A new class of distributed systems are beginning to employ DDS technology. These systems are characterized by broad geographic distribution, high aggregate data volumes, and narrow data interest within any particular node or local application. This presentation describes a set of enhancements to DDS and DDS-RTPS to better support such systems, in particular in the areas of data filtering and service discovery.

Approaches and techniques to integrating large-scale systems and systems of systems.

Analysis of the requirements of these systems and how specific features of DDS  can be leveraged to integrate these large systems. 

Monitoring a real-time distributed system for fault detection and identification is an extremely challenging problem. Faults may manifest themselves at a different node than where the actual error occurred, and may also be dependent on a particular sequencing of events and thus not easily reproducible. In addition the fault may be the loss of connectivity to some segment of the system, rendering a monitoring agent running in one segment of the system unable to communicate with other segments.

Classical approaches to distributed system security often rely on single-purpose entities to authenticate clients, enforce access and security policy, or at least distribute authentication tokens.  While these models are reasonable for controlling access to a centralized resource (such as a database), they are not suitable for highly-distributed and dynamic systems where fielded nodes with intermittent connectivity require access to real-time data.

The communication network providing real-time image sharing between the planning office and the warehouse for supply chain management is presented in this paper. Middleware plays a major role in developing distributed system efficiently for communication between image capturing devices (Vision Node) and image processing node as well as the distributed nodes. The image distribution over the network in real-time manner is useful to numerous logistic applications, such as quality control of pick-and-pack service, planning of cargo and pallet loading, and vehicles tracking.

Seaware is a publish-subscribe middleware used in multi-vehicle networked systems composed of autonomous and semi-autonomous vehicles and systems. Seaware provides a high level interface to network communications and may be deployed with a combination of heterogeneous components within a dynamic network.

Designing and constructing Real-Time Distributed Industrial Vision Systems (RT-DIVS) from scratch is very complicated task. RT-DIVS has Conflicting requirements such as reasonable development cost, ease of use, reusable code and high performance. The success key in building such systems is to recognize the need for middleware software. Middleware plays a major role in developing distributed systems efficiently.

This presentation exposes recent research in DDS Global-Data Space tools that leverage standard display models such as Microsoft Excel’s; it also explores the different categories of DDS run-time tools drawing requirements and specific examples from COTS tools commonly used to interact with data.

The Data-Distribution Service (DDS) is a widely used standard for distributing real-time publish-subscribe in performance and QoS-sensitive systems such as Combat Management Systems, Air Traffic Management and SCADA systems. As a consequence a lot of the “tactical” and “real-time” data in these systems “lives” in the DDS Global Data Space.

The DDS and JMS specifications offer alternative visions of publish-subscribe communication and have traditionally been deployed in different capacities; DDS provides a data distribution model based on strong typing and flexible QoS-based control over data delivery, while JMS provides a traditional messaging model based on loosely structured data and emphasizes a simple and portable programming model.