The Data Distribution Service (DDS) was started by the Object Management Group (OMG) in 2004. Currently, DDS is one of the contenders to support the Internet of Things (IoT) and the Industrial IOT (IIoT). DDS has also been used as a distributed simulation architecture. Given the anticipated proliferation of IoT and II devices, along with the explosive growth of sensor technology, can we expect this to have an impact on the broader community of distributed simulation? If it does, what is the impact and which distributed simulation domains will be most affected? DDS shares many of the same goals and characteristics of distributed simulation such as the need to support scale and an emphasis on Quality of Service (QoS) that can be tailored to meet the end user’s needs. In addition, DDS has some built-in features such as security that are not present in traditional distributed simulation protocols. If the IoT and II realize their potential application, we predict a large base of technology to be built around this distributed data paradigm, much of which could be directly beneficial to the distributed M&S community. In this paper we compare some of the perceived gaps and shortfalls of current distributed M&S technology to the emerging capabilities of DDS built around the IoT. Although some trial work has been conducted in this area, we propose a more focused examination of the potential of these new technologies and their applicability to current and future problems in distributed M&S.
The Internet of Things (IoT) and its data communications mechanisms such as the Data Distribution System (DDS) share properties in common with distributed modeling and simulation (M&S) and its protocols such as the High Level Architecture (HLA) and the Test and Training Enabling Architecture (TENA). This paper proposes a framework based on the sensor use case for how the two communities of practice (CoP) can benefit from one another and achieve greater capability in practical distributed computing.
KEYWORDS: Analytics, Data modeling, Computer simulations, Data processing, Computing systems, Sensors, Space operations, Control systems, Internet, Distributed computing
Modern software and network technologies are on the verge of enabling what has eluded the simulation and operational communities for more than two decades, truly integrating simulation functionality into operational Command and Control (C2) capabilities. This deep integration will benefit multiple stakeholder communities from experimentation and test to training by providing predictive and advanced analytics. There is a new opportunity to support operations with simulation once a deep integration is achieved. While it is true that doctrinal and acquisition issues remain to be addressed, nonetheless it is increasingly obvious that few technical barriers persist. How will this change the way in which common simulation and operational data is stored and accessed? As the Services move towards single networks, will there be technical and policy issues associated with sharing those operational networks with simulation data, even if the simulation data is operational in nature (e.g., associated with planning)? How will data models that have traditionally been simulation only be merged in with operational data models? How will the issues of trust be addressed?
KEYWORDS: Prototyping, Computer architecture, Modeling and simulation, Systems modeling, Computer simulations, Distributed interactive simulations, Visualization, Data modeling, 3D vision, Software development
Recent technological advances in web-based distributed computing and database technology have made possible a deeper and more transparent integration of some modeling and simulation applications. Despite these advances towards true integration of capabilities, disparate systems, architectures, and protocols will remain in the inventory for some time to come. These disparities present interoperability challenges for distributed modeling and simulation whether the application is training, experimentation, or analysis. Traditional approaches call for building gateways to bridge between disparate protocols and retaining interoperability specialists. Challenges in reconciling data models also persist. These challenges and their traditional mitigation approaches directly contribute to higher costs, schedule delays, and frustration for the end users. Osseus is a prototype software platform originally funded as a research project by the Defense Modeling & Simulation Coordination Office (DMSCO) to examine interoperability alternatives using modern, web-based technology and taking inspiration from the commercial sector. Osseus provides tools and services for nonexpert users to connect simulations, targeting the time and skillset needed to successfully connect disparate systems. The Osseus platform presents a web services interface to allow simulation applications to exchange data using modern techniques efficiently over Local or Wide Area Networks. Further, it provides Service Oriented Architecture capabilities such that finer granularity components such as individual models can contribute to simulation with minimal effort.
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