Angelo Corsaro, profile picture
Uploaded byAngelo Corsaro
PDF, PPTX1,841 views

Getting Started with Vortex

The document discusses the Vortex technology's capabilities for data sharing in industrial IoT, emphasizing its decentralized communication via the DDS global data space. It details how applications can autonomously read and write data while allowing for dynamic discovery and adaptive connectivity, which enhances data sharing efficiency and reduces bottlenecks. Moreover, it covers the various programming languages supported and the security features ensuring secure data transmission across different devices.

Embed presentation

Download as PDF, PPTX
Data Sharing in Industrial IoT Angelo Corsaro, PhD Chief Technology Officer angelo.corsaro@prismtech.com
Vortex is a standard technology for efficient, ubiquitous, interoperable, secure and platform independent data sharing across network connected devices in151 Characters
Vortex's Coordination Model
Applications can autonomously and asynchronously read and write data enjoying spatial and temporal decoupling DDS Global Data Space ... Data Writer Data Writer Data Writer Data Reader Data Reader Data Reader Data Reader Data Writer TopicA QoS TopicB QoS TopicC QoS TopicD QoS Global Data Space
Built-in dynamic discovery isolates applications from network topology and connectivity details DDS Global Data Space ... Data Writer Data Writer Data Writer Data Reader Data Reader Data Reader Data Reader Data Writer TopicA QoS TopicB QoS TopicC QoS TopicD QoS Dynamic Discovery
The relevant portion of the data space is projected on the application address space. Each typed projection is commonly called a Cache No single point of failure or bottleneck Decentralised Data Space Data Writer Data Writer Data Writer Data Reader Data Reader Data Reader Data Writer TopicA QoS TopicB QoS TopicC QoS TopicD QoS TopicD QoS TopicD QoS TopicA QoS
Connectivity is dynamically adapted to chose the most effective way of sharing data Adaptive Connectivity Data Writer Data Writer Data Writer Data Reader Data Reader Data Reader Data Writer TopicA QoS TopicB QoS TopicC QoS TopicD QoS TopicD QoS TopicD QoS TopicA QoS The communication between the DataWriter and matching DataReaders can be peer-to- peer exploiting UDP/IP (Unicast and Multicast)or TCP/IP The communication between the DataWriter and matching DataReaders can be “brokered” but still exploiting UDP/IP (Unicast and Multicast)or TCP/IP
Topic
A domain-wide information’s class A Topic defined by means of a <name, type, qos> Topic DDS Global Data Space ... Data Writer Data Writer Data Writer Data Reader Data Reader Data Reader Data Reader Data Writer TopicA QoS TopicB QoS TopicC QoS TopicD QoS Topic Type Name QoS
Topic Types
Topic Types: Language Independent Definitions
Topic types can be expressed using different syntaxes, including IDL and ProtoBuf Topic Type struct CarDynamics { string cid; long x; long y; float dx; long dy; } #pragma keylist CarDynamics cid IDL
Topic types can be expressed using different syntaxes, including IDL and ProtoBuf Topic Type message CarDynamics { option (.omg.dds.type) = {name: "CarDynamics"}; required string cid = 0 [(.omg.dds.member).key = true]; required long x = 1; required long y = 2; required float dx = 3; required long dy = 4; } ProtoBuf
Topic Types: Language Specific Definitions
Topic types can be expressed using different syntaxes, including IDL and ProtoBuf Topic Type class CarDynamics: constructor: (@cid, @x, @y, @dx, @dy) -> CoffeeScript
Topic types can be expressed using different syntaxes, including IDL and ProtoBuf Topic Type public struct CaDynamics {
 public string cid { get; set; }
 public int x { get; set; }
 public int y { get; set; }
 public int dx { get; set; }
 public int dy { get; set; }
 
 public CaDynamics (string cid, int x, int y, int dx, int dy)
 {
 this.cid = cid;
 this.x = x; this.y = y;
 this.dx = dx; this.dy = dy;
 }
 }
 C#
Topic types can be expressed using different syntaxes, including IDL and ProtoBuf Topic Type @KeyList ( topicType = "CarDynamics", keys = {"cid"})
 public class CarDynamics {
 public String cid;
 public int x; public int dx;
 public int y; public int dy;
 
 public CarDynamics(String s, int a, int b, int c,int d) {
 this.cid = s;
 this.x = a; this.dx = b;
 this.y = c; this.dy = d;
 }
 
 @Override
 public String toString() { …
 }
 
 }
 Java
Topics, Instances and Samples
CopyrightPrismTech,2015 Each unique key value identifies a stream of data Vortex demultiplexes “streams” and provides lifecycle information A DataWriter can write samples belonging to multiple instances Topic Instances CarDynamics Instances struct CarDynamics { @key string cid; long x; long y; float dx; long dy; } Topic Topic Type Sample
QoS policies allow to express temporal and availability constraints for data DDS Global Data Space ... Data Writer Data Writer Data Writer Data Reader Data Reader Data Reader Data Reader Data Writer TopicA QoS TopicB QoS TopicC QoS TopicD QoS QoS - Enabled
A collection of policies that control non- functional properties such as reliability, persistence, temporal constraints and priority QoS HISTORY LIFESPAN DURABILITY DEADLINE LATENCY BUDGET TRANSPORT PRIO TIME-BASED FILTER RESOURCE LIMITS USER DATA TOPIC DATA GROUP DATA OWENERSHIP OWN. STRENGTH LIVELINESS ENTITY FACTORY DW LIFECYCLE DR LIFECYCLE PRESENTATION RELIABILITY PARTITION DEST. ORDER RxO QoS Local QoS
QoS Policies controlling end-to-end properties follow a Request vs. Offered QoS Domain Participant DURABILITY OWENERSHIP DEADLINE LATENCY BUDGET LIVELINESS RELIABILITY DEST. ORDER Publisher DataWriter PARTITION DataReader Subscriber Domain Participant offered QoS Topic writes reads Domain Id joins joins produces-in consumes-from RxO QoS Policies requested QoS
Interacting with the Data Cache
Each Data Reader is associated with a Cache The Cache stores the last n∊𝜨∞ samples for each relevant instance Data Cache Data Writer Data Writer Data Writer Data Reader Data Reader Data Reader Data Writer TopicA QoS TopicB QoS TopicC QoS TopicD QoS TopicD QoS TopicD QoS TopicA QoS
Each Data Reader is associated with a Cache The Cache stores the last n∊𝜨∞ samples for each relevant instance Data Cache DataReader Cache DataReader ... Samples Instances Cache
The action of reading samples for a Reader Cache is non-destructive. Samples are not removed from the cache Reading Data DataReader Cache DataReader ... DataReader Cache DataReader ...read
The action of taking samples for a Reader Cache is destructive. Samples are removed from the cache Taking Data DataReader Cache DataReader ... DataReader Cache DataReader ...take
Samples can be selected using composable content and status predicates Sample Selectors DataReader Cache DataReader ...
Filters allow to control what gets into a DataReader cache Filters are expressed as SQL where clauses or as Java/C/JavaScript predicates Content-Filtering DataReader Cache DataReader ... Filter Application Network
Content Filters can be used to project on the local cache only the Topic data satisfying a given predicate Content Filters struct CarDynamics { @key string cid; long x; long y; float dx; long dy; } cid x y dx dy GR 33N GO 167 240 45 0 LO 00V IN 65 26 65 0 AN 637 OS 32 853 0 50 AB 123 CD 325 235 80 0 “dx > 50 OR dy > 50” Type CarDynamics cid x y dx dy LO 00V IN 65 26 65 0 AB 123 CD 325 235 80 0 Reader Cache
Queries allow to control what gets out of a DataReader Cache Queries are expressed as SQL where clauses or as Java/C/JavaScript predicates Content-Based Selection DataReader Cache DataReader ... Query DataReader Cache DataReader ... Application Network
Reader Cache Queries can be used to select out of the local cache the data matching a given predicate Queries struct CarDynamics { @key string cid; long x; long y; float dx; long dy; } cid x y dx dy GR 33N GO 167 240 45 0 LO 00V IN 65 26 65 0 AN 637 OS 32 853 0 50 AB 123 CD 325 235 80 0 “dx > 50 OR dy > 50” Type CarDynamics cid x y dx dy GR 33N GO 167 240 45 0 LO 00V IN 65 26 65 0 AN 637 OS 32 853 0 50 AB 123 CD 325 235 80 0 cid x y dx dy LO 00V IN 65 26 65 0 AB 123 CD 325 235 80 0 query
State based selection allows to control what gets out of a DataReader Cache State base selectors predicate on samples meta- information State-Based Selection DataReader Cache DataReader ... State Selector DataReader Cache DataReader ... Application Network
Sample State (READ, NOT_READ) allows to distinguish between new samples and samples that have already been read State-Based Selection DataReader Cache DataReader ... State Selector DataReader Cache DataReader ... Application Network
The View State (NEW, NOT_NEW) allows to distinguish a new instance from an existing one State-Based Selection DataReader Cache DataReader ... State Selector DataReader Cache DataReader ... Application Network
The Instance State (ALIVE, NOT_ALIVE_DISPOSED, NOT_ALIVE_NO_WRITERS) allows to track the life-cycle transitions of the instance to which a sample belongs State-Based Selection DataReader Cache DataReader ... State Selector DataReader Cache DataReader ... Application Network
Selector Example // == ISO C++ DDS API == auto data = dr.select() .content(query) .state(data_state) .instance(handle) .read();
your first vortex app
CopyrightPrismTech,2014 Anatomy of a DDS Application
CopyrightPrismTech,2015 Writing Data in C++ #include <dds.hpp> int main(int, char**) { DomainParticipant dp(0); Topic<Meter> topic(“SmartMeter”); auto pqos = dp.get_default_pubqos() << Partition (“FR:IdF:Essonne:Gif:Essonne:Mnts:123”); Publisher pub(dp, pqos); DataWriter<Meter> dw(pub, topic); while (!done) { auto value = readMeter() dw.write(value); std::this_thread::sleep_for(SAMPLING_PERIOD); } return 0; } enum UtilityKind { ELECTRICITY, GAS, WATER }; struct Meter { string sn; UtilityKind utility; float reading; float error; }; #pragma keylist Meter sn
CopyrightPrismTech,2015 Reading Data in C++ #include <dds.hpp> int main(int, char**) { DomainParticipant dp(0); Topic<Meter> topic(”SmartMeter”); Subscriber sub(dp); DataReader<Meter> dr(dp, topic); LambdaDataReaderListener<DataReader<Meter>> lst; lst.data_available = [](DataReader<Meter>& dr) { auto samples = data.read(); std::for_each(samples.begin(), samples.end(), [](Sample<Meter>& sample) { std::cout << sample.data() << std::endl; } } dr.listener(lst); // Print incoming data up to when the user does a Ctrl-C std::this_thread::join(); return 0; } enum UtilityKind { ELECTRICITY, GAS, WATER }; struct Meter { string sn; UtilityKind utility; float reading; float error; }; #pragma keylist Meter sn
CopyrightPrismTech,2014 Writing Data in Scala import dds._
 import dds.prelude._
 import dds.config.DefaultEntities._
 object SmartMeter {
 
 def main(args: Array[String]): Unit = {
 val topic = Topic[Meter](“SmartMeter”)
 val dw = DataWriter[Meter](topic) while (!done) { val meter = readMeter()
 dw.write(meter) Thread.sleep(SAMPLING_PERIOD) }
 }
 } enum UtilityKind { ELECTRICITY, GAS, WATER }; struct Meter { string sn; UtilityKind utility; float reading; float error; }; #pragma keylist Meter sn
CopyrightPrismTech,2014 Reading Data in Scala import dds._
 import dds.prelude._
 import dds.config.DefaultEntities._
 object SmartMeterLog {
 def main(args: Array[String]): Unit = {
 val topic = Topic[Meter](“SmartMeter”)
 val dr = DataReader[Meter](topic)
 dr listen {
 case DataAvailable(_) => dr.read.foreach(println)
 }
 }
 } enum UtilityKind { ELECTRICITY, GAS, WATER }; struct Meter { string sn; UtilityKind utility; float reading; float error; }; #pragma keylist Meter sn
CopyrightPrismTech,2015 Writing Data in Python import dds import time
 
 if __name__ == '__main__':
 topic = dds.Topic("SmartMeter", "Meter")
 dw = dds.Writer(topic)
 
 while True:
 m = readMeter()
 dw.write(m)
 time.sleep(0.1) enum UtilityKind { ELECTRICITY, GAS, WATER }; struct Meter { string sn; UtilityKind utility; float reading; float error; }; #pragma keylist Meter sn
CopyrightPrismTech,2015 Reading Data in Python import dds
 import sys
 
 def readData(dr): 
 samples = dds.range(dr.read())
 for s in samples:
 sys.stdout.write(str(s.getData()))
 
 if __name__ == '__main__':
 t = dds.Topic("SmartMeter", "Meter")
 dr = dds.Reader(t)
 dr.onDataAvailable = readData enum UtilityKind { ELECTRICITY, GAS, WATER }; struct Meter { string sn; UtilityKind utility; float reading; float error; }; #pragma keylist Meter sn
Vortex Technology Stack
Device implementations optimised for OT, IT and consumer platforms Native support for Cloud and Fog Computing Architectures Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
Available across IT, Consumer and OT platforms Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
Polyglot and Interoperable across Programming Languages Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
Fully Independent of the Cloud Infrastructure Private Clouds Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
Native Integration with the hottest real-time analytics platforms and CEP Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
Integration with mainstream Dashboard Technologies Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
High Performance 30 μs peer-to-peer latency 4+ Mmsgs/sec p2p throughput Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
>10 μs fog/cloud routing latency High Performance Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
Secure Data-Level security with Pluggable Authentication Access Control and Crypto Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
Default Plug-ins X.509 Public Key Infrastructure (PKI) based authentication Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
Default Plug-ins Access Control List file signed by a shared Certificate Authority for Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
Default Plug-ins Crypto based on TLS Cipher Suite Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
Secure Data-Security as opposed to simply Transport-Level security Arthur Dent Arthur Dent Ford Prefect Zaphod Beeblebrox Marvin Trillian left/A(r,w), left/B(r) left/A(r,w), left/B(r,w), left/X(r) left/*(r,w) left/*(r), right/(w) left/A(r,w), left/B(r,w), right/C(r,w) Ford Prefect Zaphod Beeblebrox Trillian Marvin A B A,B X * * A,B,C Identity Access Rights Sessions are authenticated and communication is encrypted Only the Topic included as part of the access rights are visible and accessible
Secure Fine-grained access control over Partition/Topic/ Instance regular expressions Arthur Dent Arthur Dent Ford Prefect Zaphod Beeblebrox Marvin Trillian left/A(r,w), left/B(r) left/A(r,w), left/B(r,w), left/X(r) left/*(r,w) left/*(r), right/(w) left/A(r,w), left/B(r,w), right/C(r,w) Ford Prefect Zaphod Beeblebrox Trillian Marvin A B A,B X * * A,B,C Identity Access Rights Sessions are authenticated and communication is encrypted Only the Topic included as part of the access rights are visible and accessible
Secure Support for Symmetric and Asymmetric Authentication Arthur Dent Arthur Dent Ford Prefect Zaphod Beeblebrox Marvin Trillian left/A(r,w), left/B(r) left/A(r,w), left/B(r,w), left/X(r) left/*(r,w) left/*(r), right/(w) left/A(r,w), left/B(r,w), right/C(r,w) Ford Prefect Zaphod Beeblebrox Trillian Marvin A B A,B X * * A,B,C Identity Access Rights Sessions are authenticated and communication is encrypted Only the Topic included as part of the access rights are visible and accessible
Boundary Security Boundary security support is enabled by Vortex-Fog Device-to-Cloud Communication Peer-to-Peer (Broker-less) Device-to-Device Communication Fog Computing Fog Computing Fog Computing TLS TLS
Boundary Security Separates security concerns at different scales and controls what information is exposed Device-to-Cloud Communication Peer-to-Peer (Broker-less) Device-to-Device Communication Fog Computing Fog Computing Fog Computing TLS TLS
Typical Deployment
Vortex device, such as Lite, Café, and Web are used to share data between different kinds of applications within a car Café and Web are typically used Android / HTML5 based infotainment Lite in typically used in ECU, sensors and onboard analytics
Vortex Fog is used to transparently (for in car apps) decouple and control the data sharing within and across the car Vortex Fog also helps defining security boundaries and policies
Vortex Fog efficiently and securely deals with car to car communication Vortex Fog allows to decouple the transport used for in-car communication and that used for car-to-car communication
Vortex Fog efficiently and securely deals with cloud connectivity adapting traffic flows and protocols Device-to-Cloud Communication Cloud Analytics Fog Analytics Fog Analytics Fog Analytics Vortex Cloud efficiently and securely makes data available to any device at an Internet Scale
Vortex Cloud efficiently and securely makes data available to any device at an Internet Scale Device-to-Cloud Communication Cloud Analytics Fog Analytics Fog Analytics Fog Analytics
Use Cases
CopyrightPrismTech,2015 Connected Boulevard — Nice, France Vortex enables is the data sharing platform for the City Operating System Tens of thousands of devices connected by Vortex
Autonomous Vehicles coordination of fast moving autonomous vehicles intermittent connectivity dynamic pairing of devices
CopyrightPrismTech,2014 Smart Factory 0.5 TB of data produced per day
CopyrightPrismTech,2014 Smart-Grid 20ms deadline for phase alignment data
ESA Extremely Large & SMART Telescope (ELT) 1750 computing nodes 100.000 mirrors whose position is adjusted 100 times per second! ELT will allow astronomers to probe the earliest stages of the formation of planetary systems and to detect water and organic molecules in proto- planetary discs around stars in the making
Launch System 80K+ data points with aggregate updates rate of ~400K msgs/sec
Connected Aircrafts 10 TB of data every 30m of flight
Oil Rig 30000 data points only 1% of available data used today
Smart Lightbulbs 96Kbytes Memory Connected Medical Devices 12 msec period for pleath data Peer-to-Peer connectivity
Vortex enables Smart, Secure and Efficient Data Sharing in IoT In Summary
CopyrightPrismTech,2015

More Related Content

PDF
DDS and OPC UA Explained
byAngelo Corsaro
 
PDF
Introducing Vortex Lite
byAngelo Corsaro
 
PDF
IoT Protocols Integration with Vortex Gateway
byAngelo Corsaro
 
PDF
Vortex: The Intelligent Data Sharing Platform for the Internet of Things
byAngelo Corsaro
 
PDF
Micro services Architecture with Vortex -- Part I
byAngelo Corsaro
 
PDF
Architecting IoT Systems with Vortex
byAngelo Corsaro
 
PDF
DDS In Action Part II
byAngelo Corsaro
 
PDF
The DDS Security Standard
byAngelo Corsaro
 
DDS and OPC UA Explained
byAngelo Corsaro
 
Introducing Vortex Lite
byAngelo Corsaro
 
IoT Protocols Integration with Vortex Gateway
byAngelo Corsaro
 
Vortex: The Intelligent Data Sharing Platform for the Internet of Things
byAngelo Corsaro
 
Micro services Architecture with Vortex -- Part I
byAngelo Corsaro
 
Architecting IoT Systems with Vortex
byAngelo Corsaro
 
DDS In Action Part II
byAngelo Corsaro
 
The DDS Security Standard
byAngelo Corsaro
 

What's hot

PDF
Desktop, Embedded and Mobile Apps with Vortex Café
byAngelo Corsaro
 
PDF
DDS: The IoT Data Sharing Standard
byAngelo Corsaro
 
PDF
Vortex Tutorial -- Part I
byAngelo Corsaro
 
PDF
Building IoT Applications with Vortex and the Intel Edison Starter Kit
byAngelo Corsaro
 
PDF
Distributed Algorithms with DDS
byAngelo Corsaro
 
PDF
Vortex Tutorial Part 2
byADLINK Technology IoT
 
PDF
DDS Tutorial -- Part I
byAngelo Corsaro
 
PDF
The DDS Tutorial Part II
byAngelo Corsaro
 
PDF
Data Sharing in Extremely Resource Constrained Envionrments
byAngelo Corsaro
 
PDF
Building Reactive Applications with DDS
byAngelo Corsaro
 
PDF
Getting Started in DDS with C++ and Java
byAngelo Corsaro
 
PDF
The Data Distribution Service Tutorial
byAngelo Corsaro
 
PDF
The DDS Tutorial - Part I
byAngelo Corsaro
 
PDF
Connected Mobile and Web Applications with Vortex
byAngelo Corsaro
 
PDF
Reactive Data Centric Architectures with Vortex, Spark and ReactiveX
byAngelo Corsaro
 
PDF
Advanced OpenSplice Programming - Part II
byAngelo Corsaro
 
PDF
The Data Distribution Service Tutorial
byAngelo Corsaro
 
PDF
Building and Scaling Internet of Things Applications with Vortex Cloud
byAngelo Corsaro
 
PDF
OMG DDS: The Data Distribution Service for Real-Time Systems
byAngelo Corsaro
 
PDF
OpenSplice DDS Tutorial -- Part II
byAngelo Corsaro
 
Desktop, Embedded and Mobile Apps with Vortex Café
byAngelo Corsaro
 
DDS: The IoT Data Sharing Standard
byAngelo Corsaro
 
Vortex Tutorial -- Part I
byAngelo Corsaro
 
Building IoT Applications with Vortex and the Intel Edison Starter Kit
byAngelo Corsaro
 
Distributed Algorithms with DDS
byAngelo Corsaro
 
Vortex Tutorial Part 2
byADLINK Technology IoT
 
DDS Tutorial -- Part I
byAngelo Corsaro
 
The DDS Tutorial Part II
byAngelo Corsaro
 
Data Sharing in Extremely Resource Constrained Envionrments
byAngelo Corsaro
 
Building Reactive Applications with DDS
byAngelo Corsaro
 
Getting Started in DDS with C++ and Java
byAngelo Corsaro
 
The Data Distribution Service Tutorial
byAngelo Corsaro
 
The DDS Tutorial - Part I
byAngelo Corsaro
 
Connected Mobile and Web Applications with Vortex
byAngelo Corsaro
 
Reactive Data Centric Architectures with Vortex, Spark and ReactiveX
byAngelo Corsaro
 
Advanced OpenSplice Programming - Part II
byAngelo Corsaro
 
The Data Distribution Service Tutorial
byAngelo Corsaro
 
Building and Scaling Internet of Things Applications with Vortex Cloud
byAngelo Corsaro
 
OMG DDS: The Data Distribution Service for Real-Time Systems
byAngelo Corsaro
 
OpenSplice DDS Tutorial -- Part II
byAngelo Corsaro
 

Similar to Getting Started with Vortex

PDF
Reactive Data Centric Architectures with DDS
byAngelo Corsaro
 
PDF
PrismTech Vortex Tutorial Part 1
byADLINK Technology IoT
 
PDF
Connected Mobile and Web Applications with PrismTech Vortex Data Sharing Plat...
byADLINK Technology IoT
 
PDF
Cyclone DDS: Sharing Data in the IoT Age
byAngelo Corsaro
 
PDF
ModeShape 3 overview
byRandall Hauch
 
PPTX
PROf TEJAS PADGHAN ICEEM ch. sambhajinagar
bytejaspadghan2
 
PDF
Open splicedds espercep-webinar
byTomasz Waszczyk
 
PDF
ME4AWSN - a Modeling Environment for Architecting WSNs
byIvano Malavolta
 
PPT
Big Data & NoSQL - EFS'11 (Pavlo Baron)
byPavlo Baron
 
PPT
Key Challenges in Cloud Computing and How Yahoo! is Approaching Them
byYahoo Developer Network
 
PDF
DATA MANAGEMENT ISSUES AND STUDY ON HETEROGENEOUS DATA STORAGE IN THE INTERNE...
byCSEIJJournal
 
PDF
Data Management Issues and Study on Heterogeneous Data Storage in the Interne...
byCSEIJJournal
 
PDF
Dynamo and NoSQL Databases
byAmir Payberah
 
PPTX
Our way to microservices
byAndi Pangeran
 
PDF
Standardizing the Data Distribution Service (DDS) API for Modern C++
bySumant Tambe
 
PDF
Cqrs
byKnoldus Inc.
 
PDF
Large Infrastructure Monitoring At CERN by Matthias Braeger at Big Data Spain...
byBig Data Spain
 
PDF
Stream Processing with DDS and CEP
byAngelo Corsaro
 
PDF
Modern Software Architectures - Overview
byCodeOps Technologies LLP
 
PDF
Introducing Vortex Lite
byADLINK Technology IoT
 
Reactive Data Centric Architectures with DDS
byAngelo Corsaro
 
PrismTech Vortex Tutorial Part 1
byADLINK Technology IoT
 
Connected Mobile and Web Applications with PrismTech Vortex Data Sharing Plat...
byADLINK Technology IoT
 
Cyclone DDS: Sharing Data in the IoT Age
byAngelo Corsaro
 
ModeShape 3 overview
byRandall Hauch
 
PROf TEJAS PADGHAN ICEEM ch. sambhajinagar
bytejaspadghan2
 
Open splicedds espercep-webinar
byTomasz Waszczyk
 
ME4AWSN - a Modeling Environment for Architecting WSNs
byIvano Malavolta
 
Big Data & NoSQL - EFS'11 (Pavlo Baron)
byPavlo Baron
 
Key Challenges in Cloud Computing and How Yahoo! is Approaching Them
byYahoo Developer Network
 
DATA MANAGEMENT ISSUES AND STUDY ON HETEROGENEOUS DATA STORAGE IN THE INTERNE...
byCSEIJJournal
 
Data Management Issues and Study on Heterogeneous Data Storage in the Interne...
byCSEIJJournal
 
Dynamo and NoSQL Databases
byAmir Payberah
 
Our way to microservices
byAndi Pangeran
 
Standardizing the Data Distribution Service (DDS) API for Modern C++
bySumant Tambe
 
Cqrs
byKnoldus Inc.
 
Large Infrastructure Monitoring At CERN by Matthias Braeger at Big Data Spain...
byBig Data Spain
 
Stream Processing with DDS and CEP
byAngelo Corsaro
 
Modern Software Architectures - Overview
byCodeOps Technologies LLP
 
Introducing Vortex Lite
byADLINK Technology IoT
 

More from Angelo Corsaro

PDF
Zenoh: The Genesis
byAngelo Corsaro
 
PDF
zenoh: The Edge Data Fabric
byAngelo Corsaro
 
PDF
Zenoh Tutorial
byAngelo Corsaro
 
PDF
Data Decentralisation: Efficiency, Privacy and Fair Monetisation
byAngelo Corsaro
 
PDF
zenoh: zero overhead pub/sub store/query compute
byAngelo Corsaro
 
PDF
zenoh -- the ZEro Network OverHead protocol
byAngelo Corsaro
 
PDF
zenoh -- the ZEro Network OverHead protocol
byAngelo Corsaro
 
PDF
Breaking the Edge -- A Journey Through Cloud, Edge and Fog Computing
byAngelo Corsaro
 
PDF
Eastern Sicily
byAngelo Corsaro
 
PDF
fog05: The Fog Computing Infrastructure
byAngelo Corsaro
 
PDF
fog05: The Fog Computing Platform
byAngelo Corsaro
 
PDF
Programming in Scala - Lecture Four
byAngelo Corsaro
 
PDF
Programming in Scala - Lecture Three
byAngelo Corsaro
 
PDF
Programming in Scala - Lecture Two
byAngelo Corsaro
 
PDF
Programming in Scala - Lecture One
byAngelo Corsaro
 
PDF
The Data Distribution Service
byAngelo Corsaro
 
PDF
RUSTing -- Partially Ordered Rust Programming Ruminations
byAngelo Corsaro
 
PDF
Vortex II -- The Industrial IoT Connectivity Standard
byAngelo Corsaro
 
PDF
Fog Computing Defined
byAngelo Corsaro
 
PDF
DDS in Action -- Part I
byAngelo Corsaro
 
Zenoh: The Genesis
byAngelo Corsaro
 
zenoh: The Edge Data Fabric
byAngelo Corsaro
 
Zenoh Tutorial
byAngelo Corsaro
 
Data Decentralisation: Efficiency, Privacy and Fair Monetisation
byAngelo Corsaro
 
zenoh: zero overhead pub/sub store/query compute
byAngelo Corsaro
 
zenoh -- the ZEro Network OverHead protocol
byAngelo Corsaro
 
zenoh -- the ZEro Network OverHead protocol
byAngelo Corsaro
 
Breaking the Edge -- A Journey Through Cloud, Edge and Fog Computing
byAngelo Corsaro
 
Eastern Sicily
byAngelo Corsaro
 
fog05: The Fog Computing Infrastructure
byAngelo Corsaro
 
fog05: The Fog Computing Platform
byAngelo Corsaro
 
Programming in Scala - Lecture Four
byAngelo Corsaro
 
Programming in Scala - Lecture Three
byAngelo Corsaro
 
Programming in Scala - Lecture Two
byAngelo Corsaro
 
Programming in Scala - Lecture One
byAngelo Corsaro
 
The Data Distribution Service
byAngelo Corsaro
 
RUSTing -- Partially Ordered Rust Programming Ruminations
byAngelo Corsaro
 
Vortex II -- The Industrial IoT Connectivity Standard
byAngelo Corsaro
 
Fog Computing Defined
byAngelo Corsaro
 
DDS in Action -- Part I
byAngelo Corsaro
 

Recently uploaded

PDF
Chapter 4 Network Security in computer security
byGetnet Tigabie Askale -(GM)
 
PDF
Startup Formation Collapses While Acquisition Activity Hits New High!
byMemoori
 
PPTX
TechSprint (SJBIT) 2025-26 Hackathon Winners & Awards Ceremony
bysuhasspgdg
 
PPTX
Retrieval Augmented Generation- The Synergistic Power of Prompt Engineering
bySemantic SEO BD
 
PDF
Advanced SELinux Management - RHCSA (RH134).pdf
byLinuxCert Guru
 
PDF
Getting Started with Apache Spark: Big Data Made Simple [Free Meetup]
byHaim Michael
 
PDF
Safer’s Picks: The 5 FME Transformers You Didn’t Know You Needed
bySafe Software
 
PDF
Post Quantum Cryptography for Dummies.pdf
byAde Ismail Isnan
 
PDF
What Is the Azure AI Foundry and Why Does It Matter for Enterprises?
byjohncarterjn
 
PPTX
Beyond the Algorithm: Designing Human-Centric Public Service with AI
byAlan Dix
 
PDF
UiPath Automation Developer Associate Training Series 2026 - Session 1
byDianaGray10
 
PDF
Supercharge Your Copilot-Driven Collaboration with Microsoft 365 Agents SDK
byAntti Koskela
 
PDF
Mesh WiFi Router: The Smart Solution for Fast, Seamless, Whole-Home Internet
byAeroMesh Systems
 
PDF
Writing GPU-Ready AI Models in Pure Java with Babylon
byAna-Maria Mihalceanu
 
PDF
The Enterprise Web3 Landscape - a view from Kaleido based on the past 10 year...
byPeter Broadhurst
 
PDF
Designing a Blog Using Wordpress
bymarkzubi50
 
PDF
Analyze and Preserve Logs - RHCSA (RH134).pdf
byLinuxCert Guru
 
PDF
AI and Zero Trust: What it takes to do it right
byMark Simos
 
PDF
Configure and Manage Systemd Timers- RHCSA (RH134).pdf
byLinuxCert Guru
 
PDF
CI CD Observability, Metrics and DORA - Shifting Left and Cleaning Up! - Febr...
byPeter Souter
 
Chapter 4 Network Security in computer security
byGetnet Tigabie Askale -(GM)
 
Startup Formation Collapses While Acquisition Activity Hits New High!
byMemoori
 
TechSprint (SJBIT) 2025-26 Hackathon Winners & Awards Ceremony
bysuhasspgdg
 
Retrieval Augmented Generation- The Synergistic Power of Prompt Engineering
bySemantic SEO BD
 
Advanced SELinux Management - RHCSA (RH134).pdf
byLinuxCert Guru
 
Getting Started with Apache Spark: Big Data Made Simple [Free Meetup]
byHaim Michael
 
Safer’s Picks: The 5 FME Transformers You Didn’t Know You Needed
bySafe Software
 
Post Quantum Cryptography for Dummies.pdf
byAde Ismail Isnan
 
What Is the Azure AI Foundry and Why Does It Matter for Enterprises?
byjohncarterjn
 
Beyond the Algorithm: Designing Human-Centric Public Service with AI
byAlan Dix
 
UiPath Automation Developer Associate Training Series 2026 - Session 1
byDianaGray10
 
Supercharge Your Copilot-Driven Collaboration with Microsoft 365 Agents SDK
byAntti Koskela
 
Mesh WiFi Router: The Smart Solution for Fast, Seamless, Whole-Home Internet
byAeroMesh Systems
 
Writing GPU-Ready AI Models in Pure Java with Babylon
byAna-Maria Mihalceanu
 
The Enterprise Web3 Landscape - a view from Kaleido based on the past 10 year...
byPeter Broadhurst
 
Designing a Blog Using Wordpress
bymarkzubi50
 
Analyze and Preserve Logs - RHCSA (RH134).pdf
byLinuxCert Guru
 
AI and Zero Trust: What it takes to do it right
byMark Simos
 
Configure and Manage Systemd Timers- RHCSA (RH134).pdf
byLinuxCert Guru
 
CI CD Observability, Metrics and DORA - Shifting Left and Cleaning Up! - Febr...
byPeter Souter
 

Getting Started with Vortex

  • 1.
    Data Sharing inIndustrial IoT Angelo Corsaro, PhD Chief Technology Officer angelo.corsaro@prismtech.com
  • 2.
    Vortex is astandard technology for efficient, ubiquitous, interoperable, secure and platform independent data sharing across network connected devices in151 Characters
  • 3.
  • 4.
    Applications can autonomously andasynchronously read and write data enjoying spatial and temporal decoupling DDS Global Data Space ... Data Writer Data Writer Data Writer Data Reader Data Reader Data Reader Data Reader Data Writer TopicA QoS TopicB QoS TopicC QoS TopicD QoS Global Data Space
  • 5.
    Built-in dynamic discovery isolatesapplications from network topology and connectivity details DDS Global Data Space ... Data Writer Data Writer Data Writer Data Reader Data Reader Data Reader Data Reader Data Writer TopicA QoS TopicB QoS TopicC QoS TopicD QoS Dynamic Discovery
  • 6.
    The relevant portionof the data space is projected on the application address space. Each typed projection is commonly called a Cache No single point of failure or bottleneck Decentralised Data Space Data Writer Data Writer Data Writer Data Reader Data Reader Data Reader Data Writer TopicA QoS TopicB QoS TopicC QoS TopicD QoS TopicD QoS TopicD QoS TopicA QoS
  • 7.
    Connectivity is dynamically adaptedto chose the most effective way of sharing data Adaptive Connectivity Data Writer Data Writer Data Writer Data Reader Data Reader Data Reader Data Writer TopicA QoS TopicB QoS TopicC QoS TopicD QoS TopicD QoS TopicD QoS TopicA QoS The communication between the DataWriter and matching DataReaders can be peer-to- peer exploiting UDP/IP (Unicast and Multicast)or TCP/IP The communication between the DataWriter and matching DataReaders can be “brokered” but still exploiting UDP/IP (Unicast and Multicast)or TCP/IP
  • 8.
  • 9.
    A domain-wide information’s classA Topic defined by means of a <name, type, qos> Topic DDS Global Data Space ... Data Writer Data Writer Data Writer Data Reader Data Reader Data Reader Data Reader Data Writer TopicA QoS TopicB QoS TopicC QoS TopicD QoS Topic Type Name QoS
  • 10.
  • 11.
  • 12.
    Topic types canbe expressed using different syntaxes, including IDL and ProtoBuf Topic Type struct CarDynamics { string cid; long x; long y; float dx; long dy; } #pragma keylist CarDynamics cid IDL
  • 13.
    Topic types canbe expressed using different syntaxes, including IDL and ProtoBuf Topic Type message CarDynamics { option (.omg.dds.type) = {name: "CarDynamics"}; required string cid = 0 [(.omg.dds.member).key = true]; required long x = 1; required long y = 2; required float dx = 3; required long dy = 4; } ProtoBuf
  • 14.
  • 15.
    Topic types canbe expressed using different syntaxes, including IDL and ProtoBuf Topic Type class CarDynamics: constructor: (@cid, @x, @y, @dx, @dy) -> CoffeeScript
  • 16.
    Topic types canbe expressed using different syntaxes, including IDL and ProtoBuf Topic Type public struct CaDynamics {
 public string cid { get; set; }
 public int x { get; set; }
 public int y { get; set; }
 public int dx { get; set; }
 public int dy { get; set; }
 
 public CaDynamics (string cid, int x, int y, int dx, int dy)
 {
 this.cid = cid;
 this.x = x; this.y = y;
 this.dx = dx; this.dy = dy;
 }
 }
 C#
  • 17.
    Topic types canbe expressed using different syntaxes, including IDL and ProtoBuf Topic Type @KeyList ( topicType = "CarDynamics", keys = {"cid"})
 public class CarDynamics {
 public String cid;
 public int x; public int dx;
 public int y; public int dy;
 
 public CarDynamics(String s, int a, int b, int c,int d) {
 this.cid = s;
 this.x = a; this.dx = b;
 this.y = c; this.dy = d;
 }
 
 @Override
 public String toString() { …
 }
 
 }
 Java
  • 18.
  • 19.
    CopyrightPrismTech,2015 Each unique keyvalue identifies a stream of data Vortex demultiplexes “streams” and provides lifecycle information A DataWriter can write samples belonging to multiple instances Topic Instances CarDynamics Instances struct CarDynamics { @key string cid; long x; long y; float dx; long dy; } Topic Topic Type Sample
  • 20.
    QoS policies allowto express temporal and availability constraints for data DDS Global Data Space ... Data Writer Data Writer Data Writer Data Reader Data Reader Data Reader Data Reader Data Writer TopicA QoS TopicB QoS TopicC QoS TopicD QoS QoS - Enabled
  • 21.
    A collection ofpolicies that control non- functional properties such as reliability, persistence, temporal constraints and priority QoS HISTORY LIFESPAN DURABILITY DEADLINE LATENCY BUDGET TRANSPORT PRIO TIME-BASED FILTER RESOURCE LIMITS USER DATA TOPIC DATA GROUP DATA OWENERSHIP OWN. STRENGTH LIVELINESS ENTITY FACTORY DW LIFECYCLE DR LIFECYCLE PRESENTATION RELIABILITY PARTITION DEST. ORDER RxO QoS Local QoS
  • 22.
    QoS Policies controlling end-to-endproperties follow a Request vs. Offered QoS Domain Participant DURABILITY OWENERSHIP DEADLINE LATENCY BUDGET LIVELINESS RELIABILITY DEST. ORDER Publisher DataWriter PARTITION DataReader Subscriber Domain Participant offered QoS Topic writes reads Domain Id joins joins produces-in consumes-from RxO QoS Policies requested QoS
  • 23.
  • 24.
    Each Data Readeris associated with a Cache The Cache stores the last n∊𝜨∞ samples for each relevant instance Data Cache Data Writer Data Writer Data Writer Data Reader Data Reader Data Reader Data Writer TopicA QoS TopicB QoS TopicC QoS TopicD QoS TopicD QoS TopicD QoS TopicA QoS
  • 25.
    Each Data Readeris associated with a Cache The Cache stores the last n∊𝜨∞ samples for each relevant instance Data Cache DataReader Cache DataReader ... Samples Instances Cache
  • 26.
    The action ofreading samples for a Reader Cache is non-destructive. Samples are not removed from the cache Reading Data DataReader Cache DataReader ... DataReader Cache DataReader ...read
  • 27.
    The action oftaking samples for a Reader Cache is destructive. Samples are removed from the cache Taking Data DataReader Cache DataReader ... DataReader Cache DataReader ...take
  • 28.
    Samples can beselected using composable content and status predicates Sample Selectors DataReader Cache DataReader ...
  • 29.
    Filters allow tocontrol what gets into a DataReader cache Filters are expressed as SQL where clauses or as Java/C/JavaScript predicates Content-Filtering DataReader Cache DataReader ... Filter Application Network
  • 30.
    Content Filters can beused to project on the local cache only the Topic data satisfying a given predicate Content Filters struct CarDynamics { @key string cid; long x; long y; float dx; long dy; } cid x y dx dy GR 33N GO 167 240 45 0 LO 00V IN 65 26 65 0 AN 637 OS 32 853 0 50 AB 123 CD 325 235 80 0 “dx > 50 OR dy > 50” Type CarDynamics cid x y dx dy LO 00V IN 65 26 65 0 AB 123 CD 325 235 80 0 Reader Cache
  • 31.
    Queries allow tocontrol what gets out of a DataReader Cache Queries are expressed as SQL where clauses or as Java/C/JavaScript predicates Content-Based Selection DataReader Cache DataReader ... Query DataReader Cache DataReader ... Application Network
  • 32.
    Reader Cache Queries canbe used to select out of the local cache the data matching a given predicate Queries struct CarDynamics { @key string cid; long x; long y; float dx; long dy; } cid x y dx dy GR 33N GO 167 240 45 0 LO 00V IN 65 26 65 0 AN 637 OS 32 853 0 50 AB 123 CD 325 235 80 0 “dx > 50 OR dy > 50” Type CarDynamics cid x y dx dy GR 33N GO 167 240 45 0 LO 00V IN 65 26 65 0 AN 637 OS 32 853 0 50 AB 123 CD 325 235 80 0 cid x y dx dy LO 00V IN 65 26 65 0 AB 123 CD 325 235 80 0 query
  • 33.
    State based selection allowsto control what gets out of a DataReader Cache State base selectors predicate on samples meta- information State-Based Selection DataReader Cache DataReader ... State Selector DataReader Cache DataReader ... Application Network
  • 34.
    Sample State (READ,NOT_READ) allows to distinguish between new samples and samples that have already been read State-Based Selection DataReader Cache DataReader ... State Selector DataReader Cache DataReader ... Application Network
  • 35.
    The View State(NEW, NOT_NEW) allows to distinguish a new instance from an existing one State-Based Selection DataReader Cache DataReader ... State Selector DataReader Cache DataReader ... Application Network
  • 36.
    The Instance State(ALIVE, NOT_ALIVE_DISPOSED, NOT_ALIVE_NO_WRITERS) allows to track the life-cycle transitions of the instance to which a sample belongs State-Based Selection DataReader Cache DataReader ... State Selector DataReader Cache DataReader ... Application Network
  • 37.
    Selector Example // ==ISO C++ DDS API == auto data = dr.select() .content(query) .state(data_state) .instance(handle) .read();
  • 38.
  • 39.
  • 40.
    CopyrightPrismTech,2015 Writing Data inC++ #include <dds.hpp> int main(int, char**) { DomainParticipant dp(0); Topic<Meter> topic(“SmartMeter”); auto pqos = dp.get_default_pubqos() << Partition (“FR:IdF:Essonne:Gif:Essonne:Mnts:123”); Publisher pub(dp, pqos); DataWriter<Meter> dw(pub, topic); while (!done) { auto value = readMeter() dw.write(value); std::this_thread::sleep_for(SAMPLING_PERIOD); } return 0; } enum UtilityKind { ELECTRICITY, GAS, WATER }; struct Meter { string sn; UtilityKind utility; float reading; float error; }; #pragma keylist Meter sn
  • 41.
    CopyrightPrismTech,2015 Reading Data inC++ #include <dds.hpp> int main(int, char**) { DomainParticipant dp(0); Topic<Meter> topic(”SmartMeter”); Subscriber sub(dp); DataReader<Meter> dr(dp, topic); LambdaDataReaderListener<DataReader<Meter>> lst; lst.data_available = [](DataReader<Meter>& dr) { auto samples = data.read(); std::for_each(samples.begin(), samples.end(), [](Sample<Meter>& sample) { std::cout << sample.data() << std::endl; } } dr.listener(lst); // Print incoming data up to when the user does a Ctrl-C std::this_thread::join(); return 0; } enum UtilityKind { ELECTRICITY, GAS, WATER }; struct Meter { string sn; UtilityKind utility; float reading; float error; }; #pragma keylist Meter sn
  • 42.
    CopyrightPrismTech,2014 Writing Data inScala import dds._
 import dds.prelude._
 import dds.config.DefaultEntities._
 object SmartMeter {
 
 def main(args: Array[String]): Unit = {
 val topic = Topic[Meter](“SmartMeter”)
 val dw = DataWriter[Meter](topic) while (!done) { val meter = readMeter()
 dw.write(meter) Thread.sleep(SAMPLING_PERIOD) }
 }
 } enum UtilityKind { ELECTRICITY, GAS, WATER }; struct Meter { string sn; UtilityKind utility; float reading; float error; }; #pragma keylist Meter sn
  • 43.
    CopyrightPrismTech,2014 Reading Data inScala import dds._
 import dds.prelude._
 import dds.config.DefaultEntities._
 object SmartMeterLog {
 def main(args: Array[String]): Unit = {
 val topic = Topic[Meter](“SmartMeter”)
 val dr = DataReader[Meter](topic)
 dr listen {
 case DataAvailable(_) => dr.read.foreach(println)
 }
 }
 } enum UtilityKind { ELECTRICITY, GAS, WATER }; struct Meter { string sn; UtilityKind utility; float reading; float error; }; #pragma keylist Meter sn
  • 44.
    CopyrightPrismTech,2015 Writing Data inPython import dds import time
 
 if __name__ == '__main__':
 topic = dds.Topic("SmartMeter", "Meter")
 dw = dds.Writer(topic)
 
 while True:
 m = readMeter()
 dw.write(m)
 time.sleep(0.1) enum UtilityKind { ELECTRICITY, GAS, WATER }; struct Meter { string sn; UtilityKind utility; float reading; float error; }; #pragma keylist Meter sn
  • 45.
    CopyrightPrismTech,2015 Reading Data inPython import dds
 import sys
 
 def readData(dr): 
 samples = dds.range(dr.read())
 for s in samples:
 sys.stdout.write(str(s.getData()))
 
 if __name__ == '__main__':
 t = dds.Topic("SmartMeter", "Meter")
 dr = dds.Reader(t)
 dr.onDataAvailable = readData enum UtilityKind { ELECTRICITY, GAS, WATER }; struct Meter { string sn; UtilityKind utility; float reading; float error; }; #pragma keylist Meter sn
  • 46.
  • 47.
    Device implementations optimised forOT, IT and consumer platforms Native support for Cloud and Fog Computing Architectures Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
  • 48.
    Available across IT,Consumer and OT platforms Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
  • 49.
    Polyglot and Interoperable acrossProgramming Languages Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
  • 50.
    Fully Independent ofthe Cloud Infrastructure Private Clouds Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
  • 51.
    Native Integration withthe hottest real-time analytics platforms and CEP Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
  • 52.
    Integration with mainstream DashboardTechnologies Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
  • 53.
    High Performance 30 μs peer-to-peerlatency 4+ Mmsgs/sec p2p throughput Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
  • 54.
    >10 μs fog/cloudrouting latency High Performance Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
  • 55.
    Secure Data-Level security with PluggableAuthentication Access Control and Crypto Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
  • 56.
    Default Plug-ins X.509 PublicKey Infrastructure (PKI) based authentication Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
  • 57.
    Default Plug-ins Access ControlList file signed by a shared Certificate Authority for Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
  • 58.
    Default Plug-ins Crypto basedon TLS Cipher Suite Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog infrastructuresdk
  • 59.
    Secure Data-Security as opposed tosimply Transport-Level security Arthur Dent Arthur Dent Ford Prefect Zaphod Beeblebrox Marvin Trillian left/A(r,w), left/B(r) left/A(r,w), left/B(r,w), left/X(r) left/*(r,w) left/*(r), right/(w) left/A(r,w), left/B(r,w), right/C(r,w) Ford Prefect Zaphod Beeblebrox Trillian Marvin A B A,B X * * A,B,C Identity Access Rights Sessions are authenticated and communication is encrypted Only the Topic included as part of the access rights are visible and accessible
  • 60.
    Secure Fine-grained access control overPartition/Topic/ Instance regular expressions Arthur Dent Arthur Dent Ford Prefect Zaphod Beeblebrox Marvin Trillian left/A(r,w), left/B(r) left/A(r,w), left/B(r,w), left/X(r) left/*(r,w) left/*(r), right/(w) left/A(r,w), left/B(r,w), right/C(r,w) Ford Prefect Zaphod Beeblebrox Trillian Marvin A B A,B X * * A,B,C Identity Access Rights Sessions are authenticated and communication is encrypted Only the Topic included as part of the access rights are visible and accessible
  • 61.
    Secure Support for Symmetricand Asymmetric Authentication Arthur Dent Arthur Dent Ford Prefect Zaphod Beeblebrox Marvin Trillian left/A(r,w), left/B(r) left/A(r,w), left/B(r,w), left/X(r) left/*(r,w) left/*(r), right/(w) left/A(r,w), left/B(r,w), right/C(r,w) Ford Prefect Zaphod Beeblebrox Trillian Marvin A B A,B X * * A,B,C Identity Access Rights Sessions are authenticated and communication is encrypted Only the Topic included as part of the access rights are visible and accessible
  • 62.
    Boundary Security Boundary securitysupport is enabled by Vortex-Fog Device-to-Cloud Communication Peer-to-Peer (Broker-less) Device-to-Device Communication Fog Computing Fog Computing Fog Computing TLS TLS
  • 63.
    Boundary Security Separates securityconcerns at different scales and controls what information is exposed Device-to-Cloud Communication Peer-to-Peer (Broker-less) Device-to-Device Communication Fog Computing Fog Computing Fog Computing TLS TLS
  • 64.
  • 65.
    Vortex device, suchas Lite, Café, and Web are used to share data between different kinds of applications within a car Café and Web are typically used Android / HTML5 based infotainment Lite in typically used in ECU, sensors and onboard analytics
  • 66.
    Vortex Fog isused to transparently (for in car apps) decouple and control the data sharing within and across the car Vortex Fog also helps defining security boundaries and policies
  • 67.
    Vortex Fog efficientlyand securely deals with car to car communication Vortex Fog allows to decouple the transport used for in-car communication and that used for car-to-car communication
  • 68.
    Vortex Fog efficientlyand securely deals with cloud connectivity adapting traffic flows and protocols Device-to-Cloud Communication Cloud Analytics Fog Analytics Fog Analytics Fog Analytics Vortex Cloud efficiently and securely makes data available to any device at an Internet Scale
  • 69.
    Vortex Cloud efficiently andsecurely makes data available to any device at an Internet Scale Device-to-Cloud Communication Cloud Analytics Fog Analytics Fog Analytics Fog Analytics
  • 70.
  • 71.
    CopyrightPrismTech,2015 Connected Boulevard —Nice, France Vortex enables is the data sharing platform for the City Operating System Tens of thousands of devices connected by Vortex
  • 72.
    Autonomous Vehicles coordination of fastmoving autonomous vehicles intermittent connectivity dynamic pairing of devices
  • 73.
  • 74.
  • 75.
    ESA Extremely Large &SMART Telescope (ELT) 1750 computing nodes 100.000 mirrors whose position is adjusted 100 times per second! ELT will allow astronomers to probe the earliest stages of the formation of planetary systems and to detect water and organic molecules in proto- planetary discs around stars in the making
  • 76.
    Launch System 80K+ datapoints with aggregate updates rate of ~400K msgs/sec
  • 77.
    Connected Aircrafts 10 TBof data every 30m of flight
  • 78.
    Oil Rig 30000data points only 1% of available data used today
  • 79.
    Smart Lightbulbs 96Kbytes Memory Connected MedicalDevices 12 msec period for pleath data Peer-to-Peer connectivity
  • 80.
    Vortex enables Smart,Secure and Efficient Data Sharing in IoT In Summary
  • 81.