David McKee, research fellow at the Distributed Systems and Services Research group at University of Leeds will give on June 20 the workshop "The Internet of Simulations: building intelligent systems" in the event Techsylvania in Cluj-Napoca, Romania. Techsylvania is the leading technology event in Eastern Europe that gathers tech enthusiasts and business people to connect, hack and share ideas.
He will introduce the audience to the Internet of Simulation (IoS) paradigm as an extension of IoT in a world where connectivity, data analysis, virtual prototyping, and Artificial Intelligence are and will continue to be important for future systems.
The main theme of this workshop is building future cities. David will also approach some technical aspects such as current practices of simulation for virtual prototyping and forecasts on how the trend will evolve in the upcoming years. He will use our IoS compliant platform Simware and some of our actual use cases as the CITIUS project, as examples of how IoS can be applied in practice.
If you have the chance to attend this tech event, don't miss the workshop. You will learn there how IoS will transform IoT in the Internet of Everything!
I have collaborated with Stephen Clements, Dave McKee, Jie Xu and Richard Romano from the University of Leeds and D. Batterby from Jaguar Land Rover in a paper that will presented in the IEEE2017 Systems of Systems Conference.
The paper "The Internet of Simulation:enabling Agile model Based Systems Engineering for Cyber-physical systems", explains how the expansion of the Internet of Things (IoT) has resulted in a complex cyber-physical system of systems that is continually evolving. With ever more complex systems being developed and changed there has been an increasing reliance on simulation as a vital part of the design process. There is also a growing need for simulation integration and co-simulation in order to analyse the complex interactions between system components. To this end, in the paper, we propose that the Internet of Simulation (IoS), as an extension of IoT, can be used to meet these needs, using IoS as a lever to do a simulation based system engineering of CPS.
If you are interested in collaborating with us in the development of the IoS, please contact me at firstname.lastname@example.org. You can also contact directly with my colleagues at the University of Leeds that will be there in case you are fortunate to travel to Hawaii to attend the conference.
The Internet of Simulations is related to many of the main tech trends for 2017 as identified by InfoWorld Magazine
Look at this very interesting article at Infoworld magazine, one of the most recognized specialized publications in identifying tech trends early.
In this article, InfoWorld identifies 11 technologies that will disrupt the current IT approaches. It is funny that they identify many cutting-edge technologies already related to the Internet of Simulations:
Finally, the article, highlights as the most important trend in 2017 the merging of emerging disruptives technologies that will increase the value proposition ([...], when joined, [the disparate technologies] are ,much more that the sum of their parts). Just the same concept as IoS!
IoS converges the latest cloud, IoT, simulation & data exchange technologies in one integrated solution that will allow to use simulations in new exciting and yet unknown ways
I have just read an interesting article in Digital Engineering magazine that explains how SIEMENS strategy is putting simulation as a key technology for the development of new industrial products. ,
This article focus on the importance of simulation in the digitalization. A leader in PLM software as SIEMENS states here that "... every aspect of digitalization in product development requires engineering simulation to move into predictive analytics..." , i.e moving forward to the Simulation based system engineering in product development.
Predictive engineering analytics is the realm of what Siemens calls intelligent modeling for realized products. Multidiscipline, multi-physics analysis gains in importance as product design becomes more about systems development than creating a single product.
I am happy to see that big companies as Siemens share our vision of a simulation based system engineering of smart and connected systems in the Internet of Simulations.
To know further about how the Internet of Simulations will help to the digitalization in Industry 4.0 click here
Improving AI with Simulation tecHnologies.
MIT Technology Review has included Reinforcement Learning as a top 10 breakthrough technologies for 2017 in its latest issue.
What is reinforcement learning? It is about to let machines learn by experimenting. As it is explained in the magazine, reinforcement learning copies a very simple principle from nature. The psychologist Edward Thorndike documented it more than 100 years ago. Thorndike placed cats inside boxes from which they could escape only by pressing a lever. After a considerable amount of pacing around and meowing, the animals would eventually step on the lever by chance. After they learned to associate this behavior with the desired outcome, they eventually escaped with increasing speed.
High fidelity simulation is going to be a key lever to reinforcement learning
Reinforcement learning algorithms can help, for example, to improve the "driving skills" of self-driving cars. Today’s driverless vehicles often falter in complex situations that involve interacting with human drivers, such as traffic circles or four-way stops. AI engineers can collaborate with simulation engineers to integrate a digital model of the driverless car in a simulated environment, replicating the most complex traffic situations without any risk for people and real traffic. In the virtual space, the control software can perform the maneuvers over and over altering its instructions a little in each attempt. Applying deep learning techniques, the system can extract the patterns from the best performed maneuvers, learning from experimentation.
We see then that high fidelity simulation is going to be a key lever to reinforcement learning but, what kind of simulation we need to do an effective learning? In a former post, we have already discussed about the many applications that simulation brings to the development of smart and connected devices, including the virtual experimentation and design of IoT's products. In that article, we were also discussing about the kind of simulation that it is needed to integrate in an effective way digital models of the new products in simulated environments: we need to work with Net-Centric and interoperable models and simulations. In the same way that the physical product evolves to the Internet of the Things, its digital model will need to evolve to an Internet of the Simulations or IoS, in which heterogeneous simulations of the diverse physical and cyber subsystems of the smart product can interoperate without restrictions.
The Internet of Simulations will allow to reinforce the learning of "smart" products by integrating a digital model of the smart product and its AI software in a complex virtual space.
But to evolve actual simulation products and solutions to the Internet of Simulations, several challenges needs to be addressed, especially in the technologies and architectures to integrate all kind of simulations and real system in a common virtual space. We are investing in new simulation technologies for the IoS and the result is our Simware platform. We are also collaborating with lead research groups as the Distributed Systems and Services Research group of the University of Leeds in the development of new simulation architectures and technologies for the Internet of Simulations. Staff and researchers in DSS group are doing very interesting projects related to the application of the Internet of Simulations to the virtual design and experimentation of new vehicles, included self-driving vehicles.
If you are interested in collaborate with us to improve the integrability of cyber-physical systems in simulated environments, send us an email to email@example.com. or write a comment here in this post.
Even when Simware platform now is a System of System simulation platform, originally Simware was designed as a real time simulation platform for the agile development of Net-Centric man in the loop simulators. Simware platform evolves the AVSM design pattern with the latest innovations in distributed and data-centric architectures, increasing the integrability, scalability, interoperability and reusability over the traditional AVSM design pattern.
AVSM or Air Vehicle Structural model was first developed in the early 90's by a collaborative effort of the US Air Force, AF contractors and the Software Engineering Institute (SEI) to address the problems associated with the development and evolution of flight simulator software.
AVSM introduced a new software design pattern for the development of hi-fi flight simulators, based on two levels of artefacts : The Executive and the Application. Executive is involved with the coordination real time scheduling and synchronization of all the simulator processes and Application is handling the computation of the vehicle simulation.
AVSM design pattern has demonstrated its value to the development of standalone simulators, Structural design is simple to understand, allow to create modular products and provide a common coordination model across the total system, but its use during the last 3 decades has also demonstrated several gaps:
To solve above challenges in AVSM structural model, Simware platform evolves the AVSM pattern with the latest innovations in distributed and data-centric architectures, increasing the integrability, scalability, interoperability and reusability over the traditional AVSM design pattern. Simware provides the same artefacts in AVSM structural model in a modern software architecture: service oriented, open, distributed and data-centric. Besides to modernize the software architecture, Simware has another very important difference with the AVSM: adds new artefacts at the Interface Level. The interface level is an essential part of Simware because it is providing the capability to integrate easily third-party components and have a seamless interoperability with them.
Simware improves the integrability, composability, interoperability and reusability of the training devices, but because of it is based on the traditional AVSM model, provides a straightforward and riskless path to migrate from any legacy architecture to Simware.
To learn more about how Simware is useful to build faster and better training devices go to http://www.simware.es/training-devices.html
Industry 4.0 promises to optimize the industrial processes, allowing to design and build more complex products, usually “smart” and connected, faster and more efficiently. Industry 4.0 will not only invent new products but also new services, as mass customization, predictive maintenance, online upgrade of products after they are sold (in the same way that software has come to be updated), etc.
Industry 4.0 will leverage networked production systems to produce new generations of smart and connected systems. Smart manufacturing processes will be applied to the development of smart systems, known also as cyber-physical systems or CPS using the Internet of the Things terminology. A Smart system can be defined as a co-engineered interacting network of physical and computational components.
A relevant part of this optimization will be achieved by adopting a design-centric workflow, supported by digital product models, understanding as such a virtual model of the product containing all the elements of mechanical, electrical, electronics and software and its virtual interactions. Under the Industry 4.0 model, product design and development will take place in simulated laboratories and utilize digital fabrication models. Only in this way companies will be able to develop and upgrade smart products faster and at a competitive price to success in the market.
Modeling & Simulation (M&S) technologies and platforms must evolve in order to meet the new requirements requested by Industry 4.0. In the same way that the industry embraces the IoT concepts, both in their life cycle processes and the products and services they provide to the customers, support technologies as is M&S must evolve to the network, embracing the new concept of the Internet of the Simulations or IoS. IoS is about the evolution of the simulation products and solutions from their proprietary and stovepipe architectures, designed to work standalone, to Net-Centric, open and interoperable solutions ready to connect and collaborate with smart systems.
IoS allows to deploy the models and simulations as services in the Cloud, enabling new business models as M&S as a Service (MSaaS), Simulation Platforms as a Service (SPaaS) or Web based Training (WBT). IoS is a lever for many key processes in the engineering life cycle of a smart product, from its conception to its deployment, enabling important improvements in productivity, collaboration and lead times.
IoS requires a new "technology infrastructure", that allows to provide simulation services with a hybrid deployment, combining some components onsite and others on the cloud. Our Simware platform is the leading networked technological infrastructure for IoS. It is providing the mechanisms to connect the simulators to the network and to share data between the publishers and subscribers or consumers of the data. Simware is the first and only microservices architecture for simulation in the market, specifically designed to support the development of real time and Net-Centric simulation products as the integration of many small and easily manageable components.
Simware platform is useful both as a development technical framework and as an integration and deployment infrastructure. Simware is an agile and flexible set of tools, libraries and APIs that supports the whole life cycle of the system engineering of any smart product : from its conception to its retirement.
Visit this page to know further about how Simware and IOS are enabling new business models in the Industry 4.0 : http://www.simware.es/industry-40.html
Only by bringing agility and lean principles & best practices to the development of the simulation products, M&S industry will achieve economies of scale, increasing the productivity and the relationship with the customer.
Go to this Linkedin post, www.linkedin.com/pulse/introducing-agility-development-your-simulation-lopez-rodriguez, to read about how Agility can be introduced in the development of simulation systems in your organization and how Simware can support you in this effort.
One of the main challenges to solve before we can evolve real time distributed simulations to the network, fully connected in the Internet of Simulations, it is how to deal with in an effective way with multiple architectures and protocols. Lead users of distributed simulation, the military simulation & training community, has been working to solve this huge challenge for a long time and the main solutions has been mainly focused on the development of complex gateways solutions that connect the individual simulators' architectures. Gateways based solutions are hard to scale and introduce many restrictions in the interoperability, because the flow of information between the simulators is limited to the capabilities of the gateway.
This problem has been already a big one when trying to connect only a few man-in-the-loop (virtual) simulators in a common synthetic environment but it is becoming in a much bigger one now that simulation is also requested to integrate with real and live systems in the network. In this case the potential number of architectures and protocols involved is enormous when you compared with the few protocols and architectures in use in the military sim & training domain. For example, the Internet of the Things is opening new exciting opportunities for the real time simulations, as a type of Cyber Physical System or CPS connected to the IoT compliant systems. (to know more take a look to my former post in this blog).
To solve this challenge, in Simware, we are taking a more holistic approach to this problem and we are founding our technology in our Data-Centric and Layered Simulation Architecture : LSA. LSA is the first distributed simulation architecture designed to meet the specific simulation requirements of IoT systems dealing with multiple architectures and protocols.
LSA will not only allow to expand the applications of real time simulations to the IoT but also will enable new business models for the traditional markets of simulations as flight simulation as it is discussed in this blog.
Our Simware product-line leverages LSA to converge multiple standards and protocols in a common data-centric simulation platform. Simware, just out-of-the-box, is offering integration between DDS, HLA and Web applications, but it can be extended easily using its APIs to support other protocols and standards, as for example JAUS to connect with robotic systems (to know further about the capabilities provided by this kind of integration take a look to the Citius use case). You can find many resources in our website to know more about LSA & Simware but a good starting point is this post in the blog.
Are you having issues dealing with multi-architecture distributed simulations? Do you want to move toward the Internet of Simulations? Please contact us and we will help you to find the right solution to your pains.
General Manager Simware Solutions
My good friends working at the M&S Technology Division of the ROK's Agency for Defense Development (commonly known as ADD) has just made a very interesting presentation of the results of one of their simulation projects at SIMULTECH 2016 conference. The paper "A DDS-based Distributed Simulation for Anti-Air Missile Systems" is another example of the use of DDS when HLA performance and scalability is not good enought for the purposes of the simulation exercise. In this paper, authors, Mr Dohyung, Mr Hyun-Shik and Mr Seong Wool, explain how they evolved ADD-Sim environment to support DDS in order to be able to run a distributed simulation for air-defence operations.
Experiments performed with this DDS-based distributed environments have shown that you can distribute the computation of many simulation models in several machines without any penalty in performance when compared with running in only one node. More interesting is the benchmark they did DDS vs HLA for this scenario, they run ADD-Sim with DDS and HLA and compared the results: DDS deployment showed better scalability while HLA showed a significant performance degradation when dealing with more than 1,000 updates per unit sim time. You can know more about this development going to the proceedings of Simultech.
ADD's results confirm our own results made with the deployment of Simware based solutions on HLA and DDS networks in our lab and also in many real deployments. Even when Simware platform is compliant with both standards, we recommend to deploy Simware on DDS if you want to have real time deterministic performance in a distributed environment or when you are dealing with many member and/or entities in the network.
General Manager Simware Solutions
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