Papers

The distributed real-time system composed of industrial robots usually needs to meet the support of low-latency, high-reliability data transmission and service invocation. Based on the Data Distribution Service (DDS) publish-subscribe communication paradigm, this paper designs a service integration framework model called Dynamic-DDS-RPC with a request-response mechanism to achieve low-latency and flexible configuration of the robot service remote procedure call function. First of all, we use JSON to implement a set of service description specifications to support service definition and program interface implementation, and uses dynamic library automatic loading technology to solve the problem that DDS-RPC does not support dynamic loading and discovery of services.

Secondly, we implement a topic-centric service request-response mechanism based on the publish-subscribe communication mode of DDS, and realize low-latency data communication. Finally, we develop a robot middleware software based on the framework, and use the middleware to compare the performance of the service-request response speed with the WebService-based middleware and the DDS-RPC-based middleware. The results show that the service integration framework proposed in this paper can realize the remote procedure call function with low latency and high flexible configuration, which verifies the effectiveness of the framework.

In this paper, we develop a power system adaptive and predictive management strategy for integrating large-scale renewable energy penetration in the power systems. The variability and uncertainty of renewable energy increase the difficulty of the power system management extremely. Also, the problem becomes more challenging if the variable energy has large penetration. The proposed strategy depends on robust optimization under unforeseen contingencies and uncertain changes in intermittent resources output. Adaptive model predictive control is used to manipulate the power system energy unit's set-points to maximize profit at maximum security. Simulation studies are conducted to validate the effectiveness of the introduced strategy. The results show that the proposed strategy is successfully able to maximize profit not only in normal operation case but also in the case of severe contingencies. In addition to, the management strategy is flexible for customized plans of the grid operator and it is scalable for system extensions. The developed strategy helps the management system to increase the free renewable energy sources share at the minimum cost with maximum security.

Partitioning is a widespread technique that enables the execution of mixed-criticality applications in the same hardware platform. New challenges for the next generation of partitioned systems include the use of multiprocessor architectures and distribution standards in order to open up this technique to a heterogeneous set of emerging scenarios (e.g., cyber-physical systems). This work describes a system architecture that enables the use of data-centric distribution middleware in partitioned real-time embedded systems based on a hypervisor for multi-core, and it focuses on the analysis of the available architectural configurations. We also present an application-case study to evaluate and identify the possible trade-offs among the different configurations.

IETF impressively defined internet interoperation across 30 years of unforeseeable syntax API. IOT needs similar future proof, but for connected things' composable semantics, security, reliability and Quality of Service (QoS). This paper overviews these with simplifying tradeoffs from a bottom up approach using Data Distribution Service (DDS). Then high level semantic additions to DDS are suggested for semantics that are backward compatible, while maintaining the security, reliability and QoS of DDS. Finally, further work is suggested toward out-of-the-box composability and interoperability between common IoT data models and compliant solutions.

Refining and petrochemical processing facilities utilize various process control applications to raise productivity and enhance plant operation. Client–server communication model is used for integrating these highly interacting applications across multiple network layers utilized in distributed control systems.

This paper presents an optimum process control environment by merging sequential and regulatory control, advanced regulatory control, multivariable control, unit-based process control, and plant-wide advanced process control into a single collaborative automation platform to ensure optimum operation of processing equipment for achieving maximum yield of all manufacturing facilities.

The main control module is replaced by a standard real-time server. The input/output racks are physically and logically decoupled from the controller by converting them into distributed autonomous process interface systems. Real-time data distribution service middleware is used for providing seamless cross-vendor interoperable communication among all process control applications and distributed autonomous process interface systems.

Detailed performance analysis was conducted to evaluate the average communication latency and aggregate messaging capacity among process control applications and distributed autonomous process interface systems.

The overall performance results confirm the viability of the new proposal as the basis for designing an optimal collaborative automation platform to handle all process control applications. It also does not impose any inherent limit on the aggregate data messaging capacity, making it suitable for scalable automation platforms. 

Modern complex embedded systems are evolving into mixed-criticality systems in order to satisfy a wide set of non-functional requirements such as security, cost, weight, timing or power consumption. Partitioning is an enabling technology for this purpose, as it provides an environment with strong temporal and spatial isolation which allows the integration of applications with different requirements into a common hardware platform. At the same time, embedded systems are increasingly networked (e.g., cyber-physical systems) and they even might require global connectivity in open environments so enhanced communication mechanisms are needed to develop distributed partitioned systems. To this end, this work proposes an architecture to enable the use of data-centric real-time distribution middleware in partitioned embedded systems based on a hypervisor. This architecture relies on distribution middleware and a set of virtual devices to provide mixed-criticality partitions with a homogeneous and interoperable communication subsystem. The results obtained show that this approach provides low overhead and a reasonable trade-off between temporal isolation and performance.

Condition-based maintenance (CBM) of naval assets is preferred over scheduled maintenance because CBM provides a window into the future of each asset’s performance, and recommends/schedules service only when needed. In practice, the asset’s condition indicators must be reduced, transmitted (off-ship), and mined using shore-based predictive analytics. Real-Time Innovations (RTI), Inc. in collaboration with the University of South Carolina CBM Center is developing a comprehensive, multi-disciplinary technology platform for advanced predictive analytics for the Navy’s mechanical, electrical, and IT assets on-board ships. RTI is developing an open, extensible, data-centric bus architecture to integrate shipboard asset monitoring data with shore-based predictive analysis tools. The interoperability challenge is addressed using the Model-Driven Architecture (MDA) by transforming sensor data to rigorously specified standard data models. Our MDA process includes open standards such as the OMG Data Distribution Service (DDS) and Open System Architecture for Condition-Based Maintenance (OSA-CBM), both of which have enjoyed success in the Navy. Furthermore, the Navy’s Information Assurance (IA) requirements are implemented using the OMG Secure-DDS standard. In summary, the technology will improve combat readiness using a truly interoperable data-bus for exchanging CBM data from ship-to-shore while reducing distractions to the sailors, standby inventory requirements, and decision time for analysts.

The Data Distribution Service (DDS) standard defines a data-centric distribution middleware that supports the development of distributed real-time systems. To this end, the standard includes a wide set of configurable parameters to provide different degrees of Quality of Service (QoS). This paper presents an analysis of these QoS parameters when DDS is used to build reactive applications normally designed under an event-driven paradigm, and shows how to represent them using the real-time end-to-end flow model defined by the MARTE standard. We also present an application-case study to illustrate the use and modeling of DDS in next-generation distributed real-time systems.

The Internet of Things (IoT) paradigm has given rise to a new class of applications wherein complex data analytics must be performed in real-time on large volumes of fast-moving, heterogeneous sensor-generated data. Such data streams are often unbounded and must be processed in a distributed and parallel manner to ensure timely processing and delivery to interested subscribers. Dataflow architectures based on event-based design have served well in such applications because events support asynchrony, loose coupling, and helps build resilient, responsive and scalable applications. However, a unified programming model for event processing and distribution that can naturally compose the processing stages in a dataflow while exploiting the inherent parallelism available in the environment and computation is still lacking. To that end, we investigate the benefits of blending Functional-style Reactive Programming with data distribution frameworks for building distributed, reactive, and high-performance stream-processing applications. Specifically, we present insights from our study integrating and evaluating Microsoft .NET Reactive Extensions (Rx) with OMG Data Distribution Service (DDS), which is a standards-based publish/subscribe middleware suitable for demanding industrial IoT applications. Several key insights from both qualitative and quantitative evaluation of our approach are presented.

This whitepaper describes a powerful C++ template library to allow users to describe their types in plain C++ and use those types directly for data-centric communication over DDS. The library transforms native C++ types into equivalent run-time TypeObject representation as specified in the DDS-XTypes standard. The library obviates the need to describe application-level data-types in external representations, such as IDL, XSD, XML, and DynamicData. The users of the library can use the full expressive power of native C++ to encapsulate the application-level data-types and use the same data-types for data distribution over DDS. The types may include all the standard template library containers (e.g., vector, list, map, unordered containers, etc.), raw pointers, smart pointers, and many more. The restrictions imposed by popular serialization/deserialization tools are eliminated. The application-level data are written directly using DDS.

As automotive electronic system design evolves, so must the HiL testbench and automotive test platforms. the fundamental functional design approach has been modular and ECU-centric, but the ECU count has steadily increased. the next big shift is to achieve functionality through the integration of multiple ECUs. Audi is responding to these challenges by radically re-thinking the architecture of the HiL test platform and defining a next generation approach. the new approach introduces the concept of a HiL-Bus to integrate the functionality of multiple existing HiL sub-systems and meet the needs of a modular best-in-class test ecosystem. By using a data-oriented approach the complexity of the testbench is reduced making it easier to integrate hardware and software products from different vendors. one of the enabling technologies (Connext DDS) is developed by Real-Time Innovations Inc.

The OMG Data Distribution Service (DDS) has been deployed in many mission-critical systems and increasingly in Internet of Things (IoT) applications since it supports a loosely-coupled, data-centric publish/subscribe paradigm with a rich set of quality-of-service (QoS) policies. Effective data communication between publishers and subscribers requires dynamic and reliable discovery of publisher/subscriber endpoints in the system, which DDS currently supports via a standardized approach called the Simple Discovery Protocol (SDP). For large-scale systems, however, SDP scales poorly since the discovery completion time grows as the number of applications and endpoints increases. In order to scale to much larger IoT applications, a more efficient protocol is required.

This paper makes three contributions to overcoming the current limitations with DDS SDP. First, it describes the Content-based Filtering Discovery Protocol (CFDP), which is our new endpoint discovery mechanism that employs content-based filters to conserve computing, memory and network resources used in the DDS discovery process. Second, it describes the design of a CFDP prototype implemented using RTI Connext DDS. Third, it analyzes the results of empirical studies conducted in a testbed we developed to evaluate the performance and resource usage of our CFDP approach compared with SDP.

Event-driven design is fundamental to developing resilient, responsive, and scalable reactive systems as it supports asynchrony and loose coupling. The OMG Data Distribution Service (DDS) is a proven event-driven technology for building data-centric reactive systems because it provides the primitives for decoupling system components with respect to time, space, quality-of-service, and behavior. DDS, by design, supports distribution scalability. However, with increasing core count in CPUs, building multicore-scalable reactive systems remains a challenge. Towards that end, we investigate the use of Functional Reactive Programming (FRP) for DDS applications. Specically, this paper presents our experience in integrating and evaluating Microsoft .NET Reactive Extensions (Rx) as a programming model for DDS-based reactive stream processing applications. We used a publicly available challenge problem involving real-time complex analytics over high-speed sensor data captured during a soccer game. We compare the FRP solution with an imperative solution we implemented in C++11 along several dimensions including code size, state management, concurrency model, event synchronization, and the fitness for the purpose of "stream processing." Our experience suggests that DDS and Rx together provide a powerful infrastructure for reactive stream processing, which allows declarative specication of concurrency and therefore dramatically simplies multicore scalability.

Avionics Sensor Health Assessment is a sub-discipline of Integrated Vehicle Health Management (IVHM), which relates to the collection of sensor data, distributing it to diagnostics/prognostics algorithms, detecting run-time anomalies, and scheduling maintenance procedures. Real-time availability of the sensor health diagnostics for aircraft (manned or unmanned) subsystems allows pilots and operators to improve operational decisions. Therefore, avionics sensor health assessments are used extensively in the mil-aero domain. As avionics platforms consist of a variety of hardware and software components, standards such as Open System Architecture for Condition-Based Maintenance (OSA-CBM) have emerged to facilitate integration and interoperability. However, OSA-CBM is a platform-independent standard that provides little guidance for avionics sensor health monitoring, which requires onboard health assessment of airborne sensors in real-time. In this paper, we present a distributed architecture for avionics sensor health assessment using the Data Distribution Service (DDS), an Object Management Group (OMG) standard for developing loosely coupled high-performance real-time distributed systems. We use the data-centric publish/subscribe model supported by DDS for data acquisition, distribution, health monitoring, and presentation of diagnostics. We developed a normalized data model for exchanging the sensor and diagnostics information in a global data space in the system. Moreover, Extensible and Dynamic Topic Types (XTypes) specification allows incremental evolution of any subset of system components without disrupting the overall health monitoring system. We believe, the DDS standard and in particular RTI Connext DDS, is a viable technology for implementing OSA-CBM for avionics systems due to its real-time characteristics and extremely low resource requirements. RTI Connext DDS is being used in other major avionics programs, such as FACE™ and UCS. We evaluated our approach to sensor health assessment in a hardware-in-the-loop simulation of an Inertial Measurement  Unit (IMU) onboard a simulated General Atomics MQ-9 Reaper UAV. Our proof-of-concept effectively demonstrates real-time health monitoring of avionics sensors using a Bayesian Network –based analysis running on an extremely low-power and lightweight processing unit. 

Master's Thesis in Intelligent Embedded Systems, School of Innovation, Design and Engineering, Marardalen University, Sweden.

This work focuses on applying DDS in the context of IEC 61499. The specific objectives are to: 1) present the structure and key feature of DDS, 2) map node-to-node communication in IEC 61499 to the DDS real-time publish-subscribe model including mapping timing requirements to QoS attributes of the publish-subscribe model, and 3) evaluate the performance of DDS communication while comparing it with the more traditional socket-based Ethernet communication.

The Object Management Group’s (OMG) Data Distribution Service (DDS) provides many configurable policies which determine end-to-end quality of service (QoS) of applications. It is challenging to predict the system’s performance in terms of latencies, throughput, and resource usage because diverse combinations of QoS configurations influence QoS of applications in different ways. To overcome this problem, design-time formal methods have been applied with mixed success, but lack of sufficient accuracy in prediction, tool support, and understanding of formalism has prevented wider adoption of the formal techniques. A promising approach to address this challenge is to emulate system behavior and gather data on the QoS parameters of interest by experimentation. To realize this approach, which is preferred over formal methods due to their limitations in accurately predicting QoS, we have developed a model-based automatic performance testing framework with generative capabilities to reduce manual efforts in generating a large number of relevant QoS configurations that can be deployed and tested on a cloud platform. This paper describes our initial efforts in developing and using this technology.

This paper describes a real-time event-based system to distribute and analyze high-velocity sensor data collected from a soccer game case study used in the DEBS 2013 Grand Challenge. Our approach uses the OMG Data Distribution Service (DDS) for data dissemination and we combine it with algorithms to provide the necessary real-time analytics. We implemented the system using the Real-Time Innovations (RTI) ConnextTMDDS implementation, which provides a novel platform for Quality-of-Service (QoS)-aware distribution of data and real-time event processing. We evaluated latency and update rates of one of the queries in our solution to show the scalability and benets of congurable QoS provided by DDS.

Building automation has grown in parallel to energy smart grids without much interaction. However, at present, these two worlds cannot remain separated any more, as long as intelligent buildings become another node of the grid. This paper shows that this integration can be performed in practice as long as a harmonized knowledge/data model for the two worlds can be defined. This paper describes how this harmonized model can be achieved, how it can be implemented as part of a smart grid node, and how it could work and be deployed in a case study.

SOA (especially web-services) is the communication architecture that has been used so far to integrate building automation within other systems but the smartgrid cannot relay in non real- time technologies and the request-response paradigm classically offered in SOA poses an obstacle very difficult to avoid. In this paper we describe an alternative based on an OMG standard, DDS, a real-time message-oriented communication middleware based on the publish-subscribe paradigm.

Abstract: The OMG DDS (Data Distribution Service) standard specifies a middleware for distributing real-time data using a publish-subscribe data-centric approach. Until now, DDS systems have been restricted to a single and isolated DDS domain, normally deployed within a single multicast-enabled LAN. As systems grow larger, the need to interconnect different DDS domains arises. In this paper, we consider the problem of communicating disjoint data-spaces that may use different schemas to refer to similar information. In this regard, we propose a DDS interconnection service capable of bridging DDS domains as well as adapting between different data schemas. A key benefit of our approach is that is compliant with the latest OMG specifications, thus the proposed service does not require any modifications to DDS applications. The paper identifies the requirements for DDS data-spaces interconnection, presents an architecture that responds to those requirements, and concludes with experimental results gathered on our prototype implementation. We show that the impact of the service on the communications performance is well within the acceptable limits for most real-world uses of DDS (latency overhead is of the order of hundreds of microseconds). Reported results also indicate that our service interconnects remote data-spaces efficiently and reduces the network traffic almost N times, with N being the number of final data subscribers.

SPARTA, the ESO Standard Platform for Adaptive optics Real Time Applications, is the high-performance, real-time computing platform serving three major 2nd generation instruments at the VLT (SPHERE, GALACSI and GRAAL) and possibly a fourth one (ERIS).

SPARTA offers a very modular and fine-grained architecture, which is generic enough to serve a variety of AO systems. It includes the definitions of all the interfaces between those modules and provides libraries and tools for their implementation and testing, as well as a mapping to technologies capable of delivering the required performance. These comprise, amongst others, VXS communication, FPGA-aided wavefront processing, command time filtering and I/O, DSP-based wavefront reconstruction, DDS data distribution and multi-CPU number crunching, most of them innovative with respect to ESO standards in use. A scaled-down version of the platform, namely SPARTA-Light, will employ a subset of the SPARTA technologies to implement the AO modules for the VLT auxiliary telescopes (NAOMI) and is the baseline for a new VLTI instrument (GRAVITY).

For the above instrument portfolio, SPARTA provides also a complete implementation of the AO application, with features customised to each instrument's needs and specific algorithms. In this paper we describe the architecture of SPARTA, its technology choices, functional units and test tools. End-to-end as well as individual module performance data is provided for the XAO system delivered to SPHERE. Initial performance results are presented for the GALACSI and GRAAL systems under development.

Abstract: The Data Distribution Service (DDS) middleware has recently been standardized by the OMG. Prior to data communication, a discovery protocol had to locate and obtain remote DDS entities and their attributes. Specifically, DDS discovery matches the DataWriters (DWs) and DataReaders (DRs) entities (Endpoints) situated in different network nodes. DDS specification does not specify how this discovery is translated “into the wire”. To provide interoperability and transparency between different DDS implementations, the OMG has standardized the DDS Interoperability Wire Protocol (DDS-RTPS). Any compliant DDS-RTPS implementation must support at least the SDP (Simple Discovery Protocol). The SDP works in relatively small or medium networks but it may not scale as the number of DDS Endpoints increases. This paper addresses the design and evaluation of an SDP alternative–which uses Bloom Filters (BF)–that increases DDS scalability. BFs use Hash functions for space-efficient probabilistic data set representation. We provide both analytical and experimental studies. Results show that our approach can improve the discovery process (in terms of network load and node resource consumption), especially in those scenarios with large Endpoint per Participant ratios.

Abstract—The use of simulation in training and education enables to prepare personal in realistic environment. But the cost and the complexity to create and reuse simulations often limits their application. In this paper we investigate a low cost; and high fidelity PC-based simulator based on Data Distribution Service (DDS) middleware. The main parts of the systems and the architecture, including the hardware and the software are introduced. Real-time networking between distributed simulators is achieved using a reliable distributed communication, which employs publish-subscribe middleware build using OMG-DDS. Result shows these methods could produce low cost, extensible, reliable and distributed simulators. 

http://community.rti.com/sites/default/files/users/Hakiri/103.pdf

Abstract: The development of embedded systems challenges software engineers with timely delivery of optimised code that is both safe and resource-aware. Within this context, we focus on distributed systems with small, specialised node hardware, specifically, wireless sensor net- work (WSN) systems. Model-driven software development (MDSD) promises to reduce errors and efforts needed for complex software projects by automated code generation from abstract software models. We present an approach for MDSD based on the data-centric OMG middleware standard DDS. In this paper, we argue that the combination of DDS features and MDSD can successfully be applied to WSN systems, and we present the design of an appropriate approach, describing an architecture, metamodels and the design workflow. Finally, we present a prototypical implementation of our approach using a WSN-enabled DDS implementation and a set of modelling and transformation tools from the Eclipse Modeling Framework.

This paper describe a details of implementing for DDS to be publish data in CAN BUS

Abstract: The Publish/Subscribe paradigm matches well with these systems. Data Distribution Service (DDS) is a Publish/Subscribe data-centric middleware. It specifies an API designed for enabling real-time data distribution and is well suited for such complex distributed systems and QoS-enabled applications. Unfortunately, the need to transmit a large number of sensor measurements over a network negatively affects the timing parameters of the control loops. The CAN-bus enables the information from a large number of sensor measurements to be conveyed within a few messages. Its priority-based medium access control is used to select the sensor messages with high timing constraints. This approach greatly reduces the time for obtaining a snapshot of the environment state and therefore supports the real- time requirements of feedback control loops.

The use of the “ Publish/Subscribe/Distribute ” paradigm and the underlying real -time CAN-Bus is a currently research topic and only today few works exist in this area. These activities are headed by University of ULM & German National Research Center for Information Technology and by Software Architecture Lab, Seoul National University as well as by our "Control and Communication Technologies" research group at the National School of Engineering of Tunis (ENIT), Department of Computer and Communication Technologies, headed by myself. The main objective of this paper is to demonstrate how DDS API is implemented on a CAN-Bus.

Abstract: Recent trends in distributed real-time and embed- ded (DRE) systems motivate the development of infor- mation management capabilities that ensure the right information is delivered to the right place at the right time to satisfy quality of service (QoS) requirements in heterogeneous environments. A promising approach to building and evolving large-scale and long-lived DRE information management systems are standards-based QoS-enabled publish/subscribe (pub/sub) platforms that enable participants to communicate by publishing information they have and subscribing to information they need in a timely manner. Since there is little exist- ing evaluation of how well these platforms meet the performance needs of DRE information management, this paper provides two contributions: (1) it describes three common architectures for the OMG Data Distri- bution Service (DDS), which is a QoS-enabled pub/sub platform standard, and (2) it evaluates implementa- tions of these architectures to investigate their design tradeoffs and compare their performance with each other and with other pub/sub middleware. Our results show that DDS implementations perform significantly better than non-DDS alternatives and are well-suited for certain classes of data-critical DRE information management systems.

This paper discusses the applicability of the Data Distribution Service (DDS) for the development of automated and modular manufacturing systems which require a flexible and robust communication infrastructure. DDS is an emergent standard for datacentric publish/subscribe middleware systems that provides an infrastructure for platform-independent many-to-many communication. It particularly addresses the needs of real-time systems that require deterministic data transfer, have low memory footprints and high robustness requirements. After an overview of the standard, several aspects of DDS are related to current challenges for the development of modern manufacturing systems with distributed architectures. Finally, an example application is presented based on a modular active fixturing system to illustrate the described aspects.

Distributed computing in complex embedded systems gain complexity, when these systems are equipped with many microcontrollers which oversee diverse Electronic Control Units (ECU) connecting hundreds or thousands of analogue and digital sensors and actuators.

The Publish/Subscribe paradigm matches well with these systems. Data Distribution Service (DDS) is a publish/subscribe data-centric middleware. It specifies an API designed for enabling real-time data distribution and is well suited for such complex distributed systems and QoS-enabled applications.

Unfortunately, the need to transmit a large number of sensor measurements over a network negatively affects the timing parameters of the control loops. The CAN-bus enables the information from a large number of sensor measurements to be conveyed within a few messages. Its priority-based medium access control is used to select the sensor messages with high timing constraints. This approach greatly reduces the time for obtaining a snapshot of the environment state and therefore supports the real-time requirements of feedback control loops.

The main objective of this paper is to demonstrate how DDS API is implemented on a CAN-Bus and gives performance evaluation related to delivery and transport QoS parameters.

Abstract: To realize real-time information sharing in generic platforms, it is especially important to support dynamic message structure changes. For the case of IDL, it is necessary to rewrite applications to change data sample structures. In this paper, we propose a dynamic reconfiguration scheme of data sample structures for DDS. Instead of using IDL, which is the static data sample structure model of DDS, we use a self describing model using data sample schema, as a dynamic data sample structure model to support dynamic reconfiguration of data sample structures. We also propose a data propagation model to provide data persistency in distributed environments. We guarantee persistency by transferring data samples through relay nodes to the receiving nodes, which have not participated in the data distribution network at the data sample distribution time. The proposed schemes can be utilized to support data sample structure changes during operation time and to provide data persistency in various environments, such as real-time enterprise environments and connection-less internet environments.

ABSTRACT: Publish/subscribe (pub/sub) middleware platforms for event- based distributed systems often provide many configurable policies that affect end-to-end quality of service (QoS). Although the flexibility and functionality of pub/sub middle- ware platforms has matured, configuring their QoS policies in semantically compatible ways has become more complex.

This paper makes two contributions to reducing the complexity of configuring QoS policies for event-based distributed systems. First, it evaluates various approaches for managing complex QoS policy configurations in pub/sub middleware platforms. Second, it describes a domain-specific modeling language (DSML) that automates the analysis and synthesis of semantically compatible QoS policy configurations.

Abstract: Modern military satellite communications terminals have typically been built as multiprocessor systems. Because of increasing pressure for reuse and modularity, current programs have been encouraged to consider the use of component middleware. While Common Object Request Broker Architecture is the most mature middleware standard available, its invocation semantics present considerable challenges for the development of such systems. Through reasoning about quality attributes, we found that a real-time publish-subscribe middleware reduces coupling, improves composability, and reduces the risk of architectural mismatch, deadlock, and integration problems compared to an invocationbased system. In building a communications-on-the-move (COTM) node, we found that this type of middleware, which exemplifies an implicit-invocation architectural style, promotes ease of system evolution and an incremental integration approach.

Abstract: There’s a world of opportunity for distributed embedded and real-time applications. The list of applications goes on and on: military systems, telecommunications, factory automation, traffic control, financial trading, medical imaging, building automation, consumer electronics, and more. These applications must find the right data, know where to send it, and deliver it to the right place at the right time. The publish-subscribe paradigm according to DDS is the best fit to such complex distributed applications that require a powerful communications model.

Thus, the goal idea of this paper is to study the defaults within a network of publish-subscribe nodes occurring in a clustered middleware, in order to calculate the loss rates while allowing for the caching size. A simulator has been developed in order to fix metrics chosen in the theoretical part.

Abstract: As control systems become more distributed and they are implemented with smaller hardware and software components, implementing the necessary communication links becomes challenging. There are considerable technical difficulties in guaranteeing upper bounds for latencies in motion or machine control, synchronizing the execution and communication of distributed components, taking corrective action in fault situations and reconfiguring the system.

In this paper, we discuss the main communication requirements of distributed control systems and use them to evaluate a certain distribution service product

Abstract: 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. Real-Time Publish-Subscribe (RTPS) model is one of the latest developments in Real-Time middleware technologies. Network Data Distribution Service (NDDS) is RTPS middleware developed by Real-Time Innovation (RTI). NDDS is widely used in Real-Time distributed and embedded systems for mission critical applications. The research work presented in this paper discusses the employment of NDDS for RT-DIVS and the advantages of NDDS¿s Quality of Service (QoS) policies in covering the requirements of RTDIVS. An experimental test set-up is used to verify the NDDS¿s performance for RT-DIVS. Tests results show that RTPS middleware (and NDDS specifically) is suitable for soft and firm timelines requirements for distributed industrial vision systems.

The OMG Data Distribution Service (DDS) is an emerging specification for publish-subscribe data distribution systems. The purpose of the specification is to provide a common application-level interface that clearly defines the data distribution service. The specification describes the service using UML, thus providing a platform-independent model that can then be mapped into a variety of concrete platforms and programming languages.

The OMG DDS attempts to unify the common practice of several existing implementations [2, 5] enumerating and providing formal definitions for the QoS (Quality of Service) settings that can be used to configure the service.

This paper introduces the OMG DDS specification, describes the main aspects of the model, QoS settings, and gives examples of the communication scenarios it supports.