High-level introduction to the OMG Data Distribution Service (DDS) standard and how it provides values beyond what is possible with traditional messaging middleware such as JMS or AMQP.
This presentation gives a brief, semi-technical introduction to Data Distribution Service (DDS) technology from the Object Management Group. The focus is on the business benefits of the technology generally, not on RTI's implementation in particular.
Webinar: Understanding the System Center suite & Windows Server 2012 Sentri
This document discusses datacenter management and provides options for managing mobile users, virtualization, security, and costs. It compares traditional and virtualized datacenters and approaches for on-premises and off-premises dynamic data centers. The System Center suite is presented as providing a productive, predictable, and flexible infrastructure that can manage applications across private and public clouds using common tools.
This presentation is part of the course "184.742 Advanced Services Engineering" at The Vienna University of Technology, in Winter Semester 2012. Check the course at: http://www.infosys.tuwien.ac.at/teaching/courses/ase/
Scayl- 2012 NAB Keynote Bill Kallman- Cloud Trendsscayl
The document summarizes key trends in cloud computing solutions for audio/video ecosystems. It notes that video traffic is increasing dramatically and will account for 90% of consumer internet traffic by 2012. It then discusses different cloud usage models and architectures that can provide benefits like speed, unlimited storage capacity, privacy and security at low cost. The document focuses on Scayl, a new service that aims to reinvent email by allowing high quality media sharing through a hybrid cloud model for direct delivery at high speeds while maintaining privacy and security.
Management High-level overview of the OMG Data Distribution Service (DDS)Gerardo Pardo-Castellote
This document provides a good management-lever introduction to the Data-Distribution Service (DDS) technology and capabilities. It was prepared by the OMG at the request of the US Navy in order to educate on the data-centric software architectural principles of DDS and how they can help meet its agility and cost-control requirements.
Interoperability demonstration between 5 different products that implement the OMG DDS Interoperability Wire Protocol (DDS-RTPS).
The demonstration took place at the March 2011 OMG technical meeting in Washington DC.
The following companies demonstrated interoperability between their products: RTI (Connext DDS). TwinOaks Computing (CoreDX), PrismTech (OpenSpliceDDS), Gallium Visual Systems/Kongsberg (Compass DDS), IBM.
Presentation of the DDS Interoperability demo performed in Washington DC between RTI, TwinOaks and PrismTech.
This demonstration shows the use of the DDS-RTPS interoperability protocol in 9 different scenarios.
This presentation gives a brief, semi-technical introduction to Data Distribution Service (DDS) technology from the Object Management Group. The focus is on the business benefits of the technology generally, not on RTI's implementation in particular.
Webinar: Understanding the System Center suite & Windows Server 2012 Sentri
This document discusses datacenter management and provides options for managing mobile users, virtualization, security, and costs. It compares traditional and virtualized datacenters and approaches for on-premises and off-premises dynamic data centers. The System Center suite is presented as providing a productive, predictable, and flexible infrastructure that can manage applications across private and public clouds using common tools.
This presentation is part of the course "184.742 Advanced Services Engineering" at The Vienna University of Technology, in Winter Semester 2012. Check the course at: http://www.infosys.tuwien.ac.at/teaching/courses/ase/
Scayl- 2012 NAB Keynote Bill Kallman- Cloud Trendsscayl
The document summarizes key trends in cloud computing solutions for audio/video ecosystems. It notes that video traffic is increasing dramatically and will account for 90% of consumer internet traffic by 2012. It then discusses different cloud usage models and architectures that can provide benefits like speed, unlimited storage capacity, privacy and security at low cost. The document focuses on Scayl, a new service that aims to reinvent email by allowing high quality media sharing through a hybrid cloud model for direct delivery at high speeds while maintaining privacy and security.
Management High-level overview of the OMG Data Distribution Service (DDS)Gerardo Pardo-Castellote
This document provides a good management-lever introduction to the Data-Distribution Service (DDS) technology and capabilities. It was prepared by the OMG at the request of the US Navy in order to educate on the data-centric software architectural principles of DDS and how they can help meet its agility and cost-control requirements.
Interoperability demonstration between 5 different products that implement the OMG DDS Interoperability Wire Protocol (DDS-RTPS).
The demonstration took place at the March 2011 OMG technical meeting in Washington DC.
The following companies demonstrated interoperability between their products: RTI (Connext DDS). TwinOaks Computing (CoreDX), PrismTech (OpenSpliceDDS), Gallium Visual Systems/Kongsberg (Compass DDS), IBM.
Presentation of the DDS Interoperability demo performed in Washington DC between RTI, TwinOaks and PrismTech.
This demonstration shows the use of the DDS-RTPS interoperability protocol in 9 different scenarios.
This document provides a summary of a masterclass on building distributed real-time systems using the Data Distribution Service (DDS). The class covers DDS concepts and technology, including runtime services, development tools, and standards. It discusses how DDS enables a data-centric model and global data space to support high-performance, scalable, and reliable real-time systems that interact directly with the physical world.
The document introduces the Object Management Group's Data Distribution Service (OMG DDS) middleware specification. It describes how DDS provides a standard for integrating real-time systems that must interact with the external environment. It addresses the challenges of integrating large, complex systems with increasing data volumes and speeds from multiple sources. DDS uses a data-centric approach based on a shared data model to loosely couple applications and reduce integration complexity. It has seen broad adoption across industries and is mandated for several Department of Defense programs.
Interoperability for Intelligence Applications using Data-Centric MiddlewareGerardo Pardo-Castellote
Presentation at the May 2012 Intelligence Workshop held in Rome Italy.
Interoperability is key to reducing cost in the development and maintenance of applications that span multiple providers or must be supported over long periods of time. This presentation describes the role of network middleware technologies in such systems and how the use of a data-centric middleware, such as OMG DDS, makes developing such systems easier and more cost-effective.
Communication Patterns Using Data-Centric Publish/SubscribeSumant Tambe
Fundamental to any distributed system are communication patterns: point-to-point, request-reply, transactional queues, and publish-subscribe. Large distributed systems often employ two or more communication patterns. Using a single middleware that supports multiple communication patterns is a very cost-effective way of developing and maintaining large distributed systems. This talk will begin with an introduction of Data Distribution Service (DDS) – an OMG standard – that supports data-centric publish-subscribe communication for real-time distributed systems. DDS separates state management and distribution from application logic and supports discoverable data models. The talk will then describe how RTI Connext Messaging goes beyond vanilla DDS and implements various communication patterns including request-reply, command-response, and guaranteed delivery. You will also learn how these patterns can be combined to create interesting variations when the underlying substrate is as powerful as DDS. We’ll also discuss APIs for creating high-performance applications using the request-reply communication pattern.
Fundamental to any distributed system are communication patterns: point-to-point, request-reply, transactional queues, and publish-subscribe. Large distributed systems often employ two or more communication patterns. Using a single middleware that supports multiple communication patterns is a very cost-effective way of developing and maintaining large distributed systems. This talk will begin with an introduction of Data Distribution Service (DDS) – an OMG standard – that supports data-centric publish-subscribe communication for real-time distributed systems. DDS separates state management and distribution from application logic and supports discoverable data models. The talk will then describe how RTI Connext Messaging goes beyond vanilla DDS and implements various communication patterns including request-reply, command-response, and guaranteed delivery. You will also learn how these patterns can be combined to create interesting variations when the underlying substrate is as powerful as DDS. We’ll also discuss APIs for creating high-performance applications using the request-reply communication pattern.
Modern Data Management for Federal ModernizationDenodo
Watch full webinar here: https://bit.ly/2QaVfE7
Faster, more agile data management is at the heart of government modernization. However, Traditional data delivery systems are limited in realizing a modernized and future-proof data architecture.
This webinar will address how data virtualization can modernize existing systems and enable new data strategies. Join this session to learn how government agencies can use data virtualization to:
- Enable governed, inter-agency data sharing
- Simplify data acquisition, search and tagging
- Streamline data delivery for transition to cloud, data science initiatives, and more
Standardizing the Data Distribution Service (DDS) API for Modern C++Sumant Tambe
The document discusses the Data Distribution Service (DDS) standard for connecting distributed real-time systems. DDS provides a data-centric publish-subscribe model and quality of service guarantees for integrating sensors, actuators and applications. It describes the key DDS entities including DomainParticipants, Topics, DataWriters and DataReaders. Code examples are given for writing and reading data using the DDS standard.
Getting real-time analytics for devices/application/business monitoring from trillions of events and petabytes of data like companies Netflix, Uber, Alibaba, Paypal, Ebay, Metamarkets do.
Big data and cloud computing are closely intertwined. The cloud is well-suited to handle big data challenges by providing massive scalability, flexible pay-as-you-go pricing, and removing the undifferentiated heavy lifting of managing infrastructure. This allows companies to focus on analyzing large and complex datasets. Examples show how companies use Amazon Web Services to collect petabytes of data from sources like sensors and social media, process it using services like EMR, and gain insights for applications in various industries.
Rethinking Disaster Prepardness to Leverage Resources in a Cloud and Mobile World: Presentation given at the 2012 Tennessee Higher Education Symposium (THEITS) - In many respects the disaster recovery plans of today are based upon the environments of old where commodity hardware, cloud resources and mobile devices didn’t exist. In November of 2011 the Tennessee Board of Regents office became the first public higher education organization to move its ERP system to the cloud by having it hosted at the state’s new data center. The following January, state auditors came on site to perform a routine biennial audit. The audit process included an information systems and disaster recovery component which led to a complete rethinking of disaster recovery in the new environment. This presentation chronicled the issues of moving mission critical systems to the cloud and how cloud resources from various sources coupled with mobile devices can be incorporated for cost effective disaster recovery planning.
Introduction to Modern Data Virtualization 2021 (APAC)Denodo
Watch full webinar here: https://bit.ly/2XXyc3R
“Through 2022, 60% of all organisations will implement data virtualization as one key delivery style in their data integration architecture," according to Gartner. What is data virtualization and why is its adoption growing so quickly? Modern data virtualization accelerates that time to insights and data services without copying or moving data.
Watch on-demand this webinar to learn:
- Why organizations across the world are adopting data virtualization
- What is modern data virtualization
- How data virtualization works and how it compares to alternative approaches to data integration and management
- How modern data virtualization can significantly increase agility while reducing costs
Introduction to Modern Data Virtualization (US)Denodo
Watch full webinar here: https://bit.ly/3uyvxN5
“Through 2022, 60% of all organizations will implement data virtualization as one key delivery style in their data integration architecture," according to Gartner. What is data virtualization and why is its adoption growing so quickly? Modern data virtualization accelerates that time to insights and data services without copying or moving data.
Watch this webinar to learn:
- Why organizations across the world are adopting data virtualization
- What is modern data virtualization
- How data virtualization works and how it compares to alternative approaches to data integration and management
- How modern data virtualization can significantly increase agility while reducing costs
- How to easily get started with Denodo Standard 8.0
Developed by Google’s Artificial Intelligence division, the Sycamore quantum processor boasts 53 qubits1.
In 2019, it achieved a feat that would take a state-of-the-art supercomputer 10,000 years to accomplish: completing a specific task in just 200 seconds1
REAL-TIME INTRUSION DETECTION SYSTEM FOR BIG DATAijp2p
The objective of the proposed system is to integrate the high volume of data along with the important
considerations like monitoring a wide array of heterogeneous security. When a real time cyber attack
occurred, the Intrusion Detection System automatically store the log in distributed environment and
monitor the log with existing intrusion dictionary. At the same time the system will check and categorize the
severity of the log to high, medium, and low respectively. After the categorization, the system will
automatically take necessary action against the user-unit with respect to the severity of the log. The
advantage of the system is that it utilize anomaly detection, evaluates data and issue alert message or
reports based on abnormal behaviour.
This document discusses cloud computing, big data, Hadoop, and data analytics. It begins with an introduction to cloud computing, explaining its benefits like scalability, reliability, and low costs. It then covers big data concepts like the 3 Vs (volume, variety, velocity), Hadoop for processing large datasets, and MapReduce as a programming model. The document also discusses data analytics, describing different types like descriptive, diagnostic, predictive, and prescriptive analytics. It emphasizes that insights from analyzing big data are more valuable than raw data. Finally, it concludes that cloud computing can enhance business efficiency by enabling flexible access to computing resources for tasks like big data analytics.
Big Data and Fast Data combined – is it possible ? Introduction aux architectures Big Data. M. Ulises Fasoli, Senior Consultant Trivadis. Conférence donnée dans le cadre du Swiss Data Forum du 24 novembre 2015 à Lausanne
Horses for Courses: Database RoundtableEric Kavanagh
The blessing and curse of today's database market? So many choices! While relational databases still dominate the day-to-day business, a host of alternatives has evolved around very specific use cases: graph, document, NoSQL, hybrid (HTAP), column store, the list goes on. And the database tools market is teeming with activity as well. Register for this special Research Webcast to hear Dr. Robin Bloor share his early findings about the evolving database market. He'll be joined by Steve Sarsfield of HPE Vertica, and Robert Reeves of Datical in a roundtable discussion with Bloor Group CEO Eric Kavanagh. Send any questions to info@insideanalysis.com, or tweet with #DBSurvival.
Use of the Data-Distribution Service (DDS) --a publish-subscribe middleware standard from OMG -- as a communication infrastructure for Event Processing Engines.
Watch full webinar here: https://bit.ly/2xc6IO0
To solve these challenges, according to Gartner "through 2022, 60% of all organizations will implement data virtualization as one key delivery style in their data integration architecture". It is clear that data virtualization has become a driving force for companies to implement agile, real-time and flexible enterprise data architecture.
In this session we will look at the data integration challenges solved by data virtualization, the main use cases and examine why this technology is growing so fastly. You will learn:
- What data virtualization really is
- How it differs from other enterprise data integration technologies
- Why data virtualization is finding enterprise-wide deployment inside some of the largest organizations
DDS Security Version 1.2 was adopted in 2024. This revision strengthens support for long runnings systems adding new cryptographic algorithms, certificate revocation, and hardness against DoS attacks.
From its first use case that enabled distributed communications for US Navy ships to the autonomous systems of today, the DDS family of standards has enabled new generations of applications to run reliably, rapidly and securely, regardless of distance or scale.
To commemorate the 20th year milestone, the DDS Foundation is creating presentations that highlight the 14 specifications in the DDS standard, along with selected real-world use cases.
This presentation introduces some of the original use-cases and experiments, along with a brief history of the Standards.
A recorded video of the presentation is available at this URL
https://www.brighttalk.com/webcast/12231/602966
More Related Content
Similar to DDS: The data-centric future beyond message-based integration
This document provides a summary of a masterclass on building distributed real-time systems using the Data Distribution Service (DDS). The class covers DDS concepts and technology, including runtime services, development tools, and standards. It discusses how DDS enables a data-centric model and global data space to support high-performance, scalable, and reliable real-time systems that interact directly with the physical world.
The document introduces the Object Management Group's Data Distribution Service (OMG DDS) middleware specification. It describes how DDS provides a standard for integrating real-time systems that must interact with the external environment. It addresses the challenges of integrating large, complex systems with increasing data volumes and speeds from multiple sources. DDS uses a data-centric approach based on a shared data model to loosely couple applications and reduce integration complexity. It has seen broad adoption across industries and is mandated for several Department of Defense programs.
Interoperability for Intelligence Applications using Data-Centric MiddlewareGerardo Pardo-Castellote
Presentation at the May 2012 Intelligence Workshop held in Rome Italy.
Interoperability is key to reducing cost in the development and maintenance of applications that span multiple providers or must be supported over long periods of time. This presentation describes the role of network middleware technologies in such systems and how the use of a data-centric middleware, such as OMG DDS, makes developing such systems easier and more cost-effective.
Communication Patterns Using Data-Centric Publish/SubscribeSumant Tambe
Fundamental to any distributed system are communication patterns: point-to-point, request-reply, transactional queues, and publish-subscribe. Large distributed systems often employ two or more communication patterns. Using a single middleware that supports multiple communication patterns is a very cost-effective way of developing and maintaining large distributed systems. This talk will begin with an introduction of Data Distribution Service (DDS) – an OMG standard – that supports data-centric publish-subscribe communication for real-time distributed systems. DDS separates state management and distribution from application logic and supports discoverable data models. The talk will then describe how RTI Connext Messaging goes beyond vanilla DDS and implements various communication patterns including request-reply, command-response, and guaranteed delivery. You will also learn how these patterns can be combined to create interesting variations when the underlying substrate is as powerful as DDS. We’ll also discuss APIs for creating high-performance applications using the request-reply communication pattern.
Fundamental to any distributed system are communication patterns: point-to-point, request-reply, transactional queues, and publish-subscribe. Large distributed systems often employ two or more communication patterns. Using a single middleware that supports multiple communication patterns is a very cost-effective way of developing and maintaining large distributed systems. This talk will begin with an introduction of Data Distribution Service (DDS) – an OMG standard – that supports data-centric publish-subscribe communication for real-time distributed systems. DDS separates state management and distribution from application logic and supports discoverable data models. The talk will then describe how RTI Connext Messaging goes beyond vanilla DDS and implements various communication patterns including request-reply, command-response, and guaranteed delivery. You will also learn how these patterns can be combined to create interesting variations when the underlying substrate is as powerful as DDS. We’ll also discuss APIs for creating high-performance applications using the request-reply communication pattern.
Modern Data Management for Federal ModernizationDenodo
Watch full webinar here: https://bit.ly/2QaVfE7
Faster, more agile data management is at the heart of government modernization. However, Traditional data delivery systems are limited in realizing a modernized and future-proof data architecture.
This webinar will address how data virtualization can modernize existing systems and enable new data strategies. Join this session to learn how government agencies can use data virtualization to:
- Enable governed, inter-agency data sharing
- Simplify data acquisition, search and tagging
- Streamline data delivery for transition to cloud, data science initiatives, and more
Standardizing the Data Distribution Service (DDS) API for Modern C++Sumant Tambe
The document discusses the Data Distribution Service (DDS) standard for connecting distributed real-time systems. DDS provides a data-centric publish-subscribe model and quality of service guarantees for integrating sensors, actuators and applications. It describes the key DDS entities including DomainParticipants, Topics, DataWriters and DataReaders. Code examples are given for writing and reading data using the DDS standard.
Getting real-time analytics for devices/application/business monitoring from trillions of events and petabytes of data like companies Netflix, Uber, Alibaba, Paypal, Ebay, Metamarkets do.
Big data and cloud computing are closely intertwined. The cloud is well-suited to handle big data challenges by providing massive scalability, flexible pay-as-you-go pricing, and removing the undifferentiated heavy lifting of managing infrastructure. This allows companies to focus on analyzing large and complex datasets. Examples show how companies use Amazon Web Services to collect petabytes of data from sources like sensors and social media, process it using services like EMR, and gain insights for applications in various industries.
Rethinking Disaster Prepardness to Leverage Resources in a Cloud and Mobile World: Presentation given at the 2012 Tennessee Higher Education Symposium (THEITS) - In many respects the disaster recovery plans of today are based upon the environments of old where commodity hardware, cloud resources and mobile devices didn’t exist. In November of 2011 the Tennessee Board of Regents office became the first public higher education organization to move its ERP system to the cloud by having it hosted at the state’s new data center. The following January, state auditors came on site to perform a routine biennial audit. The audit process included an information systems and disaster recovery component which led to a complete rethinking of disaster recovery in the new environment. This presentation chronicled the issues of moving mission critical systems to the cloud and how cloud resources from various sources coupled with mobile devices can be incorporated for cost effective disaster recovery planning.
Introduction to Modern Data Virtualization 2021 (APAC)Denodo
Watch full webinar here: https://bit.ly/2XXyc3R
“Through 2022, 60% of all organisations will implement data virtualization as one key delivery style in their data integration architecture," according to Gartner. What is data virtualization and why is its adoption growing so quickly? Modern data virtualization accelerates that time to insights and data services without copying or moving data.
Watch on-demand this webinar to learn:
- Why organizations across the world are adopting data virtualization
- What is modern data virtualization
- How data virtualization works and how it compares to alternative approaches to data integration and management
- How modern data virtualization can significantly increase agility while reducing costs
Introduction to Modern Data Virtualization (US)Denodo
Watch full webinar here: https://bit.ly/3uyvxN5
“Through 2022, 60% of all organizations will implement data virtualization as one key delivery style in their data integration architecture," according to Gartner. What is data virtualization and why is its adoption growing so quickly? Modern data virtualization accelerates that time to insights and data services without copying or moving data.
Watch this webinar to learn:
- Why organizations across the world are adopting data virtualization
- What is modern data virtualization
- How data virtualization works and how it compares to alternative approaches to data integration and management
- How modern data virtualization can significantly increase agility while reducing costs
- How to easily get started with Denodo Standard 8.0
Developed by Google’s Artificial Intelligence division, the Sycamore quantum processor boasts 53 qubits1.
In 2019, it achieved a feat that would take a state-of-the-art supercomputer 10,000 years to accomplish: completing a specific task in just 200 seconds1
REAL-TIME INTRUSION DETECTION SYSTEM FOR BIG DATAijp2p
The objective of the proposed system is to integrate the high volume of data along with the important
considerations like monitoring a wide array of heterogeneous security. When a real time cyber attack
occurred, the Intrusion Detection System automatically store the log in distributed environment and
monitor the log with existing intrusion dictionary. At the same time the system will check and categorize the
severity of the log to high, medium, and low respectively. After the categorization, the system will
automatically take necessary action against the user-unit with respect to the severity of the log. The
advantage of the system is that it utilize anomaly detection, evaluates data and issue alert message or
reports based on abnormal behaviour.
This document discusses cloud computing, big data, Hadoop, and data analytics. It begins with an introduction to cloud computing, explaining its benefits like scalability, reliability, and low costs. It then covers big data concepts like the 3 Vs (volume, variety, velocity), Hadoop for processing large datasets, and MapReduce as a programming model. The document also discusses data analytics, describing different types like descriptive, diagnostic, predictive, and prescriptive analytics. It emphasizes that insights from analyzing big data are more valuable than raw data. Finally, it concludes that cloud computing can enhance business efficiency by enabling flexible access to computing resources for tasks like big data analytics.
Big Data and Fast Data combined – is it possible ? Introduction aux architectures Big Data. M. Ulises Fasoli, Senior Consultant Trivadis. Conférence donnée dans le cadre du Swiss Data Forum du 24 novembre 2015 à Lausanne
Horses for Courses: Database RoundtableEric Kavanagh
The blessing and curse of today's database market? So many choices! While relational databases still dominate the day-to-day business, a host of alternatives has evolved around very specific use cases: graph, document, NoSQL, hybrid (HTAP), column store, the list goes on. And the database tools market is teeming with activity as well. Register for this special Research Webcast to hear Dr. Robin Bloor share his early findings about the evolving database market. He'll be joined by Steve Sarsfield of HPE Vertica, and Robert Reeves of Datical in a roundtable discussion with Bloor Group CEO Eric Kavanagh. Send any questions to info@insideanalysis.com, or tweet with #DBSurvival.
Use of the Data-Distribution Service (DDS) --a publish-subscribe middleware standard from OMG -- as a communication infrastructure for Event Processing Engines.
Watch full webinar here: https://bit.ly/2xc6IO0
To solve these challenges, according to Gartner "through 2022, 60% of all organizations will implement data virtualization as one key delivery style in their data integration architecture". It is clear that data virtualization has become a driving force for companies to implement agile, real-time and flexible enterprise data architecture.
In this session we will look at the data integration challenges solved by data virtualization, the main use cases and examine why this technology is growing so fastly. You will learn:
- What data virtualization really is
- How it differs from other enterprise data integration technologies
- Why data virtualization is finding enterprise-wide deployment inside some of the largest organizations
Similar to DDS: The data-centric future beyond message-based integration (20)
DDS Security Version 1.2 was adopted in 2024. This revision strengthens support for long runnings systems adding new cryptographic algorithms, certificate revocation, and hardness against DoS attacks.
From its first use case that enabled distributed communications for US Navy ships to the autonomous systems of today, the DDS family of standards has enabled new generations of applications to run reliably, rapidly and securely, regardless of distance or scale.
To commemorate the 20th year milestone, the DDS Foundation is creating presentations that highlight the 14 specifications in the DDS standard, along with selected real-world use cases.
This presentation introduces some of the original use-cases and experiments, along with a brief history of the Standards.
A recorded video of the presentation is available at this URL
https://www.brighttalk.com/webcast/12231/602966
Introduction to DDS: Context, Information Model, Security, and Applications.Gerardo Pardo-Castellote
Introduction to the Data-Distribution Service (DDS): Context and Applications.
This 50 minute presentation summarizes the main features of DDS including the information model, the type system, and security as well as how typical applications use DDS.
It was presented at the Canadian Government Information Day in Ottawa on September 2018.
There is also a video of this presentation at https://www.youtube.com/watch?v=6iICap5G7rw.
This Object Management Group (OMG) RFP solicits submissions identifying and defining mechanisms to achieve integration between DDS infrastructures and TSN networks. The goal is to provide all artifacts needed to support the design, deployment and execution of DDS systems over TSN networks.
The DDS-TSN integration specification sought shall realize the following functionality:
● Define mechanisms that provide the information required for TSN-enabled networks to calculate any network schedules needed to deploy a DDS system.
OMG RFP
● Identify those parts of the set of the IEEE TSN standards that are relevant for a DDS-TSN integration and indicate how the DDS aspects are mapped onto, or related to, the associated TSN aspects. Examples include TSN- standardized information models for calculating system-wide schedules and configuring network equipment.
● Identify and specify necessary extensions to the [DDSI-RTPS] and [DDS- SECURITY] specifications, if any, to allow DDS infrastructures to use TSN- enabled networks as their transport while maintaining interoperability between different DDS implementations.
● Identify and specify necessary extensions to the DDS and DDS- XML specification, if any, to allow declaration of TSN-specific properties or quality of service attributes.
A NEW ARCHITECTURE PROPOSAL TO INTEGRATE OPC UA, DDS & TSN.
Suppliers and end users need a complete solution to address the complexity of future industrial automation systems. These systems require:
• Interoperability to allow devices and independent software applications from multiple suppliers to work together seamlessly
• Extensibility to incorporate future large or intelligent systems
• Performance and flexibility to handle challenging deployments and use cases
• Robustness to guarantee continuity of operation despite partial failures
• Integrity and fine-grained security to protect against cyber attacks
• Widespread support for an industry standard
This document proposes a new technical architecture to build this future. The design combines the best of the OPC Unified Architecture (OPC UA), Data Distribution Service (DDS), and Time-Sensitive Networking (TSN) standards. It will connect the factory floor to the enterprise, sensors to cloud, and real-time devices to work cells. This proposal aims to define and standardize the architecture to unify the industry.
The document provides an overview of the DDS-XRCE specification, which defines an Agent-Client communication model to enable the use of the DDS data distribution service (DDS) in extremely resource-constrained networks. It describes the motivation for DDS-XRCE and its key aspects, including the message structure, interaction model, supported deployment scenarios, and how it provides security through the use of a client key.
The document describes a demonstration of interoperability between 5 vendor DDS security implementations using a shapes demo application. The demo consists of 6 scenarios that illustrate different aspects of DDS security configuration and functionality, including controlling access to the domain, enabling open access to selected topics, comparing data integrity vs encryption, protecting metadata, securing discovery, and fine-grained access control at the topic level. Each scenario varies the security governance and permission files to achieve the desired access control configuration.
Applying MBSE to the Industrial IoT: Using SysML with Connext DDS and SimulinkGerardo Pardo-Castellote
This document summarizes a presentation about applying model-based systems engineering (MBSE) to industrial internet of things (IIoT) systems using the SysML modeling language, Connext DDS middleware, and Simulink. It discusses how SysML can be used to design interfaces, applications, and quality of service policies for DDS-connected systems. The presentation also provides examples of integrating MagicDraw, Simulink, and Connext DDS to enable translating SysML models into implementations and deployments of distributed IIoT applications and components.
One of the most important challenges that system designers and system integrators face when deploying complex Industrial Internet of Things (IoT) systems is the integration of different connectivity solutions and standards. At RTI, we are constantly working to accelerate the Industrial IoT revolution. Over the past few years, we have developed standard connectivity gateways to ensure that DDS systems can easily integrate with other core connectivity frameworks.
This year, we developed a standard OPC UA/DDS Gateway, a bridge between two of the most well-known Industrial IoT connectivity frameworks. We are excited to announce that the gateway was just adopted by the Object Management Group (OMG).
In this webinar, we will dive deeper into the importance of choosing a baseline core connectivity standard for the Industrial IoT and how to ensure all system components are fully integrated. Attendees will also learn:
How the OPC UA/DDS Gateway specification was developed and how it works
How to leverage the Gateway to enable DDS and OPC UA applications to interoperate transparently
About the first standard connectivity gateway released with RTI Web Integration Service in Connext DDS 5.3
Gateways are a critical component of system interoperability and we will keep working to help companies accelerate Industrial IoT adoption.
This document defines an OPC UA/DDS gateway specification. It specifies how to bridge the OPC UA and DDS protocols by defining mappings between their data models, type systems and core services. This includes mapping OPC UA data types, services and subscriptions to DDS data types and topics as well as mapping DDS data types and the global data space to OPC UA address space objects. Configuration formats are also defined to allow configuration of OPC UA to DDS and DDS to OPC UA bridges.
This is the DDS-XRCE 1.0 Beta specification adopted by the OMG March 2018.
The purpose of DDS-XRCE is to enable resource-constrained devices to participate in DDS communication, while at the same time allowing those devices to be disconnected for long periods of time but still be discoverable by other DDS applications.
DDS-XRCE defines a wire protocol, the DDS-XRCE protocol, to be used between an XRCE Client and XRCE Agent. The XRCE Agent is a DDS Participant in the DDS Global Data Space. The DDS-XRCE protocol allows the client to use the XRCE Agent as a proxy in order to produce and consume data in the DDS Global Data Space.
Demonstrates interoperability of 5 independent products that implement the Data-Distribution Service (DDS) Security Standard
(https://www.omg.org/spec/DDS-SECURITY/).
Tests the following implementations: RTI Connext DDS, Twin Oaks Computing CoreDX DDS, Kongsberg InterComm DDS, ADLink Vortex DDS Cafe, and Object Computing Inc OpenDDS.
Demonstrates interoperability of 3 independent products that implement the Data-Distribution Service (DDS) Security Standard
(https://www.omg.org/spec/DDS-SECURITY/).
Tests the following implementations: RTI Connext DDS, Twin Oaks Computing CoreDX DDS, and Kongsberg InterComm DDS.
This specification provides the following additional facilities to DDS [DDS] implementations and users:
* Type System. The specification defines a model of the data types that can be used for DDS Topics. The type system is formally defined using UML. The Type System is de- fined in section 7.2 and its subsections. The structural model of this system is defined in the Type System Model in section 7.2.2. The framework under which types can be modi- fied over time is summarized in section 7.2.3, “Type Extensibility and Mutability.” The concrete rules under which the concepts from 7.2.2 and 7.2.3 come together to define compatibility in the face of such modifications are defined in section 7.2.4, “Type Com- patibility.”
* Type Representations. The specification defines the ways in which types described by the Type System may be externalized such that they can be stored in a file or communi- cated over a network. The specification adds additional Type Representations beyond the
DDS-XTypes version 1.2 1
one (IDL [IDL41]) already implied by the DDS specification. Several Type Representa- tions are specified in the subsections of section 7.3. These include IDL (7.3.1), XML (7.3.2), XML Schema (XSD) (7.3.3), and TypeObject (7.3.4).
* Data Representation. The specification defines multiple ways in which objects of the types defined by the Type System may be externalized such that they can be stored in a file or communicated over a network. (This is also commonly referred as “data serializa- tion” or “data marshaling.”) The specification extends and generalizes the mechanisms already defined by the DDS Interoperability specification [RTPS]. The specification in- cludes Data Representations that support data type evolution, that is, allow a data type to change in certain well-defined ways without breaking communication. Two Data Repre- sentations are specified in the subsections of section 7.4. These are Extended CDR (7.4.1, 7.4.2, and 7.4.3) and XML (7.4.4).
* Language Binding. The specification defines multiple ways in which applications can access the state of objects defined by the Type System. The submission extends and gen- eralizes the mechanism currently implied by the DDS specification (“Plain Language Binding”) and adds a Dynamic Language Binding that allows application to access data without compile-time knowledge of its type. The specification also defines an API to de- fine and manipulate data types programmatically. Two Language Bindings are specified in the subsections of section 7.5. These are the Plain Language Binding and the Dynamic Language Binding.
The document describes version 1.1 of the DDS Security specification which defines a security model and plugin architecture to provide information assurance capabilities to DDS implementations, including defining builtin plugins for authentication, access control, encryption, and logging; it also lists normative references and provides an overview of the specification's scope and conformance points.
This document describes the Interface Definition Language (IDL) version 4.2 specification published by the Object Management Group (OMG). It defines the syntax and semantics of IDL, which is used to define interfaces, data types, exceptions, modules and other elements used in CORBA, CCM, and other OMG specifications. The document includes sections on lexical conventions, grammar, scoping rules, standardized annotations, and CORBA/CCM profiles supported by IDL. It is intended to provide a standard way to define interfaces that are independent of specific programming languages.
This the the formal version 1.0 of the DDS Security specification released September 2016. OMG document number formal/2016-08-01.
DDS-Security defines the Security Model and Service Plugin Interface (SPI) architecture for compliant DDS implementations.
The DDS Security Model is enforced by the invocation of these SPIs by the DDS implementation. This specification also defines a set of builtin implementations of these SPIs.
* The specified builtin SPI implementations enable out-of-the box security and interoperability between compliant DDS applications.
* The use of SPIs allows DDS users to customize the behavior and technologies that the DDS implementations use for Information Assurance, specifically customization of Authentication, Access Control, Encryption, Message Authentication, Digital Signing, Logging and Data Tagging.
This specification is a response to the OMG RFP "eXtremely Resource Constrained Environments DDS (DDS- XRCE)"
It defines a DDS-XRCE Service based on a client-server protocol between a resource constrained, low-powered device (client) and an Agent (the server) that enables the device to communicate with a DDS network and publish and subscribe to topics in a DDS domain. The specifications purpose and scope is to ensure that applications based on different vendor’ implementations of the DDS-XRCE Service are compatible and interoperable.
This is the Joint submission by RTI, TwinOaks, and eProsima. Updated September 2017, OMG document number mars/2017-09-18.
inQuba Webinar Mastering Customer Journey Management with Dr Graham HillLizaNolte
HERE IS YOUR WEBINAR CONTENT! 'Mastering Customer Journey Management with Dr. Graham Hill'. We hope you find the webinar recording both insightful and enjoyable.
In this webinar, we explored essential aspects of Customer Journey Management and personalization. Here’s a summary of the key insights and topics discussed:
Key Takeaways:
Understanding the Customer Journey: Dr. Hill emphasized the importance of mapping and understanding the complete customer journey to identify touchpoints and opportunities for improvement.
Personalization Strategies: We discussed how to leverage data and insights to create personalized experiences that resonate with customers.
Technology Integration: Insights were shared on how inQuba’s advanced technology can streamline customer interactions and drive operational efficiency.
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor IvaniukFwdays
At this talk we will discuss DDoS protection tools and best practices, discuss network architectures and what AWS has to offer. Also, we will look into one of the largest DDoS attacks on Ukrainian infrastructure that happened in February 2022. We'll see, what techniques helped to keep the web resources available for Ukrainians and how AWS improved DDoS protection for all customers based on Ukraine experience
Session 1 - Intro to Robotic Process Automation.pdfUiPathCommunity
👉 Check out our full 'Africa Series - Automation Student Developers (EN)' page to register for the full program:
https://bit.ly/Automation_Student_Kickstart
In this session, we shall introduce you to the world of automation, the UiPath Platform, and guide you on how to install and setup UiPath Studio on your Windows PC.
📕 Detailed agenda:
What is RPA? Benefits of RPA?
RPA Applications
The UiPath End-to-End Automation Platform
UiPath Studio CE Installation and Setup
💻 Extra training through UiPath Academy:
Introduction to Automation
UiPath Business Automation Platform
Explore automation development with UiPath Studio
👉 Register here for our upcoming Session 2 on June 20: Introduction to UiPath Studio Fundamentals: https://community.uipath.com/events/details/uipath-lagos-presents-session-2-introduction-to-uipath-studio-fundamentals/
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
"Choosing proper type of scaling", Olena SyrotaFwdays
Imagine an IoT processing system that is already quite mature and production-ready and for which client coverage is growing and scaling and performance aspects are life and death questions. The system has Redis, MongoDB, and stream processing based on ksqldb. In this talk, firstly, we will analyze scaling approaches and then select the proper ones for our system.
The Microsoft 365 Migration Tutorial For Beginner.pptxoperationspcvita
This presentation will help you understand the power of Microsoft 365. However, we have mentioned every productivity app included in Office 365. Additionally, we have suggested the migration situation related to Office 365 and how we can help you.
You can also read: https://www.systoolsgroup.com/updates/office-365-tenant-to-tenant-migration-step-by-step-complete-guide/
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyScyllaDB
Freshworks creates AI-boosted business software that helps employees work more efficiently and effectively. Managing data across multiple RDBMS and NoSQL databases was already a challenge at their current scale. To prepare for 10X growth, they knew it was time to rethink their database strategy. Learn how they architected a solution that would simplify scaling while keeping costs under control.
High performance Serverless Java on AWS- GoTo Amsterdam 2024Vadym Kazulkin
Java is for many years one of the most popular programming languages, but it used to have hard times in the Serverless community. Java is known for its high cold start times and high memory footprint, comparing to other programming languages like Node.js and Python. In this talk I'll look at the general best practices and techniques we can use to decrease memory consumption, cold start times for Java Serverless development on AWS including GraalVM (Native Image) and AWS own offering SnapStart based on Firecracker microVM snapshot and restore and CRaC (Coordinated Restore at Checkpoint) runtime hooks. I'll also provide a lot of benchmarking on Lambda functions trying out various deployment package sizes, Lambda memory settings, Java compilation options and HTTP (a)synchronous clients and measure their impact on cold and warm start times.
Discover top-tier mobile app development services, offering innovative solutions for iOS and Android. Enhance your business with custom, user-friendly mobile applications.
The Department of Veteran Affairs (VA) invited Taylor Paschal, Knowledge & Information Management Consultant at Enterprise Knowledge, to speak at a Knowledge Management Lunch and Learn hosted on June 12, 2024. All Office of Administration staff were invited to attend and received professional development credit for participating in the voluntary event.
The objectives of the Lunch and Learn presentation were to:
- Review what KM ‘is’ and ‘isn’t’
- Understand the value of KM and the benefits of engaging
- Define and reflect on your “what’s in it for me?”
- Share actionable ways you can participate in Knowledge - - Capture & Transfer
What is an RPA CoE? Session 1 – CoE VisionDianaGray10
In the first session, we will review the organization's vision and how this has an impact on the COE Structure.
Topics covered:
• The role of a steering committee
• How do the organization’s priorities determine CoE Structure?
Speaker:
Chris Bolin, Senior Intelligent Automation Architect Anika Systems
6. Everyday Example: Calendaring
Alternative Process #1:
1. Email: ―Meeting Monday at 10:00.‖
2. Email: ―Meeting moved to Tuesday.‖
3. Email: ―Here’s dial-in info for meeting…‖
4. Rick: ―Where do I have to be? When?‖
5. Rick: (sifting through email…)
6
7. Example: Calendaring
Alternative Process #2:
1. Calendar: (add meeting Monday at 10:00)
2. Calendar: (move meeting to Tuesday)
3. Calendar: (add dial-in info)
4. Rick: ―Where do I have to be? When?‖
5. Rick: (check calendar)
7
8. What’s the Difference? State.
Things have attributes “State” (“data”) is a
and characteristics snapshot of those
– The meeting will run 1:00–2:00
in the conference room. attributes and
– My friend’s phone number is characteristics.
555-1234 and he’s currently
grooming his cat.
– The car is blue and is traveling
north from Sunnyvale at 65 Best Practice: operate
mph. on state directly, not
…whether they exist in dialogs about state.
the real world, in the
computer, or both
…whether or not we
observe or acknowledge
them
9. Data-Centricity =
the part of you care about
Describing the world
as it is
at a certain point in time
Implication: State of the world can be maintained by
infrastructure, not each app
10. Not Data-Centricity =
Saying anything else…
―Hey you: go do this.‖
―The thing changed in this way.‖
Implication: State must be inferred, reconstructed, managed by
each app
(Sometimes called “message-centricity”: focus on what’s said
vs. what is)
11. Why is it better to just describe the world?
Reconstructing the state of the world is
hard
– Must infer based on all previous messages
– Maintaining all these messages is expensive
– Each app makes these inferences
=> duplicate effort
People make mistakes
– Many copies of state => may be different =>
bugs
vs.
– Uniform operations on state => fewer bugs
12. So it’s “better.” Who cares?
Faster to implement
=> Save time and money
Easier to integrate and update
=> Protect your investment
More reliable systems
=> Protect your business
12
13. Before We Forget: the Definition
For example, data
structures in IDL file.
A data-centric architecture: Calendar Event =
•Start Time
1. …is based on a data model that is: •Duration
– Appropriately documented— •Location
i.e. understandable by humans
•Organizer
– Formally defined—
i.e. understandable by machines
– Discoverable—i.e. can be found during execution
2. The data model is independent of any domain-
specific functionality / application.
– i.e. made of nouns, not verbs
3. The (instantiated) data model is the only
authoritative source of state in the system.
14. DDS Lets You Observe a Changing World
Other data-centric technologies:
– Databases: SQL
– Web: HTTP (mostly)
…assume the world changes slowly
Not scalable
…use network resources inefficiently 100 apps => 100x load
…are highly centralized
Slow
A few updates/sec
App App
Server
App App
State
App App
Unreliable
Failure here kills many apps
15. DDS Lets You Observe a Changing World
DDS:
…allows you to observe frequent changes
…uses network resources efficiently
…is decentralized
Fast Scalable Managed Reliable
100,000’s updates/sec Load indep. # apps with QoS No single pt. failure
App App App App App App
State: Global Data Space
16. DDS Lets You Observe a Changing World
JBC-P replaced home-brew messaging w/ DDS:
Tracks 20x more objects with fewer failures
…with 97% less code(1.5M lines 50K)
…with 99% less CPU resources (88 cores 0.8)
Fast Scalable Managed Reliable
100,000’s updates/sec Load indep. # apps with QoS No single pt. failure
App App App App App App
State: Global Data Space
17. DDS Lets You Observe a Changing World
Domain: world you’re talking about
Topic: group of similar things Domain
(e.g. Yellowstone Park)
– Similar structure (―type‖) what
– Similar way they change when
over time (―QoS‖) how
Topic
Instance: individual thing (e.g. bears in the park)
DataWriter: source of observations about
part of the world (topic) Instance
(e.g. Yogi the bear)
DataReader: observer of part of the world
(topic)
26. example
DDS communications model
Data Domain Data Domain
New Writer Participant Reader Participant
“Alarm”
Got new “Alarm”
subscriber data
!
Offered Requested
Listener QoS Listener QoS
Participants scope the global data space (domain)
Topics define the data-objects (collections of subjects)
Writers publish data on Topics
Readers subscribe to data on Topics
QoS Policies are used configure the system
Listeners are used to notify the application of events
35. OMG DDS Security:
How to Secure DDS?
DDS Entities are authenticated
DDS Entities access only
domains/Topics/… they are
allowed to
DDS data integrity and
confidentiality is provided
Non-repudiation is enforced
DDS provides availability through
reliable access to data
….while maintaining DDS’s high performance
36
36. OMG DDS Security
: A Pluggable Architecture
OMG RFP accepted in Dec 2010
OMG RFP Response due in June 2011
37 OMG standard Dec 2011-Mar 2012