What’s new with Open Source DDS Community Edition v6.7 Software

DDS Community v6.7 Mailer Poster

PrismTech recently released its latest version of Open Source DDS Community Edition, the 6.7 version which adds significant new functionality and a new open source licensing model to the DDS Community Edition.

The DDS Community Edition v6.7 is being released to the open source community under the widely adopted Apache license, version 2.0 source code license. Unlike many other code licenses the Apache license places very few restrictions on the use or availability of the code.

Here are the new features included on this release:

  • Durability: Full support for TRANSIENT_LOCAL durability is now offered without relying on each standalone ‘single-process’ application to include a full durability-service (DS).  As typically a DS is run as part of a federation, we have introduced the concept of ‘client-side durability’ where standalone ‘single-process’ applications will transparently obtain historical data from dynamically discovered durability-services (as provided by our commercial OpenSplice version)
  • DCPS API’s: Support for the latest ISOCPP and JAVA5 DCPS language bindings
  • FACE: This release includes a reference implementation of the FACE 2.1 Transport Services Segment (TSS)
  • GPB: Support to use Google Protocol Buffers (GPB) as an alternative to the OMG-IDL definition for topic-types. GPB is a popular technology that supports evolvable data-types and we’ve added annotations for key- and filterable-fields to retain the data-centric features of DDS.

The new release also includes numerous other updates to the code base such as: performance and footprint improvements, bug fixes, robustness and maintainability improvements.

With having Apache license version 2.0 open source license available, this will help reduce the IoT adoption barriers and further accelerate the penetration of DDS in this new and exciting market.

Find out more details on DDS Community v6.7 or click here to download the software.

 

OT/IT Connectivity with Vortex Edge Connect

One of the main challenges facing the Industrial Internet of Things (IIoT) community is connecting operational or field systems, comprised of devices and other data sources utilizing a diverse range of protocols with higher level Internet of Things (IoT) systems. This is where Vortex Edge Connect comes in.

Vortex Edge Connect ingests data from industrial devices such as PLCs, PAC, RTUs, DAQs, sensors, actuators, etc. using a range of Operational Technology (OT) protocols. This ingested data is then converted into a normalized in-memory data model which enables this data to be shared with other higher level systems such as SCADA systems, analytics engines, ERP, MES, etc.

Due to the Vortex Edge Connects innovative design, it is highly scalable and can support 1-to-1, 1-to-many, or many-to-many data connection models. Whether you’re in a Linux or Windows environment, Vortex Edge Connect is platform and operating system independent, enabling you to deploy with ease and peace of mind for expansion and integration.

For more information on Vortex Edge Connect, please visit our website.

MathWorks MATLAB and Simulink with Vortex OpenSplice DDS Tutorial

To coincide with the release of PrismTech’s Vortex OpenSplice 6.8, we have put together a series of videos to show how simple using Vortex OpenSplice DDS in MATLAB and Simulink is.

Presented by Paul Elder, these videos walk you through everything you’ll need to get up and running with Vortex: from installation, right through to building a model.

 

PrismTech Predicts Edge Computing, Next Generation Smart Gateways will Come of Age to Enable the Industrial Internet of Things in 2017

 PrismTech 2017 forecasts.png

Mainstream adoption of edge computing and the advent of second-generation smart gateways are among PrismTech’s top predictions for the Industrial Internet of Things (IIoT) in 2017.

Steve Jennis, SVP and Head of Global Marketing for ADLINK and PrismTech, compiled the list based on his extensive knowledge of IIoT users, vendors and technologies, as well as through his collaboration with peers in industry initiatives such as the OpenFog Consortium, the Edge Computing Consortium, Open Edge Computing, the Industrial Internet Consortium® and the Object Management Group®.

Jennis predicts that:

  1. Edge computing will become a mainstream term for IIoT systems.
  2. Edge computing will be recognized as the solution to fixing the shortcomings of M2M for IIoT (latency, resilience, cost, peer-to-peer, connectivity, security, etc.).
  3. Real-time (edge) analytics and IT/OT security become two of the key drivers for new IIoT platform/infrastructure deployments.
  4. IT departments will exert more and more influence over the requirements for OT systems connected to corporate IT systems or the Internet.
  5. The Edge will become the vendor battleground in IIoT markets between traditional CT, IT and OT vendors.
  6. Users will move from tactical to strategic IIoT thinking as previously deployed point-solutions (e.g. most M2M systems) reveal more and more functional limitations and IT management issues.
  7. Major IT systems integrators will begin to offer “managed solutions” for edge computing in addition to their “managed services” for cloud computing.
  8. Interoperability and legacy integration problems will be reduced with connector technologies, data normalization and shared micro-services delivered in/on “smart gateways”.
  9. Second-generation IIoT smart gateways (software-defined with on-board IIoT software stacks, connectivity and shared services) will quickly render first-generation (hardware-defined) M2M gateways obsolete.
  10. Security at the edge will be positioned as an IT/OT firewall. The potential for hacking OT systems, possibly through IT connections, is increasingly becoming a concern. Edge computing appliances will serve as the IT/OT firewall.

“Today’s trends show that the term ‘Edge Computing’ will continue to grow in usage and come to represent most implementation scenarios for the IIoT,” Jennis said. “The addition of new capabilities ‘at the edges’ of OT systems, IT systems, the Internet and cloud services will come to define the evolution of the IIoT and its new business value-add.”

“Next-generation smart gateways and industrial servers will supply the edge platforms to support the demands of the IIoT. These gateways and servers will host the software stacks that enable data connectivity from the sensor to the cloud, while also supporting edge compute and intrinsic security,” continued Jennis. “They will thus support fog computing architectures where applications can add-value at the most appropriate place in an end-to-end IIoT system: at the device, on the edge appliance, or in the IT/cloud environment. This multi-tiered architecture will come to define the IIoT and provide the ubiquitous (and secure) data accessibility and distributed systems capabilities needed to support new vertical solutions in, for example, smart factories, intelligent transportation systems and integrated healthcare systems.”

As an example of this trend PrismTech’s newly announced Vortex Edge PMQ (http://www.prismtech.com/vortex/vortex-edge-pmq) leverages best in class IIoT edge computing, connectivity and predictive analytics technologies to provide real-time device-edge-cloud connectivity.

Getting Smarter at the Edge

With over 2 billion people around the world now users of a smartphone, we have more computing power than ever right at our fingertips than ever before. Our cars, houses, factories, cities, etc. are all becoming smarter too. With all of this distributed computing power and applications, we’re producing and consuming vast quantities of data … but are we using this data effectively?

As systems grow in complexity and the number of connected devices/sensors increases, so too does the sheer volume of data produced. That is a lot of (potentially sensitive) data to be sending to the cloud to be analyzed for faults/abnormalities. Then there is the issue of network connectivity: what if the network goes down? What if the latency is too high for the safety/mission/business critical scenario? There are many single points of failure in a cloud-reliant solution. Local computing is therefore still vitally important to many industries, but this data still has value. Aggregating this data at the edge for cloud analysis is one way in which companies can derive massive business benefits without overburdening network communications. This aggregate data can be analyzed for insights, and results deployed back down to the edge.

Automation is an area in which edge computing plays a vital role: when you need an action to be taken immediately should something happen; you require a low-latency instantaneous response. Running edge based analytics enables companies to perform reactive, predictive, and prescriptive actions in real-time with no bandwidth costs or WAN networking issues to worry about. Automating decisions at the edge enables geographically isolated systems to benefit from big-data analytics without requiring high-bandwidth, low-latency connections to the cloud.

Edge computing is enabling many areas of high interest: self-driving cars, factory automation, autonomous drones, predictive maintenance, and the list keeps growing. Unlocking the potential of the ever-growing volume of data being produced means greater efficiency, more effective and timely actions, and valuable insights.

The recently announced Vortex Edge PMQ solution utilizes the power of PrismTech’s Vortex data-connectivity software, ADLINK’s ruggedized industrial hardware, and IBM’s advanced Predictive Maintenance and Quality analytics. Vortex Edge PMQ provides an edge analytics solution designed for Industrial Internet of Things environments where cloud computing access may be limited or otherwise not desired.

For a more detailed look at Vortex Edge PMQ and implementation examples, visit http://www.prismtech.com/vortex/vortex-edge-pmq

PrismTech and RTTS Extend Partnership to Provide Unparalleled Support to Developers of Combat and Battlefield Management Systems in India

DefensePrismTech™, a global leader in software platforms for distributed systems and RTTS (RealTime TechSolutions), a systems integration specialist to defense customers that need extreme levels of performance and reliability, said today they will extend their eight-year partnership. The companies will focus on delivering technology and services that simplify combat management system development and dramatically reduce development time.

RTTS

Over the past eight years, RTTS have developed their engineering, consulting and support teams to a high level of DDS expertise, allowing developers based in India to benefit from first line support in their own time zone.

“RTTS’s team now has over 150+ man years of experience with DDS which makes us unique in India,” said Raj Rajagopolan, Director, RTTS. “I am excited to continue to grow our business with the extension of our partnership with PrismTech.”

The Indian Government are committing to develop many new combat and battlefield management systems. PrismTech and RTTS’s extended partnership will see continued growth in the use of Vortex OpenSplice in these programs.

PrismTech’s Vortex OpenSplice is the leading (commercial and Open Source) implementation of the Object Management Group™’s (OMG™) Data Distribution Service (DDS) for Real-Time Systems standard. Vortex OpenSplice has been designed to optimally address the real-time information distribution and management challenges posed by high performance real-time data-processing systems.

Further information about Vortex OpenSplice is available from PrismTech’s website at: http://www.prismtech.com/vortex.

Vortex & ADLINK’s MXE-202i IoT Gateway Demo

This demo features the combination of Vortex and ADLINK’s MXE-202i IoT Gateway that can be used to:

  • Provide reliable, real-time Device-to-device data connectivity for IoT Edge and Fog networks
  • Create a decentralized architecture that removes any single points of failure
  • Support automatic discovery for edge-based devices and applications enabling an IoT system to evolve dynamically
  • Show data interoperability between DDS and other protocols enabled by Vortex
  • Enable edge-based processing and analytics in order to:
    • Reduce response time and improve decision-making
    • Federate processing load across nodes
    • Minimize network bandwidth consumption in comparison to Cloud-centric solutions