PrismTech Presentation Highlights how OMG DDS Standard is a Crucial Enabler for the Industrial Internet of Things (IIoT)

At the recent Object Management Group (OMG) Technical meeting in Cambridge, MA, USA, PrismTech SVP for Corporate Development, Steve Jennis presented on the subject of “Data Distribution Service (OMG DDS) – Aligning OT and IT to Deliver the Potential of the Industrial Internet of Things (IIoT)” at its special Putting IIoT to Work Event.

The presentation highlighted the four mega trends that are driving IIoT adoption, specifically: (1) the continuous decline of the cost of Internet-connected sensors, (2) the vast amount of money being invested into the IoT by both large and startup companies focused on the development of devices, gateways, software, cloud, fog nodes, analytics and HMI technologies, (3) almost ubiquitous Internet connectivity and (4) the high adoption levels of smart phones, tablets and other BYOD devices.

The presentation also discussed how the OMG DDS standard can support the creation of new end-to-end IIoT systems that provide the potential for innovative new products and services, higher levels of productivity and environmental benefits.

Finally Steve showed how PrismTech’s Vortex, the leading commercial and open source implementation of the OMG DDS standard, is being used as a data-centric cross-platform enabler for OT / IT integration between edge, gateway, cloud, mobility etc. and how it is helping deliver OT and IT alignment, and thus the IIoT.

Vortex OpenSplice – Power at the core of your IoT Systems

PrismTech features Vortex OpenSplice on its latest video highlighting its exceptional properties such as power, performance, scalability, efficiency, data centricity, security and quality-of-service.

From the original OpenSplice DDS product, Vortex OpenSplice is a combination of innovation, improved performance and the most comprehensive DDS implementation available in the market. Vortex OpenSplice enables data to be shared and integrated across a wide spectrum of operating systems and platforms; and has been successfully deployed in many missions and business-critical systems.

Vortex OpenSplice is available for a FREE 30-day trial. Click here to download.

Data Distribution Service Tutorial Live Webcast

Date: 25th June 2015
Location: Online

Why Attend:

  • Learn DDS-based data-centric design and data-modeling fundamentals
  • Learn the most important Programming, Data Modeling, Quality of Service Idioms and Patterns
  • Learn how DDS can be effectively leveraged for Internet of Things systems

Abstract:

The Data Distribution Service (DDS) is a standard for efficient and ubiquitous data sharing built upon the concept of a strongly typed distributed data space. The ability to scale from resource constrained embedded systems to ultra-large scale distributed systems has made DDS the technology of choice for applications in industries such as Industrial Automation, Smart Cities, Smart Grids, Connected Vehicles, Medical Devices, Air Traffic Control and Management, Modeling and Simulation, Defense and Aerospace.

This webcast will provide attendees with an introduction to the DDS standard. After attending the webcast you will understand how to exploit DDS architectural features when designing your next system, how to write idiomatic DDS applications and what are the fundamental patterns that you should adopt in your applications.

The webcast will last approximately one hour. Click here to book your seat.

Webcast Presenter:

Angelo Corsaro, Ph.D. is Chief Technology Officer (CTO) at PrismTech where he directs the technology strategy, planning, evolution, and evangelism. Angelo leads the strategic standardization at the Object Management Group (OMG), where he co-chairs the Data Distribution Service (DDS) Special Interest Group and serves on the Architecture Board. Angelo is a widely known and cited expert in the field of real-time and distributed systems, middleware, and software patterns, has authored several international standards and enjoys over 10+ years of experience in technology management and design of high performance mission- and business-critical distributed systems. Angelo received a Ph.D. and a M.S. in Computer Science from the Washington University in St. Louis, and a Laurea Magna cum Laude in Computer Engineering from the University of Catania, Italy.

OMG Standards at Work in the Industrial Internet of Things Berlin Germany

Industrial Internet of Things standards event

Date: 17th June 2015
Location: Berlin, Germany

With the rise of smart analytics processing data generated by interconnected devices and machines, we are experiencing a technological shift not seen since the Internet Revolution of the 1980s-90s. The Industrial Internet of Things (IIoT) is delivering improved productivity, major cost savings, and streamlined processes to professionals from all industries. OMG has been active in IIoT standardization from long before “IIoT” became an industry buzzword. This half-day information session looks at two important areas where OMG standards are proving integral to IIoT efforts around the globe. Industry experts will share case studies of these standards at work in the industrial internet, and present their vision of the future within this rapidly growing field.

Data-Distribution Service for Real-Time Systems (DDS)

OMG’s Data-Distribution Service for Real-Time Systems (DDS) standard provides a protocol that meets the demanding scalability, performance, and Quality of Service requirements of IIoT applications spanning connected machines, enterprise systems, and mobile devices. DDS is deployed world-wide on platforms ranging from low-power, low-footprint devices to Cloud servers. It supports efficient bandwidth usage and flexible real-time system integration for the agile orchestration of system components, while simultaneously providing a global data space for data analytics.

Systems Assurance (SysA)

The rapid development of truly global machine-to-machine interoperability also brings with it the threat of cyber-attacks and data theft on a previously unimaginable scale. Poorly-secured IIoT systems could pose an existential threat to the industries that deploy them. OMG’s Systems Assurance Task Force (SysA TF) works on standards that ensure the reliability, safety and security of IIoT systems. Leading practitioners in the field will present a state-of-the-practice look at current issues in risk management and security assurance, describing the OMG standards and initiatives that will help the Industrial Internet of Things deliver on its promise without succumbing to the threats it faces.

Dr. Angelo Corsaro, PhD, CTO, PrismTech and Co-Chair, Data Distribution Service (DDS) Platform Special Interest Group will be speaking at the event on:

Reactive and Data-Centric Architectures with DDS

Abstract:  An increasing number of Software Architects realize that data is the most important asset of a system and start embracing the Data-Centric revolution (datacentricmanifesto.org) – setting data at the center of their architecture and modelling applications as “visitors” to the data. At the same time, architects have also realized how reactive architectures (reactivemanifesto.org) facilitate the design of scalable, fault-tolerant and high performance systems.  Few architects have yet realised how reactive and data-centric architectures are two sides of the same coin and as such should always go together.  This presentation explains why reactive data-centric architecture is the future and how the OMG DDS Standard is uniquely positioned to support this paradigm shift. A series of use cases will highlight how the data-centric revolution is being applied in practice and what measurable benefits it is providing.

Further information and registration for the event is available at: http://www.omg.org/news/meetings/tc/berlin-15/special-events/OMG_IoT_Standards_agenda.htm

Building Reactive Data-centric Applications with Vortex, Apache Spark and ReactiveX Live Webcast

Date: 30th April 2015
Location: Online

Why Attend:

  • Understand the foundations of Reactive Data-Centric Architectures as promoted by the reactivemanifesto.org and the datacentricmanifesto.org
  • Learn about the features of Vortex that support Reactive Data-Centric Architectures
  • Learn how Vortex can be used in combination with Apache Spark and ReactiveX to build high performance data-centric

Abstract:

An increasing number of Software Architects are realizing that data is the most important asset of a system and are starting to embrace the Data-centric revolution (datacentricmanifesto.org) — setting data at the center of their architecture and modeling applications as “visitors” to the data. At the same time, architects have also realized that reactive architectures (reactivemanifesto.org) facilitate the design of scalable, fault-tolerant and high performance systems.

Yet, few architects have realized that reactive and data-centric architectures are the two sides of the same coin and should always go hand in hand.

This webcast will show how reactive data-centric systems can be designed and built taking advantage of PrismTech’s Vortex data sharing capabilities along with its integration with reactive and data-centric processing technologies such as Apache Spark and ReactiveX.

The webcast will last approximately one hour.

Webcast Presenter:

Angelo Corsaro, Ph.D. is Chief Technology Officer (CTO) at PrismTech where he directs the technology strategy, planning, evolution, and evangelism. Angelo leads the strategic standardization at the Object Management Group (OMG), where he co-chairs the Data Distribution Service (DDS) Special Interest Group and serves on the Architecture Board. Angelo is a widely known and cited expert in the field of real-time and distributed systems, middleware, and software patterns, has authored several international standards and enjoys over 10+ years of experience in technology management and design of high performance mission- and business-critical distributed systems. Angelo received a Ph.D. and a M.S. in Computer Science from the Washington University in St. Louis, and a Laurea Magna cum Laude in Computer Engineering from the University of Catania, Italy.

A Comparative Study of Data Sharing Standards for the Internet of Things

Although Industrial and Consumer IoT applications typically require different levels of performance, security, fault tolerance, and safety, they are both data-centric and share the same underlying architectural pattern — the Collect | Store | Analyze | Share pipeline. As a result, data sharing is a crucial architectural element that can make the difference between the success and failure of an IoT application. The challenge for industry is that there is currently a proliferation of data-sharing and messaging protocols, no set standard, and – until now – no qualitative and quantitative analysis to provide insight and direction.

Read PrismTech CTO Angelo Corsaro’s latest article in the Cutter IT Journal which aims to help IoT practitioners understand the set of data-sharing requirements they must consider and guide them in the selection of viable technologies to satisfy those requirements by registering for FREE at Cutter Consortium

In the age of IoT, think “Data Centric”!

Data Centricity helps creating situation awareness to manage and control complex systems and systems of systems in an Internet-centric World.

In a smart city case it can help you building a system managing green smart houses and smart buildings, managing traffic, managing parking, garbage collections, energy and so one.

Unlike messaging, in a data centric based system each entity in the real world is truly represented as a data object that has :

  • An identity
  • A Structure
  • A State
  • A Lifecycle, and
  • Some Meta data that characterises it and captures all the above

Data qualities can even be attached ( such as Security, Persistency, Consistency etc …) to the data objects.

Take a Car as an example, a car is a pretty complex system that can live, circulate and evolve in other systems such as traffic mgmt. system or within a smart city system.

A car has:

  • An Identity :
  • A Status :

– It can be moving ,

– It can be Broken

– It can be in Maintenance:

– It can be Parked :

Or .. It can be scrapped:

A Data Centric system can instantaneously tells you which “new” cars have been observed or those that have left or been “disposed” from the system. It does all this with no extra effort because a Data Centric system “knows” each data entity individually and does automatic assertion of their liveliness.

  • A Lifecycle :

Being aware of the data lifecycle allows you to automate for instance your system resource management by releasing all the other objects that are associated to your data and releasing memory, threads, files etc … they are using .

Let’s now try to analyse a car structure by looking to its anatomy…. but more importantly by seeing it as an entire system.

  • A Structure

A car has a complex structure. Representing its structure is tough if you are not using a powerful data description language that captures not only subsets it is made of but also the relationships between them.

A Simple car will be made of :

  • A bodywork ….
  • 4 wheels ……..
  • Many many sensors
  • On board computer
  • Brake system …and
  • An Engine …

The engine is a subsystem itself yet is made of many other complex sub-systems:

  • A Carburettor
  • Pistons
  • Pushrods
  • Fan
  • Timing chain
  • Etc >>>>

Each of those subsystems can be captured as individual data objects:

Your data representation can be strongly structured or it can be loosely or semi-structured.

In Data centric world, you can apply and enforce business rules, for instance, the engine will function correctly only when all its sub systems are in a steady state working properly. Furthermore, Data centricity can capture relationship between data objects and entities:

Imagine you are a DRIVER OF ONE OF THOSE VEHICLES!! …

A Driver is first of all a Person, that has an identity, a state and a structure. He can own zero, one or several vehicles and cars, but unfortunately for the time being he can only drive 1 vehicle at a time !!!

All those data entities and their relationships can be captured naturally in a Data Centric system and they live in harmony in a Distributed Global Data Space (GDS).

Nowadays big and sensitive Data is coming from everywhere, data producers and the data consumers are distributed over Local, Wide area , Mobile networks or on Internet or even on ad-hoc networks. In a nutshell we can say that the Network and Internet are becoming a tremendous data space and certainly a huge gold deposit !!

Let’s say you are the owner of a “moving company”, …….

To better manage your fleet vehicles and trucks you decided to install a GPS tracking device on each vehicle of your fleet coupled with an “engine diagnostic box” provided by a cutting edge automotive supplier that enables remote diagnostic and assistance… .

Such system would not only help in knowing where your drivers are in a real-time manner but it will also allow you to assist them in case of an accident or if any truck is broken.

A scenario where Data Centricity Excels over Messaging

Let’s take the case of one driver that in a beautiful and sunny day takes his track to deliver some goods and products. While he is driving …His Truck brakes down in the middle of nowhere !!!!!!!!!! a disaster !!!!!

  1. Fortunately, the truck position is constantly reported by the GPS device and from time to time it reports the engine status compressed over mobile networks
  2. When the engine is broken its diagnostic box will update urgently the engine data graph that has been built over time and change its status to “broken” . Instantaneously, all the interested parties will be notified of “Engine status change”. Some diagnostic applications will immediately start the data analysis to identify the broken subsystem (c.f fig below), while others will be in charge of alerting you by SMS seeking for your assistance as the boss of the company in case there are some extra fees to pay. Some of those diagnostics and analysis applications will require assessing the overall engine data object, while others, more specialised, will only be looking at a subset of the engine data objects. What makes a Data Centric System unique compared to other design paradigm is that each application can have its own view on the data.
    In a very near future, such diagnostic and analysis will happen likely in the Truck provider’s “private cloud” … Such data centric system will require a technology and platform that maintains virtually a unique single dataspace yet where that dataspace will necessarily be physically distributed.
  3. If the failure cannot be fixed remotely, (by for instance restarting the engine in a degraded mode operations or disabling some automatic assistance systems (e.g the shield safety system , or restarting the on-board computer etc ….. ), a (human) expert with the required expertise will get involved for further analysis remotely .
  4. Let’s assume it is the alternator that is broken , a spare part will be immediately ordered …and
  5. an assistance vehicle will bring it to the broken truck minimizing the overall response time !!

Messaging oriented Vs Data Centric System, the Conclusion

With a Message centric system, things will be more complex to build, as …fundamentally…. a message is just an information container, with usually a header and some payload. Messaging will break the overall data representation of the system and you will lose the relationship between them !. With a messaging based system, application logic will need to rebuild each time the full picture of the system from unrelated individual pieces of basic information captured within messages and recreate the full picture and also by manually assuring the consistency of the overall picture. This process can be terribly complex, time consuming and error prone.

On the other hand, Data Centricity inherently rebuilds and guarantees consistency of the overall picture. It helps you getting the system situation awareness you are looking for free.

Data centricity is a very powerful paradigm that supersedes messaging as it can at the same time:

  1. Models Real-world entities as they are with their unique identity , state, structure, meta data and lifecycle
  2. Catchs and represent the relationship between data entities
  3. Helps implementing a decoupled systems where applications interact only by sharing data and exchanging information.
    • A Data Centric based platform will be in charge of maintaining the state of the overall system even in case of failure so that the latest consistent state of the system will always be known and will always be available from late joining applications, whatever their access point to the system will be.
  4. Data Centricity is generic enough and polymorphic to model other interaction paradigms, as it can also model :
    • Event and notification based communication ,
    • Conversational protocols , such as Request / reply based protocols in an abstract and efficient way. This will help part of the system -if needed- to be also Service Centric (to implement SOA based systems too).
    • Lightweight Transactional communications based on the so called coherent -sets and eventually consistent models
    • Message oriented communication -if needed- by a subsystem

Data Centricity is nowadays backed by an extremely powerful Real time Pub/Sub standard and interoperable Middleware technology (http://portals.omg.org/dds/) that is able to AUTOMATICALLY Discover all the Data entities whenever and wherever they are. You can now Build, Share and Monitor data distribution everywhere from embedded devices to machines and Servers in private and public Clouds or in internal company domains.

Data Centric Middlewares connect people at work whether they are, using their workstations, smartphones or tablets to the heart of any mission critical system, securely, efficiently in any circumstances.

So in a nutshell, the key lesson here is ……if you hear someone comparing Data Centric Platforms using the standard Data Distribution Service (DDS) to a Message oriented Middleware (M.o.M) tell him he is doing as if he is comparing a Data base system to a File system, or more precisely, comparing a Distributed Data Base to a Network File System!..

At the end, always remember that in the IoT Age, Data is certainly becoming your strategic economic value, its your key factor of growth and success ! Treat it appropriately!!