CoreDX DDS is a communications middleware that uses a publish/subscribe model. It provides dynamic discovery, reliable data transmission, configurable quality of service policies, durable storage of historical data, and data filtering capabilities. CoreDX DDS implements the Data Distribution Service standard to enable interoperability between implementations from different vendors.
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.
OpenSplice DDS enables seamless, timely, scalable and dependable data sharing between distributed applications and network-connected devices. Its technical and operational benefits have propelled adoption across multiple industries, such as Defence and Aerospace, SCADA, Gaming, Cloud Computing, Automotive, etc.
If you want to learn about OpenSplice DDS or discover some of its advanced features, this webcast is for you!
In this two-parts presentation we will cover most of the aspects tied to architecting and developing OpenSplice DDS systems. We will look into Quality of Services, data selectors concurrency and scalability concerns.
We will present the brand-new, and recently finalized, C++ and Java APIs for DDS, including examples of how this can be used with C++11 features. We will show how, increasingly popular, functional languages such as Scala can be used to efficiently and elegantly exploit the massive HW parallelism provided by modern multi-core processors.
Finally we will present some OpenSplice specific extensions for dealing very high-volumes of data – meaning several millions of messages per seconds.
The Data Distribution Service for Real-Time Systems (DDS) is an Object Management Group (OMG) standard for publish/subscribe designed to address the needs of a large class of mission- and business-critical distributed real-time systems and system of systems. The DDS standard was formally adopted in 2004 and in less than five years from its inception has experienced swift adoption in a wide variety of application domains. These application domains are characterized by the need to distribute high volumes of data with predictable low latencies, such as, Radar Processors, Flying and Land Drones, Combat Management Systems, Air Traffic Management, High Performance Telemetry, Large Scale Supervisory Systems, and Automated Stocks and Options Trading. Along with wide commercial adoption, the DDS Standard has been recommended and mandated as the technology for real-time data distribution by key administrations worldwide such as the US Navy, the DoD Information-Technology Standards Registry (DISR), the UK MoD, and EUROCONTROL.
This two-part Tutorial will cover most of the key aspects of DDS to ensure that you can proficiently start using it for designing or developing your next system. In brief this tutorial will get you jump-started into DDS.
DDS is a very powerful technology built around a few simple and orthogonal concepts. If you understand the core concepts then you can really quickly get up to speed and start exploiting all of its power. On the other hand, if you haven’t grasped the key abstractions you might not be able to exploit all the benefits that DDS can bring.
This presentation provides you with an introduction to the core DDS concepts and illustrates how to program DDS applications. The new C++ and Java API will be explained and used throughout the webcast for coding examples thus giving you a chance to learn the new API from one of the main authors!
The document discusses OpenSplice DDS, an implementation of the OMG DDS standard for data distribution. It provides an overview of key DDS concepts like the global data space, publishers/subscribers, topics/instances/samples, partitioning, filtering, and quality of service (QoS). DDS aims to address data distribution challenges across a wide range of applications through high performance, scalability, and interoperability between implementations.
The DDS specification provides fine-grained control over the real-time behaviour, dependability, and performance of DDS applications by means of a rich set of QoS Policies. The challenge for many DDS users is that the specifications explains very clearly how each QoS allows to control very specific aspects of data distribution yet it provides no hints on how different QoS should be composed to control complex properties such as the consistency model, or to impose end-to-end real-time scheduling decision. This half-day tutorial will fill this gap by providing attendees with (1) an explanation of how the various QoS compose, and (2) providing attendees with a series of QoS-composition Patters that can be used to control macro-properties of an application, such as the consistency model.
This 4-page document provides a product description for Shared Oracle Hosting (Linux) offered by the Utah Department of Technology Services (DTS). It includes details on features, rates and billing, ordering process, responsibilities of DTS and agencies, and service level metrics. DTS provides shared Oracle database environments on Linux in the state data center, including management, backups, monitoring, and support. Pricing is based on database size with a minimum of $200 per month for the first 2GB and $140 for each additional 2GB.
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, such as, Power Generation, Large Scale SCADA, Air Traffic Control and Management, Smart Cities, Smart Grids, Vehicles, Medical Devices, Simulation, Aerospace, Defense and Financial Trading.
This two part webcast provides an in depth introduction to DDS – the universal data sharing technology. Specifically, we will introduce (1) the DDS conceptual model and data-centric design, (2) DDS data modeling fundamentals, (3) the complete set of C++ and Java API, (4) the most important programming, data modeling and QoS Idioms, and (5) the integration between DDS and web applications.
After attending this webcast you will understand how to exploit DDS architectural features when designing your next system, how to write idiomatic DDS applications in C++ and Java and what are the fundamental patterns that you should adopt in your applications.
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.
OpenSplice DDS enables seamless, timely, scalable and dependable data sharing between distributed applications and network-connected devices. Its technical and operational benefits have propelled adoption across multiple industries, such as Defence and Aerospace, SCADA, Gaming, Cloud Computing, Automotive, etc.
If you want to learn about OpenSplice DDS or discover some of its advanced features, this webcast is for you!
In this two-parts presentation we will cover most of the aspects tied to architecting and developing OpenSplice DDS systems. We will look into Quality of Services, data selectors concurrency and scalability concerns.
We will present the brand-new, and recently finalized, C++ and Java APIs for DDS, including examples of how this can be used with C++11 features. We will show how, increasingly popular, functional languages such as Scala can be used to efficiently and elegantly exploit the massive HW parallelism provided by modern multi-core processors.
Finally we will present some OpenSplice specific extensions for dealing very high-volumes of data – meaning several millions of messages per seconds.
The Data Distribution Service for Real-Time Systems (DDS) is an Object Management Group (OMG) standard for publish/subscribe designed to address the needs of a large class of mission- and business-critical distributed real-time systems and system of systems. The DDS standard was formally adopted in 2004 and in less than five years from its inception has experienced swift adoption in a wide variety of application domains. These application domains are characterized by the need to distribute high volumes of data with predictable low latencies, such as, Radar Processors, Flying and Land Drones, Combat Management Systems, Air Traffic Management, High Performance Telemetry, Large Scale Supervisory Systems, and Automated Stocks and Options Trading. Along with wide commercial adoption, the DDS Standard has been recommended and mandated as the technology for real-time data distribution by key administrations worldwide such as the US Navy, the DoD Information-Technology Standards Registry (DISR), the UK MoD, and EUROCONTROL.
This two-part Tutorial will cover most of the key aspects of DDS to ensure that you can proficiently start using it for designing or developing your next system. In brief this tutorial will get you jump-started into DDS.
DDS is a very powerful technology built around a few simple and orthogonal concepts. If you understand the core concepts then you can really quickly get up to speed and start exploiting all of its power. On the other hand, if you haven’t grasped the key abstractions you might not be able to exploit all the benefits that DDS can bring.
This presentation provides you with an introduction to the core DDS concepts and illustrates how to program DDS applications. The new C++ and Java API will be explained and used throughout the webcast for coding examples thus giving you a chance to learn the new API from one of the main authors!
The document discusses OpenSplice DDS, an implementation of the OMG DDS standard for data distribution. It provides an overview of key DDS concepts like the global data space, publishers/subscribers, topics/instances/samples, partitioning, filtering, and quality of service (QoS). DDS aims to address data distribution challenges across a wide range of applications through high performance, scalability, and interoperability between implementations.
The DDS specification provides fine-grained control over the real-time behaviour, dependability, and performance of DDS applications by means of a rich set of QoS Policies. The challenge for many DDS users is that the specifications explains very clearly how each QoS allows to control very specific aspects of data distribution yet it provides no hints on how different QoS should be composed to control complex properties such as the consistency model, or to impose end-to-end real-time scheduling decision. This half-day tutorial will fill this gap by providing attendees with (1) an explanation of how the various QoS compose, and (2) providing attendees with a series of QoS-composition Patters that can be used to control macro-properties of an application, such as the consistency model.
This 4-page document provides a product description for Shared Oracle Hosting (Linux) offered by the Utah Department of Technology Services (DTS). It includes details on features, rates and billing, ordering process, responsibilities of DTS and agencies, and service level metrics. DTS provides shared Oracle database environments on Linux in the state data center, including management, backups, monitoring, and support. Pricing is based on database size with a minimum of $200 per month for the first 2GB and $140 for each additional 2GB.
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, such as, Power Generation, Large Scale SCADA, Air Traffic Control and Management, Smart Cities, Smart Grids, Vehicles, Medical Devices, Simulation, Aerospace, Defense and Financial Trading.
This two part webcast provides an in depth introduction to DDS – the universal data sharing technology. Specifically, we will introduce (1) the DDS conceptual model and data-centric design, (2) DDS data modeling fundamentals, (3) the complete set of C++ and Java API, (4) the most important programming, data modeling and QoS Idioms, and (5) the integration between DDS and web applications.
After attending this webcast you will understand how to exploit DDS architectural features when designing your next system, how to write idiomatic DDS applications in C++ and Java and what are the fundamental patterns that you should adopt in your applications.
Desktop, Embedded and Mobile Apps with Vortex CaféAngelo Corsaro
In the past few years we have been experiencing an amazing proliferation of mobile and embedded platforms. Contemporary developers are increasingly faced with the challenge of writing applications that can run on desktop, mobile (e.g. Android), and on low-cost embedded platforms (e.g. Raspberry-Pi and Beaglebone). This is causing a rejuvenated interest in the Java platform as the mean to achieve the holy grail of write-once and run-everywhere. With the availability of Java environments supporting almost any kind of device in several different form factors, the missing element to the picture is an effective way of enabling communication between them.
Vortex Café is a pure Java implementation of the OMG Data Distribution Service (DDS) that enables seamless, efficient and timely data sharing across many-core machines, mobile and embedded devices.
This presentation will (1) introduce the main abstractions provided by Vortex Café, (2) provide an overview of its architecture and explain how it exploits Staged Event Driven Architectures to optimize its runtime depending of the target hardware, (3) provide an overview of the typical performance delivered by Vortex Café, and (3) get you started developing distributed Java and Scala applications with Vortex Café.
The Data Distribution Service for Real-Time Systems (DDS) is an Object Management Group (OMG) standard for publish/subscribe designed to address the needs of a large class of mission- and business-critical distributed real-time systems and system of systems. The DDS standard was formally adopted in 2004 and in less than five years from its inception has experienced swift adoption in a wide variety of application domains. These application domains are characterized by the need to distribute high volumes of data with predictable low latencies, such as, Radar Processors, Flying and Land Drones, Combat Management Systems, Air Traffic Management, High Performance Telemetry, Large Scale Supervisory Systems, and Automated Stocks and Options Trading. Along with wide commercial adoption, the DDS Standard has been recommended and mandated as the technology for real-time data distribution by key administrations worldwide such as the US Navy, the DoD Information-Technology Standards Registry (DISR), the UK MoD, and EUROCONTROL.
The document summarizes the evolution of the Data Distribution Service (DDS) standard from 2004 to 2011, highlighting major releases that expanded its capabilities. Key points include:
- The 2004 standard introduced the DDS API and interoperable wire protocol.
- Later versions added features like dynamic discovery, filtering, and a high performance wire protocol.
- Programming language bindings were added for C++ and Java.
- Extensions improved type flexibility and modeling.
- 2011 saw the introduction of Web-DDS for accessing DDS through web technologies.
Connected Mobile and Web Applications with VortexAngelo Corsaro
The widespread availability of high-end mobile devices such as smart-phones, tablets and phablets, along with the availability of browser enabled devices, has imposed these platforms as one of the main target for user interfaces. As a result mobile and web applications need now to be easily “connected”to the rest of the system.
This presentations will (1) showcase how the the Vortex Data Sharing Platform can be effectively and productively used to create connected mobile and web-applications, (2) take you through the steps required to use Vortex in mobile and web applications.
This document provides an overview of the Data Distribution Service (DDS) standard for publish-subscribe communication. It explains key DDS concepts like the global data space, domain participants, topics, and quality of service policies. DDS provides a fully distributed, interoperable architecture for real-time data sharing between publishers and subscribers in applications like building automation, manufacturing, and more. The tutorial uses an example of monitoring and controlling temperatures in a large building to illustrate how DDS works.
View On Demand: http://ecast.opensystemsmedia.com/375
Top Three Reasons to Develop Your Next Distributed Application with DDS
Developing applications that can run over multiple cores, nodes or networks typically requires a significant amount of network-level programming. This low-level coding detracts from the implementation of application logic, introduces complexity, and is hard to maintain as requirements evolve and systems grow in scale. The challenges are particularly acute for real-time and embedded systems, which often have to address stringent timing, resource and reliability constraints.
Just as high-level programming languages and operating systems simplified application development by eliminating hardware dependencies, the Data Distribution Service (DDS) standard does the same for networking. DDS provides application developers with simple publish-subscribe programming interfaces that abstract out all the networking details. Application components simply publish the data they produce and subscribe to the data they consume. The DDS middleware handles all the networking and real-time Quality of Service details. Components can seamlessly communicate across different programming languages and processor families. Applications are also independent of the underlying transport protocol and network type, be it shared memory, a local area network, wide area network or even radio link.
OpenSplice DDS enables seamless, timely, scalable and dependable data sharing between distributed applications and network-connected devices. Its technical and operational benefits have propelled adoption across multiple industries, such as Defence and Aerospace, SCADA, Gaming, Cloud Computing, Automotive, etc.
If you want to learn about OpenSplice DDS or discover some of its advanced features, this webcast is for you!
In this two-parts webcast we will cover all the aspects tied to architecting and developing OpenSplice DDS systems. We will look into Quality of Services, data selectors concurrency and scalability concerns.
We will present the brand-new, and recently finalized, C++ and Java APIs for DDS, including examples of how this can be used with C++11 features. We will show how, increasingly popular, functional languages such as Scala can be used to efficiently and elegantly exploit the massive HW parallelism provided by modern multi-core processors.
Finally we will present some OpenSplice specific extensions for dealing very high-volumes of data – meaning several millions of messages per seconds.
This document discusses patterns of data distribution that are commonly used when building distributed systems and applications. It identifies three main patterns: publish-subscribe, point-to-point, and request-reply. The document argues that middleware platforms typically implement these patterns in a rigid way, whereas a better approach is for platforms to be built using fundamental "super-patterns" that can be constrained or composed to derive the common patterns. This allows platforms to be more flexible and performant while still providing familiar patterns to application developers. The document also discusses challenges for platform builders in areas like system architecture, performance, and application interfaces.
Getting Started with DDS in C++, Java and ScalaAngelo Corsaro
This document provides an overview and outline for a tutorial on getting started with the Data Distribution Service (DDS) in C++, Java, and Scala. The tutorial will cover DDS basics, data reader/writer caches, quality of service, data and state selectors, and advanced DDS topics. Upon completion, students will have a firm understanding of DDS concepts and the ability to design and write DDS applications. The tutorial will be highly interactive with examples and live demonstrations.
Microsoft® SQL Azure™ Database is a cloud-based relational database service built for Windows® Azure platform. It provides a highly available, scalable, multi-tenant database service hosted by Microsoft in the cloud. SQL Azure Database enables easy provisioning and deployment of multiple databases. Developers do not have to install, setup, patch or manage any software. High Availability and fault tolerance is built-in and no physical administration is required. SQL Azure supports Transact-SQL (T-SQL). Customers can leverage existing tools and knowledge in T-SQL based familiar relational
data model for building applications.
CodeFutures - Scaling Your Database in the CloudRightScale
RightScale Conference Santa Clara 2011: Scaling an application in the cloud often hits the most common bottleneck – the database tier. Not only is database performance the number one cause of poor application performance, but also the issue is magnified in cloud environments where I/O and bandwidth is generally slower and less predictable than in dedicated data centers. Database sharding is a highly effective method of removing the database scalability barrier, operating on top of proven RDBMS products such as MySQL and Postgres – as well as the new NoSQL database platforms. One critical aspect often given too little consideration is monitoring and continuous operation of your databases, including the full lifecycle, to ensure that they stay up.
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.
Introduced in 2004, the Data Distribution Service (DDS) has been steadily growing in popularity and adoption. Today, DDS is at the heart of a large number of mission and business critical systems, such as, Air Traffic Control and Management, Train Control Systems, Energy Production Systems, Medical Devices, Autonomous Vehicles, Smart Cities and NASA’s Kennedy Space Centre Launch System.
Considered the technological trends toward data-centricity and the rate of adoption, tomorrow, DDS will be at the at the heart of an incredible number of Industrial IoT systems.
To help you become an expert in DDS and exploit your skills in the growing DDS market, we have designed the DDS in Action webcast series. This series is a learning journey through which you will (1) discover the essence of DDS, (2) understand how to effectively exploit DDS to architect and program distributed applications that perform and scale, (3) learn the key DDS programming idioms and architectural patterns, (4) understand how to characterise DDS performances and configure for optimal latency/throughput, (5) grow your system to Internet scale, and (6) secure you DDS system.
NT Domain Restructuring and Exchange Resource Forestswebhostingguy
The document outlines the 10 step process to restructure an NT domain and migrate it to an Active Directory forest including Exchange, including planning, creating the AD forest structure, establishing trusts, preparing objects for migration, migrating users, workstations, servers and Exchange, and relaxing after completion. It discusses considerations at each step like creating OUs and GPOs, enabling sIDHistory, renaming conflicting objects, moving FSMO roles and rewriting ACLs.
Converged architecture advantages: Dell PowerEdge FX2s and FC830 servers vs. ...Principled Technologies
Based on our testing with heavy SQL Server 2014 database workloads, the converged architecture solution of a Dell PowerEdge FX2s chassis and FC830 servers delivered 3.8 times the performance of our legacy HP solution. We also found the Dell PowerEdge FX2s and FC830 solution offered 72 lower cost per new order compared to the legacy HP ProLiant DL580 G7 solution. In addition, the PowerEdge FX2s and FC830 solution does not sacrifice traditional hardware redundancy while providing the same highly available database solution in a smaller rack space. If your business runs Microsoft SQL Server 2014, the converged architecture approach with Dell PowerEdge FX2s chassis and FC830 servers powered by Intel could bring a harmonious balance of performance, reliability, and cost efficiency to your data center.
This document provides an overview of the ServiceDDS framework, which aims to integrate soft real-time systems into dynamic peer-to-peer architectures. ServiceDDS is based on standards like DDS, RTSJ, and XMPP. It uses a publish-subscribe model and allows services to be described and discovered. Topic Transformation Functions enable complex event processing. The framework also provides web access to the DDS data space through an XMPP server plugin and supports real-time requirements through latency calculation and memory management.
Building Real-Time Web Applications with Vortex-WebAngelo Corsaro
The Real-Time Web is rapidly growing and as a consequence an increasing number of applications require soft-real time interactions with the server-side as well as with peer web applications. In addition, real-time web technologies are experiencing swift adoption in traditional systems as a means of providing portable and ubiquitously accessible thin client applications.
In spite of this trend, few high level communication frameworks exist that allow efficient and timely data exchange between web applications as well as with the server-side and the back-end system. Vortex Web is one of the first technologies to bring the powerful OMG Data Distribution Service (DDS) abstractions to the world of HTML5 / JavaScript applications. With Vortex Web, HTML5 / JavaScript applications can seamlessly and efficiently share data in a timely manner amongst themselves as well as with any other kind of device or system that supports the standard DDS Interoperability wire protocol (DDSI).
This presentation will (1) introduce the key abstractions provided by Vortex Web, (2) provide an overview of its architecture and explain how Vortex Web uses Web Sockets and Web Workers to provide low latency and high throughput, and (3) get you started developing real-time web applications.
A server is a computer that manages network resources and makes them available to authorized users. Kerberos is an authentication protocol that provides encryption during authentication. Active Directory installation can be verified by checking SRV records in DNS, verifying the SYSVOL folder, and database and log files, and using commands like Dcdiag and Net share.
Consumer and Industrial IoT systems have to deal with massive volumes of data, collected as well as shared, with very heterogeneous targets, such as embedded systems, mobile, web and cloud applications. Additionally, different communication patterns, such as device-to-device as and device-to-cloud have to be supported to enable the right combination of fog, edge and cloud computing. Furthermore, increasingly more often, the system value depends on its ability to transform, in real-time, these massive amount of data in “actionable”.
This presentation identifies the key requirement of Consumer and Industrial IoT Systems and show how the Vortex platform addresses them.
The Data Distribution Service (DDS) technology may not be as well known or understood as other middleware communications technologies like Corba, JMS, Web Services or even traditional sockets that are key components of nearly all distributed applications. Developers everywhere are familiar with these conventional data communications solutions, and may be comfortable customizing them to their particular domain and application. However, the flexibility and configurability of DDS makes it a better solution for applications in a wide variety of industries, from enterprise servers to deeply embedded applications.
This paper focuses on the DDS technology in embedded environments and compares it with Sockets, Corba, JMS, and SOA Web Services.
DDS, JMS, REST APIs
Data-Centric Publish/Subscribe
Pluggable Discovery
Reliability, Serialization, Transport
Persistence Service
Monitoring, Logging, Replay
Connext Messaging adds:
- Request/reply
- Guaranteed messaging
- JMS API
- Persistence
- Additional transports
- Security
- Future: REST API
It is built on top of Connext DDS for data distribution.
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Desktop, Embedded and Mobile Apps with Vortex CaféAngelo Corsaro
In the past few years we have been experiencing an amazing proliferation of mobile and embedded platforms. Contemporary developers are increasingly faced with the challenge of writing applications that can run on desktop, mobile (e.g. Android), and on low-cost embedded platforms (e.g. Raspberry-Pi and Beaglebone). This is causing a rejuvenated interest in the Java platform as the mean to achieve the holy grail of write-once and run-everywhere. With the availability of Java environments supporting almost any kind of device in several different form factors, the missing element to the picture is an effective way of enabling communication between them.
Vortex Café is a pure Java implementation of the OMG Data Distribution Service (DDS) that enables seamless, efficient and timely data sharing across many-core machines, mobile and embedded devices.
This presentation will (1) introduce the main abstractions provided by Vortex Café, (2) provide an overview of its architecture and explain how it exploits Staged Event Driven Architectures to optimize its runtime depending of the target hardware, (3) provide an overview of the typical performance delivered by Vortex Café, and (3) get you started developing distributed Java and Scala applications with Vortex Café.
The Data Distribution Service for Real-Time Systems (DDS) is an Object Management Group (OMG) standard for publish/subscribe designed to address the needs of a large class of mission- and business-critical distributed real-time systems and system of systems. The DDS standard was formally adopted in 2004 and in less than five years from its inception has experienced swift adoption in a wide variety of application domains. These application domains are characterized by the need to distribute high volumes of data with predictable low latencies, such as, Radar Processors, Flying and Land Drones, Combat Management Systems, Air Traffic Management, High Performance Telemetry, Large Scale Supervisory Systems, and Automated Stocks and Options Trading. Along with wide commercial adoption, the DDS Standard has been recommended and mandated as the technology for real-time data distribution by key administrations worldwide such as the US Navy, the DoD Information-Technology Standards Registry (DISR), the UK MoD, and EUROCONTROL.
The document summarizes the evolution of the Data Distribution Service (DDS) standard from 2004 to 2011, highlighting major releases that expanded its capabilities. Key points include:
- The 2004 standard introduced the DDS API and interoperable wire protocol.
- Later versions added features like dynamic discovery, filtering, and a high performance wire protocol.
- Programming language bindings were added for C++ and Java.
- Extensions improved type flexibility and modeling.
- 2011 saw the introduction of Web-DDS for accessing DDS through web technologies.
Connected Mobile and Web Applications with VortexAngelo Corsaro
The widespread availability of high-end mobile devices such as smart-phones, tablets and phablets, along with the availability of browser enabled devices, has imposed these platforms as one of the main target for user interfaces. As a result mobile and web applications need now to be easily “connected”to the rest of the system.
This presentations will (1) showcase how the the Vortex Data Sharing Platform can be effectively and productively used to create connected mobile and web-applications, (2) take you through the steps required to use Vortex in mobile and web applications.
This document provides an overview of the Data Distribution Service (DDS) standard for publish-subscribe communication. It explains key DDS concepts like the global data space, domain participants, topics, and quality of service policies. DDS provides a fully distributed, interoperable architecture for real-time data sharing between publishers and subscribers in applications like building automation, manufacturing, and more. The tutorial uses an example of monitoring and controlling temperatures in a large building to illustrate how DDS works.
View On Demand: http://ecast.opensystemsmedia.com/375
Top Three Reasons to Develop Your Next Distributed Application with DDS
Developing applications that can run over multiple cores, nodes or networks typically requires a significant amount of network-level programming. This low-level coding detracts from the implementation of application logic, introduces complexity, and is hard to maintain as requirements evolve and systems grow in scale. The challenges are particularly acute for real-time and embedded systems, which often have to address stringent timing, resource and reliability constraints.
Just as high-level programming languages and operating systems simplified application development by eliminating hardware dependencies, the Data Distribution Service (DDS) standard does the same for networking. DDS provides application developers with simple publish-subscribe programming interfaces that abstract out all the networking details. Application components simply publish the data they produce and subscribe to the data they consume. The DDS middleware handles all the networking and real-time Quality of Service details. Components can seamlessly communicate across different programming languages and processor families. Applications are also independent of the underlying transport protocol and network type, be it shared memory, a local area network, wide area network or even radio link.
OpenSplice DDS enables seamless, timely, scalable and dependable data sharing between distributed applications and network-connected devices. Its technical and operational benefits have propelled adoption across multiple industries, such as Defence and Aerospace, SCADA, Gaming, Cloud Computing, Automotive, etc.
If you want to learn about OpenSplice DDS or discover some of its advanced features, this webcast is for you!
In this two-parts webcast we will cover all the aspects tied to architecting and developing OpenSplice DDS systems. We will look into Quality of Services, data selectors concurrency and scalability concerns.
We will present the brand-new, and recently finalized, C++ and Java APIs for DDS, including examples of how this can be used with C++11 features. We will show how, increasingly popular, functional languages such as Scala can be used to efficiently and elegantly exploit the massive HW parallelism provided by modern multi-core processors.
Finally we will present some OpenSplice specific extensions for dealing very high-volumes of data – meaning several millions of messages per seconds.
This document discusses patterns of data distribution that are commonly used when building distributed systems and applications. It identifies three main patterns: publish-subscribe, point-to-point, and request-reply. The document argues that middleware platforms typically implement these patterns in a rigid way, whereas a better approach is for platforms to be built using fundamental "super-patterns" that can be constrained or composed to derive the common patterns. This allows platforms to be more flexible and performant while still providing familiar patterns to application developers. The document also discusses challenges for platform builders in areas like system architecture, performance, and application interfaces.
Getting Started with DDS in C++, Java and ScalaAngelo Corsaro
This document provides an overview and outline for a tutorial on getting started with the Data Distribution Service (DDS) in C++, Java, and Scala. The tutorial will cover DDS basics, data reader/writer caches, quality of service, data and state selectors, and advanced DDS topics. Upon completion, students will have a firm understanding of DDS concepts and the ability to design and write DDS applications. The tutorial will be highly interactive with examples and live demonstrations.
Microsoft® SQL Azure™ Database is a cloud-based relational database service built for Windows® Azure platform. It provides a highly available, scalable, multi-tenant database service hosted by Microsoft in the cloud. SQL Azure Database enables easy provisioning and deployment of multiple databases. Developers do not have to install, setup, patch or manage any software. High Availability and fault tolerance is built-in and no physical administration is required. SQL Azure supports Transact-SQL (T-SQL). Customers can leverage existing tools and knowledge in T-SQL based familiar relational
data model for building applications.
CodeFutures - Scaling Your Database in the CloudRightScale
RightScale Conference Santa Clara 2011: Scaling an application in the cloud often hits the most common bottleneck – the database tier. Not only is database performance the number one cause of poor application performance, but also the issue is magnified in cloud environments where I/O and bandwidth is generally slower and less predictable than in dedicated data centers. Database sharding is a highly effective method of removing the database scalability barrier, operating on top of proven RDBMS products such as MySQL and Postgres – as well as the new NoSQL database platforms. One critical aspect often given too little consideration is monitoring and continuous operation of your databases, including the full lifecycle, to ensure that they stay up.
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.
Introduced in 2004, the Data Distribution Service (DDS) has been steadily growing in popularity and adoption. Today, DDS is at the heart of a large number of mission and business critical systems, such as, Air Traffic Control and Management, Train Control Systems, Energy Production Systems, Medical Devices, Autonomous Vehicles, Smart Cities and NASA’s Kennedy Space Centre Launch System.
Considered the technological trends toward data-centricity and the rate of adoption, tomorrow, DDS will be at the at the heart of an incredible number of Industrial IoT systems.
To help you become an expert in DDS and exploit your skills in the growing DDS market, we have designed the DDS in Action webcast series. This series is a learning journey through which you will (1) discover the essence of DDS, (2) understand how to effectively exploit DDS to architect and program distributed applications that perform and scale, (3) learn the key DDS programming idioms and architectural patterns, (4) understand how to characterise DDS performances and configure for optimal latency/throughput, (5) grow your system to Internet scale, and (6) secure you DDS system.
NT Domain Restructuring and Exchange Resource Forestswebhostingguy
The document outlines the 10 step process to restructure an NT domain and migrate it to an Active Directory forest including Exchange, including planning, creating the AD forest structure, establishing trusts, preparing objects for migration, migrating users, workstations, servers and Exchange, and relaxing after completion. It discusses considerations at each step like creating OUs and GPOs, enabling sIDHistory, renaming conflicting objects, moving FSMO roles and rewriting ACLs.
Converged architecture advantages: Dell PowerEdge FX2s and FC830 servers vs. ...Principled Technologies
Based on our testing with heavy SQL Server 2014 database workloads, the converged architecture solution of a Dell PowerEdge FX2s chassis and FC830 servers delivered 3.8 times the performance of our legacy HP solution. We also found the Dell PowerEdge FX2s and FC830 solution offered 72 lower cost per new order compared to the legacy HP ProLiant DL580 G7 solution. In addition, the PowerEdge FX2s and FC830 solution does not sacrifice traditional hardware redundancy while providing the same highly available database solution in a smaller rack space. If your business runs Microsoft SQL Server 2014, the converged architecture approach with Dell PowerEdge FX2s chassis and FC830 servers powered by Intel could bring a harmonious balance of performance, reliability, and cost efficiency to your data center.
This document provides an overview of the ServiceDDS framework, which aims to integrate soft real-time systems into dynamic peer-to-peer architectures. ServiceDDS is based on standards like DDS, RTSJ, and XMPP. It uses a publish-subscribe model and allows services to be described and discovered. Topic Transformation Functions enable complex event processing. The framework also provides web access to the DDS data space through an XMPP server plugin and supports real-time requirements through latency calculation and memory management.
Building Real-Time Web Applications with Vortex-WebAngelo Corsaro
The Real-Time Web is rapidly growing and as a consequence an increasing number of applications require soft-real time interactions with the server-side as well as with peer web applications. In addition, real-time web technologies are experiencing swift adoption in traditional systems as a means of providing portable and ubiquitously accessible thin client applications.
In spite of this trend, few high level communication frameworks exist that allow efficient and timely data exchange between web applications as well as with the server-side and the back-end system. Vortex Web is one of the first technologies to bring the powerful OMG Data Distribution Service (DDS) abstractions to the world of HTML5 / JavaScript applications. With Vortex Web, HTML5 / JavaScript applications can seamlessly and efficiently share data in a timely manner amongst themselves as well as with any other kind of device or system that supports the standard DDS Interoperability wire protocol (DDSI).
This presentation will (1) introduce the key abstractions provided by Vortex Web, (2) provide an overview of its architecture and explain how Vortex Web uses Web Sockets and Web Workers to provide low latency and high throughput, and (3) get you started developing real-time web applications.
A server is a computer that manages network resources and makes them available to authorized users. Kerberos is an authentication protocol that provides encryption during authentication. Active Directory installation can be verified by checking SRV records in DNS, verifying the SYSVOL folder, and database and log files, and using commands like Dcdiag and Net share.
Consumer and Industrial IoT systems have to deal with massive volumes of data, collected as well as shared, with very heterogeneous targets, such as embedded systems, mobile, web and cloud applications. Additionally, different communication patterns, such as device-to-device as and device-to-cloud have to be supported to enable the right combination of fog, edge and cloud computing. Furthermore, increasingly more often, the system value depends on its ability to transform, in real-time, these massive amount of data in “actionable”.
This presentation identifies the key requirement of Consumer and Industrial IoT Systems and show how the Vortex platform addresses them.
The Data Distribution Service (DDS) technology may not be as well known or understood as other middleware communications technologies like Corba, JMS, Web Services or even traditional sockets that are key components of nearly all distributed applications. Developers everywhere are familiar with these conventional data communications solutions, and may be comfortable customizing them to their particular domain and application. However, the flexibility and configurability of DDS makes it a better solution for applications in a wide variety of industries, from enterprise servers to deeply embedded applications.
This paper focuses on the DDS technology in embedded environments and compares it with Sockets, Corba, JMS, and SOA Web Services.
DDS, JMS, REST APIs
Data-Centric Publish/Subscribe
Pluggable Discovery
Reliability, Serialization, Transport
Persistence Service
Monitoring, Logging, Replay
Connext Messaging adds:
- Request/reply
- Guaranteed messaging
- JMS API
- Persistence
- Additional transports
- Security
- Future: REST API
It is built on top of Connext DDS for data distribution.
<XML>
As a leading innovator, you selected DDS to solve a complex communications challenge. Good choice! Now you recognize that your challenge is evolving: you need to consider adding more mobile and embedded devices into the network. The resource requirements of your DDS middleware are becoming a crucial factor. Even if you wanted your vendor to port to the rapidly expanding field of hand-held and mobile embedded devices, you wonder - will your applications still fit and run with needed performance levels within the memory footprint and CPU cycle constraints?
Your management or your client is now requesting you handle some new and interesting hardware and software, mobility solutions while bringing in data from new sources. To do this you might be able to select higher memory versions and/or faster CPU versions of the new devices in order to achieve the performance you need. Or you might be forced to drop features and functionality so that your DDS enabled application fits and provides acceptable performance. Either your costs go up or you leave out features. Do you really want to make that trade off? What options exist now?
Fortunately, one of the great strengths of the DDS standard is that it is open and provides interoperability between DDS versions from other suppliers. That’s one of the reasons your choice of DDS was a good one!
Twin Oaks Computing (www.twinoakscomputing.com) has designed its implementation from the ground up especially for resource constrained environments. CoreDX DDS is a high-performance implementation of the OMG Data Distribution Service (DDS) standard. The CoreDX DDS Publish-Subscribe messaging infrastructure provides high-throughput, low-latency data communications in an extremely small footprint.
CoreDX DDS applications can easily communicate with applications based on DDS from other vendors. This multi-vendor interoperability is enabled by multiple standards managed by the Object Management Group (OMG), including specifications of the application programming interface (API), real-time publish subscribe wire protocol (RTPS), and quality of service (QoS) features. CoreDX DDS includes proven support across all of these interoperability aspects. Twin Oaks has publicly demonstrated CoreDX DDS interoperability with RTI DDS and OpenSplice DDS.
Interoperability is particularly important for systems that are deployed for long periods of time, often measured in the decades, before they can be upgraded or replaced. Maintaining these systems through individual component failures, and ever changing and expanding requirements is hard. Interoperable middleware technologies like DDS make this challenge easier. System
Figure 1: Examples of Supported Hardware
4
Interoperable DDS Strategies 4
Integrators, faced with the challenge of integrating components from diverse sources, demand interoperability.
DODS (Distributed Oceanographic Data System) is a software package that helps users provide and access data over the internet in a consistent way. It allows data analysis tools to access datasets from any location as if the data were local. DODS uses client and server architecture, with clients making requests via URLs that are processed by DODS servers to deliver subsetted data in the expected format. This transforms tools into "network-savvy" clients that can access remote data from any DODS server regardless of the native data format.
DDS is an IoT protocol developed by OMG for M2M communication that enables data exchange via a publish-subscribe methodology without a broker. It uses multicasting to provide high quality QoS and can be deployed from low footprint devices to the cloud. The DDS protocol stack has two layers: the DCPS layer delivers information to subscribers through a topic-based publish/subscribe API, and the DLRL layer provides an interface to create object views from topics. DDSI/RTPS is the standard wire protocol that allows interoperability between DDS implementations.
The document discusses the advantages of using CoreDX DDS middleware. It states that CoreDX DDS has a small footprint, small source code size, and low memory usage. It also offers high performance, scalability, reliable communication, interoperability, no single point of failure, support for multi-core systems, dynamic types, and multiple programming languages and platforms. CoreDX DDS is developed by Twin Oaks Computing to provide robust data distribution for critical applications.
Twin Oaks Computing provides middleware and services to help software engineers build distributed systems. Their flagship product, CoreDX DDS, is a communications middleware that enables platforms and applications to interoperate in a flexible, robust manner. Twin Oaks aims to reduce costs and risks for clients through products, support, and engineering expertise.
Fiware - communicating with ROS robots using Fast RTPSJaime Martin Losa
How to connect FIWARE to Robots ? We discuss how the FIWARE enablers can connect to ROS2, a de facto standard for robotic frameworks, using Fast RTPS and KIARA.
Interoperability demonstration between 7 different products that implement the OMG DDS Interoperability Wire Protocol (DDS-RTPS).
The demonstration took place at the June 2013 OMG technical meeting in Berlin Germany.
The following companies demonstrated interoperability between their products: RTI (Connext DDS). TwinOaks Computing (CoreDX), PrismTech (OpenSpliceDDS), OCI (OpenDDS), ETRI (ETRI DDS), NADS, and RemedyRT.
Как повысить доступность ЦОД? Введение в балансировщики трафика. Часть 2SkillFactory
Василий Солдатов, системный инженер Brocade, компании-лидера рынка высокотехнологичных балансировщиков трафика – о том, как повысить качество услуг дата-центра и обеспечить безотказный и высокоскоростной доступ к данным клиента.
Ozone is an object store for Hadoop. Ozone solves the small file problem of HDFS, which allows users to store trillions of files in Ozone and access them as if there are on HDFS. Ozone plugs into existing Hadoop deployments seamlessly, and programs like Hive, LLAP, and Spark work without any modifications. This talk looks at the architecture, reliability, and performance of Ozone.
In this talk, we will also explore Hadoop distributed storage layer, a block storage layer that makes this scaling possible, and how we plan to use the Hadoop distributed storage layer for scaling HDFS.
We will demonstrate how to install an Ozone cluster, how to create volumes, buckets, and keys, how to run Hive and Spark against HDFS and Ozone file systems using federation, so that users don’t have to worry about where the data is stored. In other words, a full user primer on Ozone will be part of this talk.
Speakers
Anu Engineer, Software Engineer, Hortonworks
Xiaoyu Yao, Software Engineer, Hortonworks
This document discusses Data Distribution Service (DDS) as an industrial Internet of Things connectivity framework. It compares message-centric and data-centric architectures, noting that DDS takes a data-centric approach. The document then provides an overview of DDS, describing its core functions like discovery, evolution, load balancing and quality of service policies. It demonstrates DDS through examples of backward compatibility, redundancy, and integration with other tools. DDS creates a shared data bus that allows systems to evolve over time while maintaining consistency.
In a distributed system, components running on different Operating Systems and applications written in different programming languages all work together as one single reliable system. As the complexity of these systems increase, it becomes more important to gain visibility into your environment and expose potential problems before they jeopardize your production system.
RTI Connext Tools offer a rich tools suite that helps you develop applications more efficiently. They enable you to monitor, analyze and debug your complete system in operation. And they provide facilities for recording and replaying data in real-time, and logging diagnostic system data for deeper analysis and archiving. This webinar explores the many tools available for development, debugging, and testing applications in your distributed system.
How to connect FIWARE to Robots ? We discuss how the FIWARE enablers can connect to ROS2, a de facto standard for robotic frameworks, using Fast RTPS and KIARA.
MBSE meets Industrial IoT: Introducing the New MagicDraw Plug-in for RTI Co...Istvan Rath
Slides of the talk at the MBSE Cyber Experience Symposium 2019 (https://mbsecyberexperience2019.com/speakers/abstracts/item/mbse-meets-industrial-iot-introducing-the-new-magicdraw-connext-dds-plug-in)
Streaming Data Into Your Lakehouse With Frank Munz | Current 2022HostedbyConfluent
Streaming Data Into Your Lakehouse With Frank Munz | Current 2022
The last years have taught us that cheap, virtually unlimited, and highly available cloud object storage doesn't make a solid enterprise data platform. Too many data lakes didn't fulfill their expectations and degenerated into sad data swamps.
With the Linux Foundation OSS project Delta Lake (https://github.com/delta-io), you can turn your data lake into the foundation of a data lakehouse that brings back ACID transactions, schema enforcement, upserts, efficient metadata handling, and time travel.
In this session, we explore how a data lakehouse works with streaming, using Apache Kafka as an example.
This talk is for data architects who are not afraid of some code and for data engineers who love open source and cloud services.
Attendees of this talk will learn:
1. Lakehouse architecture 101, the honest tech bits
2. The data lakehouse and streaming data: what's there beyond Apache Spark™ Structured Streaming?
3. Why the lakehouse and Apache Kafka make a great couple and what concepts you should know to get them hitched with success.
4. Streaming data with declarative data pipelines: In a live demo, I will show data ingestion, cleansing, and transformation based on a simulation of the Data Donation Project (DDP, https://corona-datenspende.de/science/en) built on the lakehouse with Apache Kafka, Apache Spark™, and Delta Live Tables (a fully managed service).
DDP is a scientific IoT experiment to determine COVID outbreaks in Germany by detecting elevated heart rates correlated to infections. Half a million volunteers have already decided to donate their heart rate data from their fitness trackers.
Presentation on the OMG Data-Distribution Service (DDS) Interoperability demo held during the Santa Clara OMG meeting on December 8, 2010.
Four vendors demonstrated the wire-protocol interoperability of their DDS Implementations: RTI, PrismTech, Gallium Visual Systems, and Twin Oaks Computing.
This is a demonstration of the use of the DDS Interoperability Wire Protocol standard (DDS-RTPS)
Chapter08 -- network operating systems and windows server 2003-based networkingRaja Waseem Akhtar
This chapter discusses network operating systems and Windows Server 2003. It covers the functions of a network OS like managing resources and users. Windows Server 2003 editions are examined along with installation requirements. Features like Active Directory, file systems, and integration with other OSs are described. The chapter concludes with instructions for a basic Windows Server 2003 installation and configuration of users and groups.
Even though the U.S. Department of Defense budget is shrinking and the country's military footprint worldwide is receding the need for the warfighter to have accurate and actionable intelligence has never been more critical. Data from Intelligence, Surveillance, and Reconnaissance (C4ISR) systems such as radar, image processing payloads on Unmanned Aerial Vehicles, and more will be used and fused together to provide commanders with real-time situational awareness. Each system will also need to embrace open architectures and the latest commercial standards to meet the DoD's performance, size, and cost requirements. This e-cast will discuss how embedded defense suppliers are meeting these challenges.
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
A Comprehensive Guide to DeFi Development Services in 2024Intelisync
DeFi represents a paradigm shift in the financial industry. Instead of relying on traditional, centralized institutions like banks, DeFi leverages blockchain technology to create a decentralized network of financial services. This means that financial transactions can occur directly between parties, without intermediaries, using smart contracts on platforms like Ethereum.
In 2024, we are witnessing an explosion of new DeFi projects and protocols, each pushing the boundaries of what’s possible in finance.
In summary, DeFi in 2024 is not just a trend; it’s a revolution that democratizes finance, enhances security and transparency, and fosters continuous innovation. As we proceed through this presentation, we'll explore the various components and services of DeFi in detail, shedding light on how they are transforming the financial landscape.
At Intelisync, we specialize in providing comprehensive DeFi development services tailored to meet the unique needs of our clients. From smart contract development to dApp creation and security audits, we ensure that your DeFi project is built with innovation, security, and scalability in mind. Trust Intelisync to guide you through the intricate landscape of decentralized finance and unlock the full potential of blockchain technology.
Ready to take your DeFi project to the next level? Partner with Intelisync for expert DeFi development services today!
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
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.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on integration of Salesforce with Bonterra Impact Management.
Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Dive into the realm of operating systems (OS) with Pravash Chandra Das, a seasoned Digital Forensic Analyst, as your guide. 🚀 This comprehensive presentation illuminates the core concepts, types, and evolution of OS, essential for understanding modern computing landscapes.
Beginning with the foundational definition, Das clarifies the pivotal role of OS as system software orchestrating hardware resources, software applications, and user interactions. Through succinct descriptions, he delineates the diverse types of OS, from single-user, single-task environments like early MS-DOS iterations, to multi-user, multi-tasking systems exemplified by modern Linux distributions.
Crucial components like the kernel and shell are dissected, highlighting their indispensable functions in resource management and user interface interaction. Das elucidates how the kernel acts as the central nervous system, orchestrating process scheduling, memory allocation, and device management. Meanwhile, the shell serves as the gateway for user commands, bridging the gap between human input and machine execution. 💻
The narrative then shifts to a captivating exploration of prominent desktop OSs, Windows, macOS, and Linux. Windows, with its globally ubiquitous presence and user-friendly interface, emerges as a cornerstone in personal computing history. macOS, lauded for its sleek design and seamless integration with Apple's ecosystem, stands as a beacon of stability and creativity. Linux, an open-source marvel, offers unparalleled flexibility and security, revolutionizing the computing landscape. 🖥️
Moving to the realm of mobile devices, Das unravels the dominance of Android and iOS. Android's open-source ethos fosters a vibrant ecosystem of customization and innovation, while iOS boasts a seamless user experience and robust security infrastructure. Meanwhile, discontinued platforms like Symbian and Palm OS evoke nostalgia for their pioneering roles in the smartphone revolution.
The journey concludes with a reflection on the ever-evolving landscape of OS, underscored by the emergence of real-time operating systems (RTOS) and the persistent quest for innovation and efficiency. As technology continues to shape our world, understanding the foundations and evolution of operating systems remains paramount. Join Pravash Chandra Das on this illuminating journey through the heart of computing. 🌟
Digital Marketing Trends in 2024 | Guide for Staying AheadWask
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
2. What is CoreDX DDS?
CoreDX DDS is a Communications
Middleware
Eases development and deployment of
Distributed Applications
Supports interoperable communications
High Throughput with Low Latency
Insulates Application from Communication
Details
3. CoreDX DDS Publish /
Subscribe Middleware
Message Oriented Middleware DDS extends MOM concepts
A Publisher Generates Data Adds Strong Data Typing
A Subscriber Accesses Data Adds Quality of Service Policies
The Middleware Manages the ▪ Reliability / History / Durability /
Connections and the Data Filtering
Publisher and Subscriber are Formalized Standard (API and
Wire Protocol)
Loosely Coupled
▪ Portable / Interoperable between
Vendors
Subscriber
Publisher
Data Subscriber
Publisher Topic
Subscriber
Data Type QoS
4. CoreDX DDS Architecture
DomainParticipant
Associated with a
Domain
Communicates with
other
DomainParticipants in
the same Domain
Contains
DataReaders,
DataWriters, and
Topics
A DataWriter publishes data on a Topic
A DataReader subscribes to a Topic
Each Topic has a Defined Data Type
5. Standards Based Data
Communication
Object Management Group manages DDS standards:
DDS API: Data Distribution Service
▪ Entities
▪ QoS Policies
▪ Asynchronous and Synchronous notifications
▪ Data Types
DDS Language Bindings:
DDS Wire Protocol: Real-Time Publish Subscribe (RTPS) Wire Protocol
▪ Discovery
▪ Reliability
▪ Data Encoding
DDS-Related Technologies
▪ Extensible Types
▪ Web Enabled DDS (in work)
▪ DDS Security (in work)
6. Technical Features
Dynamic Discovery Cross-platform
Reliability Interoperability
Durability Portability
Historical Data Caches High Performance
Filtering Highly Configurable
Ownership
7. CoreDX DDS Features:
Dynamic Discovery
DDS Dynamic Discovery is powerful and useful
Built-in to all CoreDX DDS Applications
▪ CoreDX DDS applications publish and subscribe to data
without configuring endpoints
▪ CoreDX DDS Entities do not require knowledge of other DDS
Entities they may be communicating with
Interoperable between DDS implementations
▪ Applications built on compliant DDS implementations will
automatically discover each other
Automatic
▪ No special configuration required
▪ Simply create DDS Entities
8. CoreDX DDS Features:
Dynamic Discovery (cont)
CoreDX DDS Applications (DomainParticipants)
Automatically discover each other
Exchange network information
▪ IP addresses for multicast and unicast data transfers
Producers and Consumers (DataWriters, DataReaders)
Automatically discover each other
Exchange configuration information
Determine if data exchange is appropriate
▪ Do Topics match?
▪ Do Data Types match?
▪ Do communication behavior expectations match?
If so, enable data exchange
9. CoreDX DDS Features:
Quality of Service Policies
QoS Policies tailor the behavior of data
communications
What are the reliability requirements?
How long is data saved for possible future
publication or future access by the application?
▪ What are the storage requirements?
What are the timing requirements?
How should data be presented to subscribers?
Should data be filtered?
Are there redundancy or failover requirements?
DDS specifies 22 distinct QoS Policies
Twin Oaks Computing, Inc. PROPRIETARY
10. CoreDX DDS Features:
Efficient Reliability: Overview
CoreDX DDS provides configurable Reliable
data communications
Even on unreliable networks (e.g. wireless)
Using UDP (MULTICAST and UNICAST)
CoreDX DDS Reliability Addresses
Dropped Packets
Out of Order Samples
Communication Disconnects
Application Re-Starts
11. CoreDX DDS Features:
Efficient Reliability: Protocol
01 RELIABLE Guarantees: 01
02 02
Data 03
• Delivery and Order Data 03
Writer 04 Reader 04
05 BEST EFFORT Guarantees: 05
06 • Order 06
07 07
07 06 05 04 03 02 01
Configurable Heartbeat and Performance monitored by
ACK/NACK interval readers and writers
Avoid packet storms Flexible handling of slow readers
Configuration items to balance Dynamically remove slow readers
latency and overhead
Heartbeats, delays, resource limits
12. CoreDX DDS Features:
Efficient Reliability: Example
One dropped
Writer sends Heartbeats sample
Heartbeats can be sent with
DATA messages Writer Reader
Reader returns ACK/NACK 01
01
Missed samples detected by
Reader 02 02 01
NACK Indicate specific missing 03 03 + HB 02
samples 04 03
04 ACK (1,3),
Combined with ACK to NACK [2]
04
acknowledge other samples 05 05
02 05
Writer can send Data using 06 06 + HB
MULTICAST 07 07 06
Repairs are sent UNICAST ACK (6) 07
Reader delivers samples to the
application in order
13. CoreDX DDS Features:
Durability
CoreDX DDS provides configurable Durable data
communications
CoreDX DDS Durability addresses
How long data is saved by Data Writers
If previously published data is sent to „late joining‟ DataReaders
Durability Options
Volatile: Published data is saved just long enough to be sent to
currently matched Readers
Transient Local: Published data is saved for as long as the Data
Writer is alive (until application exit)
Transient, Persistent: Published data is saved by an external
service, through application restarts, machine reboots
14. CoreDX DDS Features:
Durability: Example
Durability Example
Data
Producer
S1 S3 Data published with
Durability = TRANSIENT_LOCAL
S2 S4
Subscribing to data with Subscribing to data with S4 S2
Durability = VOLITILE Durability =
S4 TRANSIENT_LOCAL S2 S1
Data Data
Consumer 1 Consumer 2
15. CoreDX DDS Features:
Historical Data Caches
Each Data Reader and Data Writer maintains a Data Cache
Data Reader Cache
Holds received data to be delivered to the application
Can be sized and configured to save received data for later use
Multiple ways to access received data
CoreDX DDS „loans‟ data to the application
▪ Improves performance
▪ Eliminates extra data copy
Data Writer Cache
Holds published data to be written on the wire
Can be sized and configured to save historical data to be
delivered to late joining Readers
16. CoreDX DDS Features:
Filtering
Kinds of Filters:
Content Filters are specified by an SQL-like query
▪ Same syntax as the “WHERE” clause in an SQL query
Time Based Filters are specified by a duration for
minimum separate between samples
Read Filters allow the application to „read‟ specific
kinds of data from the Data Cache
▪ Previously seen / Not seen
▪ New data / Old data
▪ Alive / Dead
▪ Matching a content-based query
17. CoreDX DDS Features:
Filtering (cont)
Filters are configurable
By each Reader
Applied at the Writer or Reader
Filters can reduce network and
CPU load
Filter applied at the Writer
▪ Writer can send only the data requested by a Reader (UNICAST)
▪ Other Readers do not „wake up‟ to receive/process unwanted data
Filter applied at the Reader
▪ Writer can MULTICAST data to all Readers
▪ All Readers will „wake up‟ to receive / apply filters to data
18. CoreDX DDS Features:
Ownership
CoreDX DDS provides configurable Ownership of published
data
Shared: Readers receive (duplicate) data from all Writers
Exclusive: Readers receive one copy of data, even when multiple
Writers are publishing (duplicate) data
Data Data
Producer 1 Producer 2
S1 Ownership.kind = EXCLUSIVE S2 Ownership.kind = EXCLUSIVE
Ownership.strength = 10 Ownership.strength = 5
S1
The consumer will see data from
S2 only the strongest producer.
S1
Data
Consumer
20. CoreDX DDS Features:
Portability
Portable across languages
Common API defined for multiple languages
Portable across Operating Systems
Same programming experience on all
operating systems
Portable across vendors
Standardized API
21. CoreDX DDS Features:
Interoperability
What is it?
The ability of DDS implementations from different
vendors/sources to communicate
Why do we want it?
Increased flexibility in implementation decisions
Vendor independence
Open Standards from the OMG allow for
Interoperability
DDS API
RTPS Wire protocol
Vendors commit to and test Interoperability
▪ Twin Oaks Computing, RTI, (partial) Prism Tech, Gallium
22. CoreDX DDS:
Source Code: Portable, Certifiable
Features:
Minimal Lines of Source Code
▪ Entire „C‟ CoreDX DDS library < 35K SLOC
▪ Safety Critical Edition < 13K SLOC
Completely Native Source Code
▪ No 3rd party products or packages
Made in the USA
▪ All CoreDX product development performed in the United States, by United States
Citizens
Minimal dependencies on Operating System libraries
Benefits:
Eases analysis and certification of baseline
EASY TO PORT TO ANY PLATFORM: Enterprise to Bare-Metal
operating systems
Twin Oaks Computing, Inc
22 PROPRIETARY
24. CoreDX DDS:
Performance: CPU, Network
Long running throughput
test
• TX1024 byte messages
• Total throughput of over
700 Megabits/sec
• CPU utilization of a single
core
• doesn‟t exceed 30%
• machine has 4 cores
• Equates to less than 10%
of total CPU
Twin Oaks Computing, Inc
24 PROPRIETARY
25. CoreDX DDS:
Small Run-time Memory Requirements
CoreDX DDS run-time memory requirements
Local Entity Local Entity Remote (Discovered)
Size (bytes) Entity Size (bytes)
DomainParticipant * 12000 2100
DataReader 3200 2500
DataWriter 3200 2400
Topic 750 0
For example:
An application with * DomainParticipant size includes
▪ 1 DomainParticipant, all built-in Topics, DataWriters,
▪ 6 DataWriters, and and DataReaders
▪ 4 DataReaders
will require <100KB Heap Memory
Twin Oaks Computing, Inc
25 PROPRIETARY
27. CoreDX DDS Features:
Configurability
DDS API includes specific policies for tailoring
communication behavior.
Deadline Latency Budget Reliability
Destination Order Lifespan Resource Limits
Durability Liveliness Time Based Filter
Entity Factory Ownership Topic Data
Group Data Partition User Data
History Reader Data Lifecycle Writer Data Lifecycle
In addition, CoreDX DDS allows configuration of:
Transport Threads
Discovery Memory Usage
Reliability Logging
29. Comparison:
DDS and JMS
lookup ConnectionFactory JNDI lookup ConnectionFactory
create Connection create Connection
create Session create Session
create MessageProducer JMS create MessageConsumer
start the Connection Server start the Connection
write data read data
JMS requires a Server that must JMS Server often requires
be configured and connected significant resources, and creates
a single point of failure
create a DDS Participant
create a Topic create a DDS participant
create a Publisher create a Topic
create a DataWriter create a Subscriber
write data create a DataReader
Each DDS application contains all read data
necessary code for discovery and
communications, no server
required
30. DDS and JMS
Feature JMS DDS
Architecture Publish subscribe Publish subscribe (multicast)
Platform Same API is exposed for all HW, Same API is exposed for all HW,
Independence OS, and languages supported OS, and languages supported
Discovery of JNDI and JMS servers must be Dynamic Discovery, no need to
endpoints specified and configured specify where endpoints reside
Type Safety Generic Objects and XML are Strong type safety, application
not type safe calls write() and read() with a
specific data type
Tailoring Limited ability to tailor QoS policies allow for easy
communication communications tailoring of communication
behavior behaviors
Interoperability None Open standard with proven
interoperability
31. Comparison:
DDS and SOA Web Services
Web Server
create Service
enable web services configure Server Address
install web service Web call Service
Service get response
A web server must be configured The client must be configured with
to provide web services, and the the address of the web server
web service must be installed before the service can be called
create a DDS Participant create a DDS participant
create a Topic create a Topic
create a Publisher create a Subscriber
create a DataWriter create a DataReader
write data read data
Each DDS application contains all
necessary code for discovery and
communications, no server or
end point configuration required
32. DDS and SOA Web Services
Feature Web Services DDS
Architecture Message oriented Middleware Publish subscribe (multicast)
Platform Same API is exposed for all HW, Same API is exposed for all HW,
Independence OS, and languages supported. OS, and languages supported
Browser clients can run
anywhere
Discovery of Web server must be specified Dynamic Discovery, no need to
endpoints and configured specify where endpoints reside
Type Safety Use of HTTP and XML does not Strong type safety, application
provide strong type safety calls write() and read() with a
specific data type
Tailoring Limited ability to tailor QoS policies allow for easy
communication communications tailoring of communication
behavior behaviors
Interoperability Some interoperability with Open standard with proven
multiple protocols used: SOAP, interoperability
REST, WSDL
33. For More Information
Visit our Website
http://www.twinoakscomputing.com for:
Quick Start Guides
Free Evaluations
Free Demonstrations (with source code)
Programmer‟s Guide
Reference Manuals
White Papers
Contact Us
Phone: 1-855-671-8754
Email: contact@twinoakscomputing.com
Facebook / Linked In / Twitter / Pinterest / Google+
34. Summary
Common, Complex Communication Requirements:
Where do I get my data?
How often?
What happens if you don‟t send it?
What happens if I don‟t receive it?
How much received data do I need to store for future use?
How do I select (filter) only the data I need to receive?
CoreDX DDS addresses all these requirements
Twin Oaks Computing, Inc
34 PROPRIETARY
“All this, and No tradeoff in performance”These are graphs of performance benchmarks run over a Gbit ETHERNET network. As you can see, these numbers are pretty good.Throughput is above 900 Mbps, and latency is around 75 microsecs