This document provides an introduction to Eclipse Zenoh, an open source project that unifies data in motion, data at rest, and computations in a distributed system. Zenoh elegantly blends traditional publish-subscribe with geo-distributed storage, queries, and computations. The presentation will demonstrate Zenoh's advantages for enabling typical edge computing scenarios and simplifying large-scale distributed applications through real-world use cases. It will also provide an overview of Zenoh's architecture, performance, and APIs.
zenoh: zero overhead pub/sub store/query computeAngelo Corsaro
Unifies data in motion, data in-use, data at rest and computations.
It carefully blends traditional pub/sub with distributed queries, while retaining a level of time and space efficiency that is well beyond any of the mainstream stacks.
It provides built-in support for geo-distributed storages and distributed computations
This was the opening presentation of the Zenoh Summit in June 2022. The presentation goes through the motivations that lead to the design of the zenoh protocol and provides an introduction of its core concepts. This is the place to start to understand why you should care about zenoh and the way in which is disrupts existing technologies.
The recording for this presentation is available at https://bit.ly/3QOuC6i
zenoh -- the ZEro Network OverHead protocolAngelo Corsaro
This presentation introduces the key ideas behind zenoh -- an Internet scale data-centric protocol that unifies data-sharing between any kind of device including those constrained with respect to the node resources, such as computational resources and power, as well as the network.
zenoh: zero overhead pub/sub store/query computeAngelo Corsaro
Unifies data in motion, data in-use, data at rest and computations.
It carefully blends traditional pub/sub with distributed queries, while retaining a level of time and space efficiency that is well beyond any of the mainstream stacks.
It provides built-in support for geo-distributed storages and distributed computations
This was the opening presentation of the Zenoh Summit in June 2022. The presentation goes through the motivations that lead to the design of the zenoh protocol and provides an introduction of its core concepts. This is the place to start to understand why you should care about zenoh and the way in which is disrupts existing technologies.
The recording for this presentation is available at https://bit.ly/3QOuC6i
zenoh -- the ZEro Network OverHead protocolAngelo Corsaro
This presentation introduces the key ideas behind zenoh -- an Internet scale data-centric protocol that unifies data-sharing between any kind of device including those constrained with respect to the node resources, such as computational resources and power, as well as the network.
By John Breitenbach, RTI Field Applications Engineer
Contents
Introduction to RTI
Introduction to Data Distribution Service (DDS)
DDS Secure
Connext DDS Professional
Real-World Use Cases
RTI Professional Services
The Data Distribution Service (DDS) is a standard for ubiquitous, interoperable, secure, platform independent, and real-time data sharing across network connected devices. DDS is today used in a large class of 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.
Differently from traditional message-centric technologies, DDS is data-centric – the accent is on seamless (user-defined) data sharing as opposed to message delivery. Therefore, when embracing DDS and data-centricity, data modeling becomes a key step in the design of a distributed system.
This webcast will (1) explain the role and scope of data modeling in DDS, (2) introduce the techniques at the foundation of effective and extensible Data Models, and (3) summarize the most common DDS Data Modeling Idioms.
Making the right data available at the right time, at the right place, securely, efficiently, whilst promoting interoperability, is a key need for virtually any IoT application. After all, IoT is about leveraging access data – that used to be unavailable – in order to improve the ability to react, manage, predict and preserve a cyber-physical system.
The Data Distribution Service (DDS) is a standard for interoperable, secure, and efficient data sharing, used at the foundation of some of the most challenging Consumer and Industrial IoT applications, such as Smart Cities, Autonomous Vehicles, Smart Grids, Smart Farming, Home Automation and Connected Medical Devices.
In this presentation we will (1) introduce the Eclipse Cyclone DDS project, (2) provide a quick intro that will get you started with Cyclone DDS, (3) present a few Cyclone DDS use cases, and (4) share the Cyclone DDS development road-map.
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.
View On-Demand http://ecast.opensystemsmedia.com/403
Repeat Success, Not Mistakes; Use DDS Best Practices to Design Your Complex Distributed Systems
RTI Connext DDS is a powerful tool that lets you efficiently build and integrate complex distributed systems like no other technology – if you use it right. Be aware of how to get the most out of DDS and how to avoid common pitfalls when developing your system. We've developed RTI Connext best practices over the course of hundreds of customer projects and many years. In this webinar, you will learn how to apply the best practices we have developed to use RTI Connext DDS in ways that will enable your system to scale effectively with optimal performance, while avoiding missteps that will cause poor performance, non-determinism and scalability problems.
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.
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.
Data-Centric and Message-Centric System ArchitectureRick Warren
Presentation from April, 2010 summarizing the principles of data-centric design and how they apply to DDS technology. Message-centric design is presented by way of contrast.
Apache Spark Data Source V2 with Wenchen Fan and Gengliang WangDatabricks
As a general computing engine, Spark can process data from various data management/storage systems, including HDFS, Hive, Cassandra and Kafka. For flexibility and high throughput, Spark defines the Data Source API, which is an abstraction of the storage layer. The Data Source API has two requirements.
1) Generality: support reading/writing most data management/storage systems.
2) Flexibility: customize and optimize the read and write paths for different systems based on their capabilities.
Data Source API V2 is one of the most important features coming with Spark 2.3. This talk will dive into the design and implementation of Data Source API V2, with comparison to the Data Source API V1. We also demonstrate how to implement a file-based data source using the Data Source API V2 for showing its generality and flexibility.
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!
Apache Spark in Depth: Core Concepts, Architecture & InternalsAnton Kirillov
Slides cover Spark core concepts of Apache Spark such as RDD, DAG, execution workflow, forming stages of tasks and shuffle implementation and also describes architecture and main components of Spark Driver. The workshop part covers Spark execution modes , provides link to github repo which contains Spark Applications examples and dockerized Hadoop environment to experiment with
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.
Zenoh développe rapidement le projet Eclipse qui unifie les données en mouvement, les données au repos et les calculs. Il mélange élégamment les pub/sub traditionnels avec un stockage, des requêtes et des calculs géo-distribués, tout en maintenant un niveau d’efficacité temporelle et spatiale qui va bien au-delà de n’importe quelle pile générale. Cette présentation donnera un aperçu d’Eclipse Zenoh ainsi qu’une explication précise des problématiques qui ont motivé le lancement de ce projet. Nous aborderons une série de cas pratiques qui démontrent les avantages qu’offre Zenoh en matière de facilitation et d’optimisation de scénarios edge types et de simplification du développement d’applications distribuées à grande échelle.
By John Breitenbach, RTI Field Applications Engineer
Contents
Introduction to RTI
Introduction to Data Distribution Service (DDS)
DDS Secure
Connext DDS Professional
Real-World Use Cases
RTI Professional Services
The Data Distribution Service (DDS) is a standard for ubiquitous, interoperable, secure, platform independent, and real-time data sharing across network connected devices. DDS is today used in a large class of 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.
Differently from traditional message-centric technologies, DDS is data-centric – the accent is on seamless (user-defined) data sharing as opposed to message delivery. Therefore, when embracing DDS and data-centricity, data modeling becomes a key step in the design of a distributed system.
This webcast will (1) explain the role and scope of data modeling in DDS, (2) introduce the techniques at the foundation of effective and extensible Data Models, and (3) summarize the most common DDS Data Modeling Idioms.
Making the right data available at the right time, at the right place, securely, efficiently, whilst promoting interoperability, is a key need for virtually any IoT application. After all, IoT is about leveraging access data – that used to be unavailable – in order to improve the ability to react, manage, predict and preserve a cyber-physical system.
The Data Distribution Service (DDS) is a standard for interoperable, secure, and efficient data sharing, used at the foundation of some of the most challenging Consumer and Industrial IoT applications, such as Smart Cities, Autonomous Vehicles, Smart Grids, Smart Farming, Home Automation and Connected Medical Devices.
In this presentation we will (1) introduce the Eclipse Cyclone DDS project, (2) provide a quick intro that will get you started with Cyclone DDS, (3) present a few Cyclone DDS use cases, and (4) share the Cyclone DDS development road-map.
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.
View On-Demand http://ecast.opensystemsmedia.com/403
Repeat Success, Not Mistakes; Use DDS Best Practices to Design Your Complex Distributed Systems
RTI Connext DDS is a powerful tool that lets you efficiently build and integrate complex distributed systems like no other technology – if you use it right. Be aware of how to get the most out of DDS and how to avoid common pitfalls when developing your system. We've developed RTI Connext best practices over the course of hundreds of customer projects and many years. In this webinar, you will learn how to apply the best practices we have developed to use RTI Connext DDS in ways that will enable your system to scale effectively with optimal performance, while avoiding missteps that will cause poor performance, non-determinism and scalability problems.
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.
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.
Data-Centric and Message-Centric System ArchitectureRick Warren
Presentation from April, 2010 summarizing the principles of data-centric design and how they apply to DDS technology. Message-centric design is presented by way of contrast.
Apache Spark Data Source V2 with Wenchen Fan and Gengliang WangDatabricks
As a general computing engine, Spark can process data from various data management/storage systems, including HDFS, Hive, Cassandra and Kafka. For flexibility and high throughput, Spark defines the Data Source API, which is an abstraction of the storage layer. The Data Source API has two requirements.
1) Generality: support reading/writing most data management/storage systems.
2) Flexibility: customize and optimize the read and write paths for different systems based on their capabilities.
Data Source API V2 is one of the most important features coming with Spark 2.3. This talk will dive into the design and implementation of Data Source API V2, with comparison to the Data Source API V1. We also demonstrate how to implement a file-based data source using the Data Source API V2 for showing its generality and flexibility.
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!
Apache Spark in Depth: Core Concepts, Architecture & InternalsAnton Kirillov
Slides cover Spark core concepts of Apache Spark such as RDD, DAG, execution workflow, forming stages of tasks and shuffle implementation and also describes architecture and main components of Spark Driver. The workshop part covers Spark execution modes , provides link to github repo which contains Spark Applications examples and dockerized Hadoop environment to experiment with
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.
Zenoh développe rapidement le projet Eclipse qui unifie les données en mouvement, les données au repos et les calculs. Il mélange élégamment les pub/sub traditionnels avec un stockage, des requêtes et des calculs géo-distribués, tout en maintenant un niveau d’efficacité temporelle et spatiale qui va bien au-delà de n’importe quelle pile générale. Cette présentation donnera un aperçu d’Eclipse Zenoh ainsi qu’une explication précise des problématiques qui ont motivé le lancement de ce projet. Nous aborderons une série de cas pratiques qui démontrent les avantages qu’offre Zenoh en matière de facilitation et d’optimisation de scénarios edge types et de simplification du développement d’applications distribuées à grande échelle.
Evolution from EDA to Data Mesh: Data in Motionconfluent
Thoughtworks Zhamak Dehghani observations on these traditional approaches’s failure modes, inspired her to develop an alternative big data management architecture that she aptly named the Data Mesh. This represents a paradigm shift that draws from modern distributed architecture and is founded on the principles of domain-driven design, self-serve platform, and product thinking with Data. In the last decade Apache Kafka has established a new category of data management infrastructure for data in motion that has been leveraged in modern distributed data architectures.
Java Abs Peer To Peer Design & Implementation Of A Tuple Sncct
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A Secure and Dynamic Multi-keyword Ranked Search Scheme over Encrypted Cloud ...1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
A Secure and Dynamic Multi-keyword Ranked Search Scheme over Encrypted Cloud ...1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
How Consistent Data Services Deliver Simplicity, Compatibility, And Lower CostDana Gardner
A transcript of a discussion on the latest technologies and products delivering common data services across today’s hybrid cloud, distributed data centers, and burgeoning edge landscapes.
Data Virtualization to Survive a Multi and Hybrid Cloud WorldDenodo
Watch full webinar here:https://buff.ly/2Edqlpo
Hybrid cloud computing is slowing becoming the standard for businesses. The transition to hybrid can be challenging depending on the environment and the needs of the business. A successful move will involve using the right technology and seeking the right help. At the same time, multi-cloud strategies are on the rise. More enterprise organizations than ever before are analyzing their current technology portfolio and defining a cloud strategy that encompasses multiple cloud platforms to suit specific app workloads, and move those workloads as they see fit.
In this session, you will learn:
*Key challenges of migration to the cloud in a complex data landscape
*How data virtualization can help build a data driven, multi-location cloud architecture for real time integration
*How customers are taking advantage of data virtualization to save time and costs with limited resources
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
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zenoh -- the ZEro Network OverHead protocolAngelo Corsaro
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Fog computing aims at providing horizontal, system-level, abstractions to distribute computing, storage, control and networking functions closer to the user along a cloud-to-thing continuum. Whilst fog computing is increasingly recognised as the key paradigm at the foundation of Consumer and Industrial Internet of Things (IoT), most of the initiatives on fog computing focus on extending cloud infrastructure. As a consequence, these infrastructure fall short in addressing heterogeneity and resource constraints characteristics of fog computing environments.
fog⌀5 (read as fog O-five or fog OS) is an Eclipse IoT Project that is building a fog computing infrastructure from first principle. In other terms, fog⌀5 has been designed to address the challenges induced by fog computing in terms of heterogeneity, decentralisation, resource constraints, geographical scale and security.
This webcast will introduce fog⌀5, motivate its architecture and building blocks as well as provide a demonstration of fog⌀5 provisioning applications that span from the cloud to the things.
The video recording for this presentation is available at https://www.youtube.com/watch?v=Osl3O5DxHF8
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Data Sharing in Extremely Resource Constrained EnvionrmentsAngelo Corsaro
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RUSTing is not a tutorial on the Rust programming language.
I decided to create the RUSTing series as a way to document and share programming idioms and techniques.
From time to time I’ll draw parallels with Haskell and Scala, having some familiarity with one of them is useful but not indispensable.
Vortex II -- The Industrial IoT Connectivity StandardAngelo Corsaro
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This presentation will (1) introduce the new features introduced in with Vortex 2.4, (2) explain how Vortex 2.4 addresses the requirements of Industrial Internet of Things application better than any other existing platform, and (3)showcase how innovative companies are using Vortex for building leading edge Industrial Internet of Things applications.
Fog computing has emerged as a new paradigm for architecting IoT applications that require greater scalability, performance and security. This talk will motivate the need to Fog Computing and explain what it is and how it differs from other initiatives in Telco such as Mobile/Multiple-Access Edge Computing.
The Object Management Group (OMG) Data Distribution Service (DDS) and the OPC Foundation OLE for Process Control Unified Architecture (OPC-UA) are commonly considered as two of the most relevant technologies for data and information management in the Industrial Internet of Things. Although several articles and quotes on the two technologies have appeared on various medias in the past six months, there is still an incredible confusion on how the two technology compare and what’s their applicability.
This presentation, was motivated by the author's frustration with reading and hearing so many mis-conceptions as well as “apple-to-oranges” comparisons. Thus to contribute to clarity and help with positioning and applicability this webcast will (1) explain the key concepts behind DDS and OPC-UA and relate them with the reason why these technologies were created in the first place, (2) clarify the differences and applicability in IoT for DDS and OPC-UA, and (3) report on the ongoing standardisation activities that are looking at DDS/OPC-UA inter-working.
The Cloudy, Foggy and Misty Internet of Things -- Toward Fluid IoT Architect...Angelo Corsaro
Early Internet of Things(IoT) applications have been build around cloud-centric architectures where information generated at the edge by the “things” in conveyed and processed in a cloud infrastructure. These architectures centralise processing and decision on the data-centre assuming sufficient connectivity, bandwidth and latency.
As applications of the Internet of Things extend to industrial and more demanding consumer applications, the assumptions underlying cloud-centric architectures start to be violated as, — for several of these applications — connectivity, bandwidth and latency to the data-centre are a challenge.
Fog and Mist computing have emerged as forms of “Cloud Computing” closer to the “Edge” and to the “Things” that should alleviate the connectivity, bandwidth and latency challenges faced by Industrial and extremely demanding Consumer Internet of Things Applications.
This presentation, will (1) introduce Cloud, Fog and Mist Computing architectures for the Internet of Things, (2) motivate their need and explain their applicability with real-world use cases, and (3) introduce the concept of fluid IoT architectures and explain how these can be architected and built.
Building IoT Applications with Vortex and the Intel Edison Starter KitAngelo Corsaro
Whilst there isn’t a universal agreement on what exactly is IoT, nor on the line that separates Consumer and Industrial IoT, everyone unanimously agrees that unconstrained access to data is the game changing dimension of IoT.
Vortex positions as the best data sharing platform for IoT enabling data to flow unconstrained across devices and at any scale.
This presentation, will demonstrate how quickly and effectively you can build real-world IoT applications that scale using Vortex and the Intel Edison Starter Kit. Specifically, you will learn how to leverage vortex to virtualise devices, integrate different protocols, flexibly execute analytics where it makes the most sense and leverage Cloud as well as Fog computing architectures.
Throughout the webcast we will leverage Intel’s Edison starter kit, available at https://software.intel.com/en-us/iot/hardware/edison, you will be able to download our code examples before the webcast to particulate to the live demo!
Microservices Architecture with Vortex — Part IIAngelo Corsaro
As we saw in Part I, Microservice Architectures are a modular approach to system-building where we decompose complex applications in, small, autonomous and loosely coupled processes communicating through a language and platform independent API. In this webcast we will briefly refresh the key ideas behind Microservice Architectures and then look at how they can be easily implemented in Vortex. Specifically we will (1) look into the key idioms and patterns that are used when implementing Vortex Microservices and (2) walk you through the design and implementation of a micro service application for a real-world use case.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
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This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
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Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
DevOps and Testing slides at DASA ConnectKari Kakkonen
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Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...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 the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
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The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
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Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
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Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
zenoh: The Edge Data Fabric
1. Angelo Corsaro, PhD
Chief Technology Officer
Advanced Technology Office
angelo@adlink-labs.tech
Data
The
Edge
Fabric
<
2. Abstract
Zenoh is rapidly growing Eclipse project that uni
fi
es data in motion,
data at rest and computations. It elegantly blends traditional pub/sub
with geo distributed storage, queries and computations, while
retaining a level of time and space ef
fi
ciency that is well beyond any of
the mainstream stacks. This presentation will provide an introduction to
Eclipse Zenoh along with a crisp explanation of the challenges that
motivated the creation of this project. We will go through a series of
real-world use cases that demonstrate the advantages brought by
Zenoh in enabling and optimising typical edge scenarios and in
simplifying the development of any scale distributed applications.
3. Speaker Bio
Angelo Corsaro, Ph.D. is Chief Technology Of
fi
cer (CTO) at ADLINK Technology Inc. where he
looks after corporate technology strategy and innovation, leads the Advanced Technology
Of
fi
ce and the Software and Technology Business Unit.
Angelo is a world top expert in edge/fog computing and a well known researcher in the area of
high performance and large scale distributed systems. Angelo has over 100 publications on
referred journals, conferences, workshops, and magazines. Angelo has co-authored over ten
international standards.
Specialties: Fog/Edge Computing, Industrial and Consumer Internet of Things, Innovation and
Innovation Management, Product Strategy, Open Source, High Performance Computing, Large
Scale Mission/Business Critical Distributed Systems, Real-Time Systems, Software Patterns,
Functional Programming Languages
6. Moving and Resting
Technologies for dealing with
data in motion and data at rest
have belonged historically to
different families
Publish/Subscribe is today the
leading paradigm for dealing
with with data in motion
Databases (SQL and NoSQL)
are the leading paradigm to
deal with data at rest
Data in Motion
Data at Rest
7. Pushing and Pulling
Technologies for dealing
with data in motion and
data at rest also distinguish
in another dimension:
Data in motion is Pushed
to interested parties
Data at rest is Pulled when
needed
Push
Data at Rest
Pull
9. Decentralisation
The increasing availability of and
storage, compute capabilities on
devices is creating new
opportunities for computing
and storing and data much
closer its production
Existing technologies for data in
motion and data at rest fall short
in supporting this scenario.
More importantly fail to provide a
uni
fi
ed data management.
11. Robotics
Robotics applications are quickly
evolving to require swarm
coordination, Internet-Scale
management and teleoperation
Robots are increasingly operating in
swarms and over constantly
expanding geographical regions
12. Computation Offloading
Next generation robotics (and
autonomous driving) applications
need to leverage surrounding
infrastructure to of
fl
oad
computations and facilitate
coordination
13. Key Differences
• Many
• Moving
• Geo-Distributed
• Collaborative
• Internet Scale
• Open Environment
• Distributed Computing
• One
• Fixed
• Geo-localised
• Stand-Alone
• LAN Scale
• Closed Environment
• Cloud Computing
15. Smart Home Today
Data produced locally is sent to the cloud
where it is processed and stored
The core of the application logic runs on the
cloud.
Most if not all of the interactions with devices
that are close to you are through the cloud
This leads to several problems, including
energy waste, availability in case of
connectivity issues, privacy concerns…
16. Exploiting Locality
Ideally we would want communication to be local
whenever possible.
Ideally we would want to place computations
closer to data sources
Ideally we would want most of the data to be kept
in our house… But still access it from anywhere — if
I have the rights to do so
Some could be still processed or stored on the
cloud — but that should be a choice not the only
option.
17. Managing a Residence
Let’s assume for a moment that we want to exploit data and computation
locality at each house, yet we would like to easily monitor or query any
kind of data — for which we have the rights. How can I do that?
18. Traditional Approach #1
Replicate all data on the cloud
and use that as the location to
access information on the
houses
The drawbacks of this solution
is that all data is duplicated,
energy is wasted to send data
across the cloud, and privacy is
again at risk …
19. Traditional Approach #2
Data is kept on the house and
when needing to access it the
house of interest is addressed
The drawbacks of this solution
is there is no location
transparency. What if I want to
keep some of the data on an
edge server? Or even the
cloud?
…
20. Wouldn’t be nice if…
We could keep data where it
makes sense an retrieve it when
needed in a location transparent
manner — just naming the data
Wouldn’t it be nice if we could
provision application logic
wherever it made sense on this
computing fabric?
22. Technological Gap
The ecosystem of technologies available
today for data plane are unable to cover
the needs of these large scale
distributed systems because either
cannot work at the proper scale, e.g.
DDS, or are inherently depending on
broker technologies, e.g. MQTT, AMQP
Additionally none of this technologies
help with dealing with geo-distributed
data at rest
24. Uni
fi
es data in motion, data in-use, data at
rest and computations.
It carefully blends traditional pub/sub with
distributed queries, while retaining a level of
time and space ef
fi
ciency that is well beyond
any of the mainstream stacks.
It provides built-in support for geo-distributed
storages and distributed computations
25. Provides a high level API for pub/sub and
distributed queries, data representation
transcoding, an implementation of geo-distributed
storage and distributed computed values
zenoh Data Link
Network
Transport
Physical
zenoh
zenoh.net
Implements a networking layer capable of running
above a Data Link, Network or Transport Layer. This
protocol provides primitives for ef
fi
cient pub/sub
and distributed queries. It supports fragmentation
and ordered reliable delivery.
zenoh.net
28. Brokered Communication
Router and peers can
help with brokering
communication
between clients as
well as between
clients and mesh of
peers
Router
Client
Client
Client
Peer
Peer
Peer
Peer
Peer
Client
Client
Client
31. Naming Data
Following the tradition of Named Data Networking protocols, data is
named by a sequence of byte arrays — called key — such as:
/home/kitchen/sensors/temp
/home/kitchen/sensors/C202
Data interest and intents are expressed by means of keys regular expressions,
such as:
/home/*/sensors/temp
/home/**/C202
32. Selecting Data
Uses selector to de
fi
nes data sets. A selector is composed by a key
expression, and optionally a predicate, a projection and a set of
properties
/myhome/*/sensor/temp?value>25
/mycar/dynamics?speed>25#acceleration
The key-expression is used to route the query, while predicate, properties,
projection, etc., are interpreted only by the entity that executes the query. It also
provide different policies to control query consolidation and completeness
and potentially quorums
33. Primitives: Entities
Resource. A named data, in other term a (key,value)
Publisher. A spring of values for a key expression
Subscriber. A sink of values for a key expression
Queryable. A well of values for a key expression
(e.g. /home/kitchen/sensor/temp, 21.5
(e.g. /home/kitchen/sensor/temp
/home/kitchen/sensor/hum, 0.67)
/home/kitchen/sensor/* )
(e.g. /home/kitchen/sensor/temp
/home/kitchen/sensor/*)
(e.g. /home/**)
34. Primitives: Operations
open/close — Open/Close a zenoh.net session
scout — Looks for zenoh entities, the kinds of relevant nodes, e.g. peers,
router, etc., is speci
fi
ed by a bit-mask.
declare/undeclare — Declare/Undeclare resource, publisher, subscriber and
queryable. Declarations are used for discovery and various optimisations. For
subscribers the declare primitive registers a user provided call-back that will
be triggered when data is available. For queryable, the declare primitive register
a user provided call-back triggered whenever a query needs to be answered.
35. Primitives: Operations
write — Writes data for a key expression
query — Issues a distributed query and returns a stream of results. The
query target, coverage and consolidation depends on policies
pull — Pulls data for a pull subscriber.
36. Storage
A storage is de
fi
ned by:
Selector. De
fi
nes the set of
resources keys that stores this
storage
Back-end. De
fi
nes the storage
technology used
/myhome/status/**
…
Storage Back-end
Storage Selector
zenoh storages can be created via the
administration API anywhere on the network
and back-ends are dynamically loaded plugins.
zenoh storages automatically align their
initial state, but can also be bound to
existing data-bases
37. Eval
An eval is de
fi
ned by:
Selector. De
fi
nes the set of
resources keys that will trigger
this computation
Implementation. The user
code implementing the
computation
Eval Implementation
/myhome/energy-cons
Eval Selector
45. Protocol Summary Highlights
Most wire/power/memory ef
fi
cient protocol in the market to provide
connectivity to extremely constrained targets
Supports push and pull pub/sub along with distributed queries
Resource keys are represented as integers on the wire, these integer
are local to a session => good for wire ef
fi
ciency
Supports for peer-to-peer and routed communication.
Support for zero-copy.
Ordered reliable data delivery and fragmentation.
Minimal wire overhead for user data is 4-6 bytes
Data Link
Network
Transport
Physical
zenoh
zenoh.net
55. Greetings
from zenoh import Zenoh
# Get a zenoh session
zs = Zenoh({‘peer’: ‘tcp/eu.zenoh.io:7447’})
z = zs.workspace()
# play around
z.put(“/demo/eu/greet/italian”, “Ciao!”)
57. Getting Greetings
from zenoh import Zenoh, ChangeKind
# Define the listener
def listener(change):
print("{} : {} (encoding: {} , timestamp: {})”
.format(change.path,
"DELETED" if change.kind == ChangeKind.DELETE
else change.value.get_content(),
"none" if change.kind == ChangeKind.DELETE
else change.value.encoding_descr(),
change.timestamp))
z.subscribe(“/demo/**/greet/*“, listener)
58. Finding out Greetings
# How do people greet in EU?
workspace.get(“/demo/eu/**/greet”)
# How about American?
workspace.get(“/demo/us-*/**/greet”)
# Just get me all you know about greeting…
workspace.get(“/demo/**/greet”)
62. Greeting of the Day
Imagine you want to do a greeting of the day that each time
somebody tries to query it generates a random quote, or a
daily quote, etc.
We could do that with an eval, here is how:
def quote_eval(request):
make_a_cute_quote(request)
z.register_eval(“/demo/*/greet/*/daily”, quote_eval)
66. ROS2 and
ROS2 based robots can leverage zenoh
into two ways (1) by leveraging a ROS2
RMW for zenoh, or (2) by leveraging the
zenoh-bridge-dds which transparently
moves R2X communication over zenoh
The latter case does not require any
change to your robot, not even a
recompile / re-link
Zenoh also supports full interoperability
with ROS2 in the sense than you can
read/write data from/into ROS2 via native
zenoh API
68. Internet Scale Robotics
Zenoh enables for mesh peer-
to-peer communication when
useful, routed communication
when necessary and in general
enables ef
fi
cient Internet-scale
Additionally, it does not require
any changes to your existing
ROS2 systems.
72. zenoh is an innovative and performant
protocol that solves some of they problems
at the very core of IoT and Edge Computing
Its open architecture enables to easily
expand both storage back-ends as well as
protocols that are routed and integrated into
the zenoh world
If you like zenoh, star our repo and start
hacking some code!