DDS is becoming a key integration technology for the Internet of Things. A wide variety of industries are using DDS to connect real-world systems. These include healthcare, industrial automation, automotive, energy, transportation, and manufacturing. In these real-world, real-time systems, the right answer delivered too late is wrong. DDS provides a scalable, high-performance software data bus to handle the demanding volume, variety, and speed of data.
DDS is a powerful technology that can be difficult to implement quickly. Now, RTI is introducing a new tool that accelerates development by orders of magnitude! This webinar will show you how to quickly go from an initial concept to a working and fully functional implementation in hours instead of weeks. The new tool, Prototyper, leverages simple scripting to build distributed modules for RTI Connext™. It quickly turns concepts into implementation. We will illustrate it using a real-world example – starting from an initial system concept, we will walk through the 5 critical steps to build a complete working system.
This webinar is for you, if you have ever wondered:
I have an idea! How can I quickly show a working proof of concept?
I have a very short timeline and/or a very limited staff. Can DDS help me get it done faster than other technology options?
I am new to DDS. How can I quickly get something working without having to become a DDS expert?
I am defining a data model. Is is better to model the data this way or that?
I have a data model. Do these QoS policies make sense?
I have a working system. Are the data flows working correctly? How can I test and validate?
This is the slides of the UCLA School of Engineering Matlab workshop on Matlab graphics.
Learning Matlab graphics by examples:
- In 2 hours, you will be able to create publication-quality plots.
- Starts from the basic 2D line plots to more advanced 3D plots.
- You will also learn some advanced topics like fine-tuning the appearance of your figure and the concept of handles.
- You will be able to create amazing animations: we use 2D wave equation and Lorentz attractor as examples.
This is the slides of the UCLA School of Engineering Matlab workshop on Matlab graphics.
Learning Matlab graphics by examples:
- In 2 hours, you will be able to create publication-quality plots.
- Starts from the basic 2D line plots to more advanced 3D plots.
- You will also learn some advanced topics like fine-tuning the appearance of your figure and the concept of handles.
- You will be able to create amazing animations: we use 2D wave equation and Lorentz attractor as examples.
This file contains all the practicals with output regarding GTU syllabus. so it will help to IT and Computer engineering students. It is really knowledgeable so refer these for computer graphics practicals.
Spark's capabilities as a better and faster Hadoop, as a distributed Scala platform, and as an interactive, batch and streaming environment are quite well known. But its prowess to be all that as a multilingual platform have not received sufficient spotlight.
Traditionally RDBMS environments needed to glue together set oriented SQL with row-level specialized procedural languages (e.g. Pl/SQL), or use APIs in non-SQL languages e.g. JDBC. In spark however, the confluence of Scala and SQL is that of two equals as both are set or collection oriented, but have their own unique strengths.
This presentation will illustrate with background and examples on how to exploit this fusion of Scala and SQL in a way that takes advantage of both their strengths as well as boosts productivity.
Rainer Grimm, “Functional Programming in C++11”Platonov Sergey
C++ это мультипарадигменный язык, поэтому программист сам может выбирать и совмещать структурный, объектно-ориентированный, обобщенный и функциональный подходы. Функциональный аспект C++ особенно расширился стандартом C++11: лямбда-функции, variadic templates, std::function, std::bind. (язык доклада: английский).
This file contains all the practicals with output regarding GTU syllabus. so it will help to IT and Computer engineering students. It is really knowledgeable so refer these for computer graphics practicals.
Spark's capabilities as a better and faster Hadoop, as a distributed Scala platform, and as an interactive, batch and streaming environment are quite well known. But its prowess to be all that as a multilingual platform have not received sufficient spotlight.
Traditionally RDBMS environments needed to glue together set oriented SQL with row-level specialized procedural languages (e.g. Pl/SQL), or use APIs in non-SQL languages e.g. JDBC. In spark however, the confluence of Scala and SQL is that of two equals as both are set or collection oriented, but have their own unique strengths.
This presentation will illustrate with background and examples on how to exploit this fusion of Scala and SQL in a way that takes advantage of both their strengths as well as boosts productivity.
Rainer Grimm, “Functional Programming in C++11”Platonov Sergey
C++ это мультипарадигменный язык, поэтому программист сам может выбирать и совмещать структурный, объектно-ориентированный, обобщенный и функциональный подходы. Функциональный аспект C++ особенно расширился стандартом C++11: лямбда-функции, variadic templates, std::function, std::bind. (язык доклада: английский).
As the amount of metrics, software that produce and process them, and people involved in them continue to increase, we need better ways to organize them, to make them self-describing, and do so in a way that is consistent. Leveraging this, we can then automatically build graphs and dashboards, given a query that represents an information need, even for complicated cases. We can build richer visualizations, alerting and fault detection. This talk will introduce the concepts and related tools, demonstrate possibilities using the Graph-Explorer interface, and lay the groundwork for future work.
Overview of a few ways to group and summarize data in R using sample airfare data from DOT/BTS's O&D Survey.
Starts with naive approach with subset() & loops, shows base R's tapply() & aggregate(), highlights doBy and plyr packages.
Presented at the March 2011 meeting of the Greater Boston useR Group.
Business Dashboards using Bonobo ETL, Grafana and Apache AirflowRomain Dorgueil
Zero-to-one hands-on introduction to building a business dashboard using Bonobo ETL, Apache Airflow, and a bit of Grafana (because graphs are cool). The talk is based on the early version of our tools to visualize apercite.fr website. Plan, Implementation, Visualization, Monitoring and Iterate from there.
A presentation I made for Apache Spark and Apache Cassandra Integration.
First I present what are some of the differences between RDBMS and NoSQL, then I proceed with the Cassandra infrastructure and usual errors when creating a Cassandra Data Model.
Finally, I provide the Spark underlying main concepts and some settings for proper configuration.
Monitoring Your ISP Using InfluxDB Cloud and Raspberry PiInfluxData
When a large group of people change their habits, it can be tricky for infrastructures! Working from home and spending time indoor today means attending video calls and streaming movies and tv shows. This leads to increased internet traffic that can create congestion on the network infrastructure. So how do you get real-time visibility into your ISP connection? In this meetup, Mirko presents his setup based on a time series database and Raspberry Pi to better understand his ISP connection quality and speed — including upload and download speeds. Join us to discover how he does it using Telegraf, InfluxDB Cloud, Astro Pi, Telegram and Grafana! Finally, proof that your ISP connection is (or is not) as fast as it promises.
Real-Time Innovations (RTI) is the largest software framework provider for smart machines and real-world systems. The company’s RTI Connext® product enables intelligent architecture by sharing information in real-time, making large applications work together as one.
Originally presented on April 11, 2017
Watch on-demand: https://event.on24.com/eventRegistration/EventLobbyServlet?target=reg20.jsp&referrer=&eventid=1383298&sessionid=1&key=96B34B2E00F5FAA33C2957FE29D84624®Tag=&sourcepage=register
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
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
GridMate - End to end testing is a critical piece to ensure quality and avoid...
Build It Fast: 5 Steps from Concept to Working Distributed System
1. RTI QuickStart Training
Build it Fast:
5 Steps from Concept to Working
Distributed System
Rajive Joshi, Ph.D.
Principal Solution Architect
Webinar
Real-Time Innovations Inc.
September 25, 2013
3. Agenda
• Why is building distributed systems hard?
• The 5 Critical Steps – Best Practice
• The Prototyper – Separating Structure and
Behavior
• Defining structure using XML
• Coding behavior using Lua – A Small Fast Dynamic
Scripting Language
• Real-World Example
• Summary
4. Why is Building Distributed Systems Hard?
• Logical Design Considerations
– Data flows
– Data delivery: availability, timing, ordering, reliability, filtering,
fault tolerance, etc.
– Component behaviors
• Physical Design Considerations
– Platform Differences: CPU, OS, Programming Languages
– Discovery and Network configurations
– Low Level Device I/O
• Performance & Scalability Considerations
– # of data flows
– # of components/endpoints
– Latency vs. Throughput
5. The 5 Critical Steps
Articulate Concept
1. Draw a diagram of the components and the interconnecting data-
flows
Define Structure
2. Define the data types for the interconnecting data flows (in IDL or
XML)
3. Define the system structure as a collection of data-oriented
component interfaces (in XML)
Configure Behavior
4. Code the component behavior (in the Lua scripting language)
5. Adjust QoS policies to achieve the desired data-flow behavior
Best
Practice
6. The RTI Connext Platform Continues to Grow…
C/C++/Java/C#/Ada
• Code Generation
• Edit/Compile/Link/Run
Lua Scripting (in RTI Prototyper Runtime)
• Edit/Run(live update)
New!
7. The RTI Prototyper with Lua
1. -- Interface: parameters, inputs, outputs
2. local A, B, C = 30, 30, 10 -- Change the 'C' parameter to to see various flower shapes
3. local ShapeWriter = CONTAINER.WRITER[3] -- Triangles
4.
5. -- Global counter (preserved across invocations)
6. if not count then count = 0 else count = count + 1 end
7.
8. local shape = ShapeWriter.instance;
9. local angle = count % 360;
10.
11. shape['x'] = 120 + (A+B) * math.cos(angle) + B * math.cos((A/B-C)*angle)
12. shape['y'] = 120 + (A+B) * math.sin(angle) + B * math.sin((A/B-C)*angle)
13.
14. shape['shapesize'] = 5
15. shape['color'] = "RED"
16.
17. ShapeWriter:write() Lua Component
N inputs M outputs
DDS
8. Prototyper (Container)
The RTI Prototyper with Lua
Lua Engine
1. -- Interface: parameters, inputs, outputs
2. local A, B, C = 30, 30, 10 -- Change the 'C' parameter to to see various flower shapes
3. local ShapeWriter = CONTAINER.WRITER[3] -- Triangles
4.
5. -- Global counter (preserved across invocations)
6. if not count then count = 0 else count = count + 1 end
7.
8. local shape = ShapeWriter.instance;
9. local angle = count % 360;
10.
11. shape['x'] = 120 + (A+B) * math.cos(angle) + B * math.cos((A/B-C)*angle)
12. shape['y'] = 120 + (A+B) * math.sin(angle) + B * math.sin((A/B-C)*angle)
13.
14. shape['shapesize'] = 5
15. shape['color'] = "RED"
16.
17. ShapeWriter:write()
DDS
Lua Component
Behavior
9. Prototyper (Container)
The RTI Prototyper with Lua
Lua Engine
1. -- Interface: parameters, inputs, outputs
2. local A, B, C = 30, 30, 10 -- Change the 'C' parameter to to see various flower shapes
3. local ShapeWriter = CONTAINER.WRITER[3] -- Triangles
4.
5. -- Global counter (preserved across invocations)
6. if not count then count = 0 else count = count + 1 end
7.
8. local shape = ShapeWriter.instance;
9. local angle = count % 360;
10.
11. shape['x'] = 120 + (A+B) * math.cos(angle) + B * math.cos((A/B-C)*angle)
12. shape['y'] = 120 + (A+B) * math.sin(angle) + B * math.sin((A/B-C)*angle)
13.
14. shape['shapesize'] = 5
15. shape['color'] = "RED"
16.
17. ShapeWriter:write()
Lua Component
Behavior
DDS
Settings
(Structure/
Wiring)
Bind the
Component
Interface
(to data-space)
10. Prototyper (Container)
The RTI Prototyper with Lua
Lua Engine
1. -- Interface: parameters, inputs, outputs
2. local A, B, C = 30, 30, 10 -- Change the 'C' parameter to to see various flower shapes
3. local ShapeWriter = CONTAINER.WRITER[3] -- Triangles
4.
5. -- Global counter (preserved across invocations)
6. if not count then count = 0 else count = count + 1 end
7.
8. local shape = ShapeWriter.instance;
9. local angle = count % 360;
10.
11. shape['x'] = 120 + (A+B) * math.cos(angle) + B * math.cos((A/B-C)*angle)
12. shape['y'] = 120 + (A+B) * math.sin(angle) + B * math.sin((A/B-C)*angle)
13.
14. shape['shapesize'] = 5
15. shape['color'] = "RED"
16.
17. ShapeWriter:write()
Lua Component
Behavior
DDS
Settings
(Structure/
Wiring)
Bind the
Component
Interface
(to data-space)
Prototyper
determines
when the
Lua Component
runs
11. Prototyper (Container)
The RTI Prototyper with Lua
Lua Engine
1. -- Interface: parameters, inputs, outputs
2. local A, B, C = 30, 30, 10 -- Change the 'C' parameter to to see various flower shapes
3. local ShapeWriter = CONTAINER.WRITER[3] -- Triangles
4.
5. -- Global counter (preserved across invocations)
6. if not count then count = 0 else count = count + 1 end
7.
8. local shape = ShapeWriter.instance;
9. local angle = count % 360;
10.
11. shape['x'] = 120 + (A+B) * math.cos(angle) + B * math.cos((A/B-C)*angle)
12. shape['y'] = 120 + (A+B) * math.sin(angle) + B * math.sin((A/B-C)*angle)
13.
14. shape['shapesize'] = 5
15. shape['color'] = "RED"
16.
17. ShapeWriter:write()
Lua Component
Behavior
DDS
Settings
(Structure/
Wiring)
Bind the
Component
Interface
(to data-space)
Prototyper
determines
when the
Lua Component
runs
Lua Component
state preserved
across runs
(code can change!)
12. Prototyper (Container)
The RTI Prototyper with Lua
Lua Engine
1. -- Interface: parameters, inputs, outputs
2. local A, B, C = 30, 30, 10 -- Change the 'C' parameter to to see various flower shapes
3. local ShapeWriter = CONTAINER.WRITER[3] -- Triangles
4.
5. -- Global counter (preserved across invocations)
6. if not count then count = 0 else count = count + 1 end
7.
8. local shape = ShapeWriter.instance;
9. local angle = count % 360;
10.
11. shape['x'] = 120 + (A+B) * math.cos(angle) + B * math.cos((A/B-C)*angle)
12. shape['y'] = 120 + (A+B) * math.sin(angle) + B * math.sin((A/B-C)*angle)
13.
14. shape['shapesize'] = 5
15. shape['color'] = "RED"
16.
17. ShapeWriter:write()
DDS
Settings
(Structure/
Wiring)
RTI
Community
Portal
Download
Lua Component
Behavior
For details, see:
Getting Started
Guide
Bind the
Component
Interface
(to data-space)
13. Dynamically Scriptable (in Lua)
Distributed Components
(using DDS)
Data Distribution Service (DDS)
1. -- Interface: parameters, inputs, outputs
2. local A, B, C = 30, 30, 10 -- Change the 'C' parameter to to see various flower shapes
3. local ShapeWriter = CONTAINER.WRITER[3] -- Triangles
4.
5. -- Global counter (preserved across invocations)
6. if not count then count = 0 else count = count + 1 end
7.
8. local shape = ShapeWriter.instance;
9. local angle = count % 360;
10.
11. shape['x'] = 120 + (A+B) * math.cos(angle) + B * math.cos((A/B-C)*angle)
12. shape['y'] = 120 + (A+B) * math.sin(angle) + B * math.sin((A/B-C)*angle)
13.
14. shape['shapesize'] = 5
15. shape['color'] = "RED"
16.
17. ShapeWriter:write()
1. -- Interface: parameters, inputs, outputs
2. local A, B, C = 30, 30, 10 -- Change the 'C' parameter to to see various flower shapes
3. local ShapeWriter = CONTAINER.WRITER[3] -- Triangles
4.
5. -- Global counter (preserved across invocations)
6. if not count then count = 0 else count = count + 1 end
7.
8. local shape = ShapeWriter.instance;
9. local angle = count % 360;
10.
11. shape['x'] = 120 + (A+B) * math.cos(angle) + B * math.cos((A/B-C)*angle)
12. shape['y'] = 120 + (A+B) * math.sin(angle) + B * math.sin((A/B-C)*angle)
13.
14. shape['shapesize'] = 5
15. shape['color'] = "RED"
16.
17. ShapeWriter:write()
1. -- Interface: parameters, inputs, outputs
2. local A, B, C = 30, 30, 10 -- Change the 'C' parameter to to see various flower shapes
3. local ShapeWriter = CONTAINER.WRITER[3] -- Triangles
4.
5. -- Global counter (preserved across invocations)
6. if not count then count = 0 else count = count + 1 end
7.
8. local shape = ShapeWriter.instance;
9. local angle = count % 360;
10.
11. shape['x'] = 120 + (A+B) * math.cos(angle) + B * math.cos((A/B-C)*angle)
12. shape['y'] = 120 + (A+B) * math.sin(angle) + B * math.sin((A/B-C)*angle)
13.
14. shape['shapesize'] = 5
15. shape['color'] = "RED"
16.
17. ShapeWriter:write()
1. -- Interface: parameters, inputs, outputs
2. local A, B, C = 30, 30, 10 -- Change the 'C' parameter to to see various flower shapes
3. local ShapeWriter = CONTAINER.WRITER[3] -- Triangles
4.
5. -- Global counter (preserved across invocations)
6. if not count then count = 0 else count = count + 1 end
7.
8. local shape = ShapeWriter.instance;
9. local angle = count % 360;
10.
11. shape['x'] = 120 + (A+B) * math.cos(angle) + B * math.cos((A/B-C)*angle)
12. shape['y'] = 120 + (A+B) * math.sin(angle) + B * math.sin((A/B-C)*angle)
13.
14. shape['shapesize'] = 5
15. shape['color'] = "RED"
16.
17. ShapeWriter:write()
17. Transformation - Try it Out Yourself
1. local SIZE_FACTOR = 0.5 -- change the factor to see the size changing
2. local reader = CONTAINER.READER[1] -- input
3. local writer = CONTAINER.WRITER[1] -- output
4.
5. reader:take() -- take all the samples on from the data-space
6.
7. for i, shape in ipairs(reader.sample) do -- iterate through all the samples
8.
9. if (not reader.info[i].valid_data) then break end -- skip invalid content
10.
11. writer.instance['color'] = shape['color']
12. writer.instance['x'] = shape['x']
13. writer.instance['y'] = shape['y']
14. writer.instance['shapesize'] = shape['shapesize'] * SIZE_FACTOR -- transform
15.
16. writer:write() -- output transformed sample
17. end
Data Distribution Service (DDS)
Prototyper:
shapes/ShapePubSub.lua
Subscriber
(Shapes Demo)
Publisher
(Shapes Demo)
18. Transformation - Try it Out Yourself
Dynamic
Live
Code
Update
1. local SIZE_FACTOR = 0.5 -- change the factor to see the size changing
2. local reader = CONTAINER.READER[1] -- input
3. local writer = CONTAINER.WRITER[1] -- output
4.
5. reader:take() -- take all the samples on from the data-space
6.
7. for i, shape in ipairs(reader.sample) do -- iterate through all the samples
8.
9. if (not reader.info[i].valid_data) then break end -- skip invalid content
10.
11. writer.instance['color'] = shape['color']
12. writer.instance['x'] = shape['x']
13. writer.instance['y'] = shape['y']
14. writer.instance['shapesize'] = shape['shapesize'] * SIZE_FACTOR -- transform
15.
16. writer:write() -- output transformed sample
17. end
1. local SIZE_FACTOR = 5 -- change the factor to see the size changing
2. local reader = CONTAINER.READER[1] -- input
3. local writer = CONTAINER.WRITER[1] -- output
4.
5. reader:take() -- take all the samples on from the data-space
6.
7. for i, shape in ipairs(reader.sample) do -- iterate through all the samples
8.
9. if (not reader.info[i].valid_data) then break end -- skip invalid content
10.
11. writer.instance['color'] = shape['color']
12. writer.instance['x'] = shape['x']
13. writer.instance['y'] = shape['y']
14. writer.instance['shapesize'] = shape['shapesize'] * SIZE_FACTOR -- transform
15.
16. writer:write() -- output transformed sample
17. end
before
after
shapes/ShapePubSub.lua
20. -- Interface: parameters, inputs, outputs
local reader1 = CONTAINER.READER[1]
local reader2 = CONTAINER.READER[2]
local writer = CONTAINER.WRITER[#CONTAINER.WRITER]
-- Globals (preserved across invocations)
if not shapesize then shapesize={} end -- shapesize of the output stream
-- Cache the 'shapesize' for a color from the 2nd input stream ---
reader2:take()
for i, shape in ipairs(reader2.sample) do
if (not reader2.info[i].valid_data) then break end
local color = shape['color']
shapesize[color] = shape['x']
end
-- Merge the 'shapesize' for a color with x and y from the 1st input stream ---
reader1:take()
for i, shape in ipairs(reader1.sample) do
if (not reader1.info[i].valid_data) then break end
local color = shape['color’]
writer.instance['color'] = color
writer.instance['x'] = shape['x']
writer.instance['y'] = shape['y']
writer.instance['shapesize'] = shapesize[color] or shape['shapesize']
writer:write()
end
shapes/Correlator.lua
How many lines of C/C++/Java
code would it take?
21. Correlation - Try it Out Yourself
1. local SIZE_FACTOR = 0.5 -- change the factor to see the size changing
2. local reader = CONTAINER.READER[1] -- input
3. local writer = CONTAINER.WRITER[1] -- output
4.
5. reader:take() -- take all the samples on from the data-space
6.
7. for i, shape in ipairs(reader.sample) do -- iterate through all the samples
8.
9. if (not reader.info[i].valid_data) then break end -- skip invalid content
10.
11. writer.instance['color'] = shape['color']
12. writer.instance['x'] = shape['x']
13. writer.instance['y'] = shape['y']
14. writer.instance['shapesize'] = shape['shapesize'] * SIZE_FACTOR -- transform
15.
16. writer:write() -- output transformed sample
17. end
Data Distribution Service (DDS)
Prototyper:
shapes/Correlator.lua
Subscriber
(Shapes Demo)
Publishers
(Shapes Demo)
22. Choreography
xs, ys
ws
xc, yc
wc
xs, ys
xc
Pub-Sub mediation Request-Reply
Pub-Sub
Request-Reply
How many RED objects?
shapes/Choreography.lua
Choreography.xml
28. Examples Included in the Download
Real-Time Processing Category Example
Simulation/Data Generation shapes/Flower.lua
shapes/Figure8.lua
shapes/ShapePublisher.lua
Data Capture shapes/ShapeSubscriber.lua
Transformation shapes/ShapePubSub.lua
Aggregation shapes/Aggregation.lua
Correlation shapes/Correlator.lua
Splitting shapes/SplitterDelayNAverage.lua
Choreography (pattern mediation) shapes/Choreography.lua
Choreography.xml
Device I/O shapes/FileInputAdapter.lua
shapes/mouse/MouseInputAdapter.lua
29. Why should I care?
• Fast Development and Deployment
– No automatic code generation, compile, or re-start
– Be able to try our a variety of ideas quickly and interactively
• Extreme Usability
– Intuitive: don’t reinvent, leverage the language
– Minimalistic: eliminate accidental complexity
– Orthogonal: avoid redundancy, stackable concepts
• Sophisticated Use Cases
– Non-trivial, e.g.:
correlation, splitting, aggregation, transformation, choreography, I/O,
data collection, data generation, etc.
• Separation of Concerns
– Structure vs. Behavior
– Developer vs. Integrator
Do you care
about time to
market?
30. Agenda
• Why is building distributed systems hard?
• The 5 Critical Steps – Best Practice
• The Prototyper – Separating Structure and
Behavior
• Defining structure using XML
• Coding behavior using Lua – A Small Fast Dynamic
Scripting Language
• Real-World Example
• Summary
31. Prototyper (Container)
The RTI Prototyper with Lua
Lua Engine
DDS
Settings
(Structure/
Wiring)
USER_QOS_PROFILES.xml
XML Based
Application
Configuration
RTI
Community
Portal
Download
1. -- Interface: parameters, inputs, outputs
2. local A, B, C = 30, 30, 10 -- Change the 'C' parameter to to see various flower shapes
3. local ShapeWriter = CONTAINER.WRITER[3] -- Triangles
4.
5. -- Global counter (preserved across invocations)
6. if not count then count = 0 else count = count + 1 end
7.
8. local shape = ShapeWriter.instance;
9. local angle = count % 360;
10.
11. shape['x'] = 120 + (A+B) * math.cos(angle) + B * math.cos((A/B-C)*angle)
12. shape['y'] = 120 + (A+B) * math.sin(angle) + B * math.sin((A/B-C)*angle)
13.
14. shape['shapesize'] = 5
15. shape['color'] = "RED"
16.
17. ShapeWriter:write()
Lua Component
Behavior
For details, see:
Getting Started
Guide
Structure
33. Prototyper (Container)
The RTI Prototyper with Lua
Lua Engine
1. -- Interface: parameters, inputs, outputs
2. local A, B, C = 30, 30, 10 -- Change the 'C' parameter to to see various flower shapes
3. local ShapeWriter = CONTAINER.WRITER[3] -- Triangles
4.
5. -- Global counter (preserved across invocations)
6. if not count then count = 0 else count = count + 1 end
7.
8. local shape = ShapeWriter.instance;
9. local angle = count % 360;
10.
11. shape['x'] = 120 + (A+B) * math.cos(angle) + B * math.cos((A/B-C)*angle)
12. shape['y'] = 120 + (A+B) * math.sin(angle) + B * math.sin((A/B-C)*angle)
13.
14. shape['shapesize'] = 5
15. shape['color'] = "RED"
16.
17. ShapeWriter:write()
DDS
Settings
(Structure/
Wiring)
USER_QOS_PROFILES.xml
XML Based
Application
Configuration
RTI
Community
Portal
Download
Lua Component
Behavior
For details, see:
Getting Started
GuideBehavior
34. Why Lua?
• Fast
– One of the fastest popular
scripting languages (from
literature*)
• Very Small (~250KB)
– Can be built for a variety of OSes
or no-OS
• Easy to Learn
• Solid foundation (1993)
– Minimal
– Clean
• Embeddable & Extensible
– Naturally in C
• Growing Community
– Popular in Gaming
– Adopted by Wireshark, Eclipse
M2M, Wikipedia, CoronaSDK, etc.
– Rich Libraries/Ecosystem
• Open-Source! Free!!
35. Where can I learn Lua?
www.lua.org
Don’t worry. It’s easy!
36. Parse XML
configuration files
Create DomainParticipant specified
by the configuration name
Print valid
configuration names
Prompt user for
configuration name
Wait For
Data to arrive OR ‘period’ to elapse
(whichever happens first)
Execute the Lua Code Component
Lua ‘intentExit’? or
Completed ‘runDuration’?
Configuration name
Specified?
NO
YES
NO
YES
Prototyper with
Lua
Runtime Container
Workflow
37. RTI Prototyper with Lua
Runtime Container
• When can the Lua Component run?
– On any one or more of the following events
• on Start
• on Data arrival
• on Period (timer)
• on Stop
– User Configurable, e.g.
• Data (Event) Driven : lua.onPeriod = false
• Timer (Polling) Driven : lua.onData = false
– Default: data + timer driven
1. -- Interface: parameters, inputs, outputs
2. local A, B, C = 30, 30, 10 -- Change the 'C' parameter to to see various flower shapes
3. local ShapeWriter = CONTAINER.WRITER[3] -- Triangles
4.
5. -- Global counter (preserved across invocations)
6. if not count then count = 0 else count = count + 1 end
7.
8. local shape = ShapeWriter.instance;
9. local angle = count % 360;
10.
11. shape['x'] = 120 + (A+B) * math.cos(angle) + B * math.cos((A/B-C)*angle)
12. shape['y'] = 120 + (A+B) * math.sin(angle) + B * math.sin((A/B-C)*angle)
13.
14. shape['shapesize'] = 5
15. shape['color'] = "RED"
16.
17. ShapeWriter:write()
Lua Component
Behavior
38. Lua Component Programming Model
Interface
• Incoming data is consumed using a
READER table
• Outgoing data is produced using a
WRITER table
• Container status and component’s
intents are communicated using a
CONTEXT table
N inputs M outputs
CONTAINER.
READER[1]
CONTAINER.
WRITER[1]
CONTAINER.
READER[N] CONTAINER.
WRITER[M]
-- Lua Component Code --
CONTAINER.CONTEXT
Lua Component Code
• Decides when to read/take incoming data
• Decides when to write outgoing data
• Maintains global state across invocations
• Dynamically Reconfigurable, i.e. code can
be changed while the container is running
39. Writing Data
local foo = 'HelloPublisher::HelloWriter’
-- or --
local foo = 1
local foo_writer = CONTAINER.WRITER[foo]
foo_writer.instance['x'] = 100
foo_writer.instance['y'] = 100
foo_writer.instance['shapesize'] = 30
foo_writer.instance['color'] = "BLUE"
foo_writer:write()
40. Reading Data
local foo = 'HelloPublisher::HelloReader’
-- or --
local foo = 1
local foo_reader = CONTAINER.READER[foo]
foo_reader:take()
for i, shape in ipairs(foo_reader.sample) do
print("t color:", shape['color']) – key
print("t x:", shape['x'])
print("t y:", shape['y'])
print("t shapesize:”, shape['shapesize'])
end
41. Agenda
• Why is building distributed systems hard?
• The 5 Critical Steps – Best Practice
• The Prototyper – Separating Structure and
Behavior
• Defining structure using XML
• Coding behavior using Lua – A Small Fast Dynamic
Scripting Language
• Real-World Example
• Summary
47. Step 1: Draw a diagram of the components and
the interconnecting data-flows
Station
Controller
Production
Lot
Recipe
Recipe
Configurator
To Other
Station
Controllers
From Other
Station
Controllers
Production
Lot
48. Step 1: Draw a diagram of the components and
the interconnecting data-flows
Station
Controller
Production
Lot
Recipe
Recipe
Configurator
Production
Lot
Task
Generator
Production
Lot
To Other
Station
Controllers
From Other
Station
Controllers
49. Step 2: Define the data types for the
interconnecting data flows (in IDL or XML)
Recipe
typedef long StationControlId;
struct RecipeType {
// Uniquely identifies the recipe
string<64> recipeName; //@key
// Defines the sequence of station
// controllers that must be
// traversed to make the product
sequence<StationControlId> steps;
};
<typedef name="StationControlId" type="long" />
<struct name="RecipeType”>
<member name="recipeName" stringMaxLength="64" type="string" key="true" />
<member name="steps" sequenceMaxLength="-1" type="nonBasic"
nonBasicTypeName="StationControlId" />
</struct>
XML
IDL
50. Step 2: Define the data types for the
interconnecting data flows (in IDL or XML)
enum LotStatus {
WAITING_FOR_SC,
PROCESSING_AT_SC,
COMPLETED
};
struct ProductionLotType {
long lotId; //@key
// Identfies the product
string<64> productName;
// Identifies the recipe used
string<64> recipeName;
LotStatus status;
StationControlId assignedSC;
};
Production
LotIDL
51. Step 2: Define the data types for the
interconnecting data flows (in IDL or XML)
<enum name="LotStatus" bitBound="32">
<enumerator name="WAITING_FOR_SC" />
<enumerator name="PROCESSING_AT_SC" />
<enumerator name="COMPLETED" />
</enum>
<struct name="ProductionLotType">
<member name="lotId" type="long" key="true" />
<member name="productName" stringMaxLength="64" type="string" />
<member name="recipeName" stringMaxLength="64" type="string" />
<member name="status" type="nonBasic" nonBasicTypeName="LotStatus" />
<member name="assignedSC" type="nonBasic” nonBasicTypeName="StationControlId" />
</struct>
Production
LotXML
52. Step 3: Define the system structure as a collection of
data-oriented component interfaces (in XML)
<domain_library name="FactoryDomainLib">
<domain name="ChocolateFactory" domain_id="90">
<register_type name="ProductionLotType" kind="dynamicData"
type_ref="FactoryTypes::ProductionLotType"/>
<register_type name="RecipeType" kind="dynamicData"
type_ref="FactoryTypes::RecipeType"/>
<topic register_type_ref="ProductionLotType" name="ProductionLot"/>
<topic register_type_ref="RecipeType" name="Recipe"/>
</domain>
</domain_library>
Production
Lot
Recipe
53. Step 3: Define the system structure as a collection of
data-oriented component interfaces (in XML)
<domain_participant name="RecipeConfigurator"
domain_ref="FactoryDomainLib::ChocolateFactory">
<participant_qos base_name="ChocolateManufacture_Library::ChocolateManufacture_Profile">
<participant_name>
<name>RecipeConfigurator</name>
<role_name>RecipeConfigurator</role_name>
</participant_name>
<property>
<value>
<element>
<name>lua.file</name>
<value>RecipeConfigurator.lua</value>
</element>
<element>
<name>lua.onStart</name>
<value>true</value>
</element>
</value>
</property>
</participant_qos>
<publisher name="RecipePublisher">
<data_writer topic_ref="Recipe" name="RecipeWriter">
<datawriter_qos base_name="ChocolateManufacture_Library::ChocolateManufacture_Profile"/>
</data_writer>
</publisher>
</domain_participant>
Recipe
Recipe
Configurator
54. Step 3: Define the system structure as a collection of
data-oriented component interfaces (in XML)
<participant_library name="FactoryParticipantLib">
<domain_participant name="TaskGenerator"
domain_ref="FactoryDomainLib::ChocolateFactory">
<participant_qos base_name="ChocolateManufacture_Library::ChocolateManufacture_Profile">
<participant_name>
<name>TaskGenerator</name>
<role_name>TaskGenerator</role_name>
</participant_name>
<property>
<value>
<element>
<name>lua.file</name>
<value>TaskGenerator.lua</value>
</element>
<element>
<name>lua.onStart</name>
<value>true</value>
</element>
</value>
</property>
</participant_qos>
<publisher name="TaskPublisher">
<data_writer topic_ref="ProductionLot" name="TaskWriter">
<datawriter_qos base_name="ChocolateManufacture_Library::ChocolateManufacture_Profile"/>
</data_writer>
</publisher>
</domain_participant>
Task
Generator
Production
Lot
55. Step 3: Define the system structure as a collection of
data-oriented component interfaces (in XML)
<domain_participant name="StationController"
domain_ref="FactoryDomainLib::ChocolateFactory">
<participant_qos base_name="ChocolateManufacture_Library::ChocolateManufacture_Profile">
<participant_name>
<name>StationController#$(STATION_CONTROLLER_ID)</name>
<role_name>StationController</role_name>
</participant_name>
<property>
<value>
<element>
<name>lua.file</name>
<value>StationController.lua</value>
</element>
<element>
<name>lua.onStart</name>
<value>true</value>
</element>
</value>
</property>
</participant_qos>
</domain_participant>
Station
Controller
Production
Lot
Production
Lot
Recipe
56. Step 3: Define the system structure as a collection of
data-oriented component interfaces (in XML)
<publisher name="SCPublisher">
<data_writer topic_ref="ProductionLot" name="LotWriter">
<datawriter_qos base_name="ChocolateManufacture_Library::ChocolateManufacture_Profile"/>
</data_writer>
</publisher>
<subscriber name="SCSubscriber">
<data_reader topic_ref="Recipe" name="RecipeReader">
<datareader_qos base_name="ChocolateManufacture_Library::ChocolateManufacture_Profile"/>
</data_reader>
<data_reader topic_ref="ProductionLot" name="LotReader">
<datareader_qos base_name="ChocolateManufacture_Library::ChocolateManufacture_Profile"/>
<filter name="MyLots" kind="builtin.sql">
<expression>assignedSC = $(STATION_CONTROLLER_ID) AND status = 0</expression>
</filter>
</data_reader>
</subscriber>
</domain_participant>
Station
Controller
Production
Lot
Production
Lot
Recipe
57. Step 4: Code the component behavior in the Lua
scripting language
Recipe
Configurator
if ( CONTAINER.CONTEXT.onStartEvent ) then
print("Starting RecipeConfigurator")
ConfigWriter = PROTOTYPER.WRITER["RecipePublisher::RecipeWriter”]
outputRecipe = ConfigWriter.instance
outputRecipe.recipeName = "DarkChocolateRecipe"
local stations = { 1, 2, 3, 4, 6, 7, 8, 9, 11, 12, 13 }
for i, station in ipairs( stations ) do
step = "steps[".. i .."]"
outputRecipe[step] = station
end
ConfigWriter:write()
outputRecipe.recipeName = "WhiteChocolateRecipe"
local stations = { 1, 2, 4, 5, 6, 7, 8, 9, 11, 12, 13 }
for i, station in ipairs( stations ) do
step = "steps[".. i .."]"
outputRecipe[step] = station
end
ConfigWriter:write()
outputRecipe.recipeName = "MilkChocolateRecipe"
local stations = { 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13 }
for i, station in ipairs( stations ) do
step = "steps[".. i .."]"
outputRecipe[step] = station
end
ConfigWriter:write()
end
58. Step 4: Code the component behavior in the Lua
scripting language
if ( CONTAINER.CONTEXT.onStartEvent ) then
print("Starting TaskGenerator”)
TaskWriter = PROTOTYPER.WRITER["TaskPublisher::TaskWriter"]
count = 0
end
local taskLot = TaskWriter.instance
-- We use the count to simulate the continuous generation of tasks
count = count+1
taskLot.lotId = count
taskLot.status = 0
taskLot.assignedSC = 1
if (count <= 1) then
taskLot.productName = "DarkChocolate"
taskLot.recipeName = "DarkChocolateRecipe"
taskLot.assignedSC = 1
elseif (count <= 2) then
taskLot.productName = "WhiteChocolate"
taskLot.recipeName = "WhiteChocolateRecipe"
elseif (count <= 3) then
taskLot.productName = "MilkChocolate"
taskLot.recipeName = "MilkChocolateRecipe"
end
TaskWriter:write()
if ( count > 3 ) then
CONTAINER.CONTEXT.intentExit = true
end
Task
Generator
59. Step 4: Code the component behavior in the Lua
scripting language
-- State initialization to perform the first time the script runs
if ( CONTAINER.CONTEXT.onStartEvent ) then
-- Sentinel values returned by recipeGetNextSCNumber()
NEXT_STATION_COMPLETED=-1
-- Enumerated values that may appear in the Lot.status
LOT_STATUS_WAITING_FOR_SC=0
LOT_STATUS_PROCESSING_AT_SC=1
LOT_STATUS_COMPLETED=2
-- Possible value for the SC's stationState
SC_STATE_READY = 'READY'
SC_STATE_PROCESSING = 'PROCESSING'
-- The number for this station conroller is passed as an
-- environment variable
mySCNumber = tonumber(os.getenv("STATION_CONTROLLER_ID"))
print("Starting SC#" .. mySCNumber)
stationState = SC_STATE_READY
delayCount = 0
-- Queues all the lots that are waiting to be processed by the SC
taskQUEUE = {}
-- Indexed by the recipe name. Stores the next SC# for that recipe
recipeTable = {}
End
-- Helper functions
-- :
Station
Controller
62. Agenda
• Why is building distributed systems hard?
• The 5 Critical Steps – Best Practice
• The Prototyper – Separating Structure and
Behavior
• Defining structure using XML
• Coding behavior using Lua – A Small Fast Dynamic
Scripting Language
• Real-World Example
• Summary
63. Prototyper (Container)
The RTI Prototyper with Lua
Lua Engine
1. -- Interface: parameters, inputs, outputs
2. local A, B, C = 30, 30, 10 -- Change the 'C' parameter to to see various flower shapes
3. local ShapeWriter = CONTAINER.WRITER[3] -- Triangles
4.
5. -- Global counter (preserved across invocations)
6. if not count then count = 0 else count = count + 1 end
7.
8. local shape = ShapeWriter.instance;
9. local angle = count % 360;
10.
11. shape['x'] = 120 + (A+B) * math.cos(angle) + B * math.cos((A/B-C)*angle)
12. shape['y'] = 120 + (A+B) * math.sin(angle) + B * math.sin((A/B-C)*angle)
13.
14. shape['shapesize'] = 5
15. shape['color'] = "RED"
16.
17. ShapeWriter:write()
DDS
Settings
(Structure/
Wiring)
USER_QOS_PROFILES.xml
XML Based
Application
Configuration
RTI
Community
Portal
Download
Lua Component
Behavior
For details, see:
Getting Started
Guide
64. RTI Prototyper with Lua Enables…
• Fast Development & Deployment
– No automatic code generation, compile, or re-start
– Fewer lines of code
– Change behavior (code) on the fly
• Extreme Usability
– Engage domain experts (don’t need to be a middleware expert)
– Natural and intuitive programming model
• Sophisticated Use Cases
– Mediation of communication patterns: pub-sub, request-reply
– Non-trivial, eg:
correlation, splitting, aggregation, transformation, choreography, I/O,
data collection, data generation, etc.
• Separation of Concerns
– Easy to Maintain and Evolve for Large and Small Teams
– Developer focused on processing, not infrastructure configuration
– System integrator can independently manage configuration & QoS
65. The 5 Critical Steps
Articulate Concept
1. Draw a diagram of the components and the interconnecting data-
flows
Define Structure
2. Define the data types for the interconnecting data flows (in IDL or
XML)
3. Define the system structure as a collection of data-oriented
component interfaces (in XML)
Configure Behavior
4. Code the component behavior in the Lua scripting language
5. Adjust QoS policies to achieve the desired data-flow behavior
LATER: Optimize selected components in C/C++/Java/C#,
but only if necessary!
66. Key Benefits
• Get stuff done fast(er)!
• Quickly try out new ideas, and show a working proof
of concept.
• Get more done with the same staff.
• Ease into the learning curve of DDS by getting
something up and running first, and then learn more as
you need to.
• Explore tradeoff between data-model choices.
• Experiment with QoS policies for a given data model.
• Script test scenarios for existing DDS system!
• Test and validate an existing system. Build your own
test harness.
67. Ready to Ride?
• Download it (experimental version):
– community.rti.com Downloads RTI Prototyper with
Lua Pick your flavor (Mac, Linux, Windows, Raspberry
pi)
• Install it:
– Windows: Unzip
– Others: Run the installer:
chmod +x rti_prototyper_with_lua-5-1.0.0-x64Darwin10gcc4.2.1.run
./rti_prototyper_with_lua-5-1.0.0-x64Darwin10gcc4.2.1.run
Choose an existing directory
• Try it:
– Apply the 5 Critical Steps to build your working distributed
system