a set of comprehensive quality of service (QoS) policies to achieve the matching of data transmission standards [10]. All participant entities in the DDS communication architecture, as well as the read and write operations of the participant entities, need to bind a special QoS policy.…”