Internet of Things: a possible change in the distributed modeling and simulation architecture paradigm

Abstract

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.