History of Internet and Future Trends, Internet of Things, Intelligent Transport Systems, Web service Composition

1. Future Internet: Technologies, Applications & Perspectives
SABER FERJANI
http://www.publicpolicy.telefonica.com/blogs/wp-content/uploads/2013/04/Future-Internet.jpg

2. Outline
1. State of the art
2. Technologies
3. Applications
4. Challenges
5. Conclusions
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3. I. State of the art
1. Internet Evolution
2. Web Evolution
3. Future Internet Constituents
4. Future Internet Landscape
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4. 250K 100M 500M1000
1. Evolution of the internet
1969 1980 1982 1989 1995 1998 2001 2003 2004 2005
300
Web 2.0
UCLA
creates
ARPANET IPv4 first
used
The word
“Internet”
is used for
the first
time
WWW
invention
Official launch of:
- Amazon.com
- Yahoo.com
- Ebay.com
- Msn.com
IPv6 introduced
Official launch of:
- Google.com
- Disney.com
- PayPal.com
1BEstimated users:
Web 1.0
http://www.usfca.edu/fac-staff/morriss/478/spring03/internet/history.htm
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5. Web1.0
Web2.0
Web3.0
2. Web Evolution
Mostly Static
HTML
Interactive,
Social
Networking
WoT, M2M,
Virtual-Real
world
interaction
0.5
12.5
25
50
6.3 6.8 7.2 7.6
2003 2010 2015 2020
Connected devices (Billion) World population (Billion)
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6. 3. Future Internet Constituents
 Internet by/for people
 Internet of content
 Internet of service
 Internet of Things
Future
internet
Any time ,
Any
Context
Any thing,
Any device
Any place,
Any where
Any path,
Any
network
Any
service,
Any
business
Any one,
Any body
Content Connectivity
Computing Convergence
CommunicationCollection
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7. 4. Future Internet Landscape
WAN
RFID
M2M
U2M
U2U
Mobile
phone
Object
Tracking
Smart Grid
Home Automation
Environmental
Monitoring
Industrial
Sensors
AMI
http://stakeholders.ofcom.org.uk/binaries/research/technology-research/wsn3.pdf
NFC
Mobile
Device
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8. II. Technologies
1. Internet protocols
2. Constrained device protocols
3. Service composition
4. Semantic web
5. Wireless ad hoc networks
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9. 1. Internet protocols
1. Classification of Internet protocols
Deployment
• Client/Server: HTTP
• Peer-to-Peer: BitTorrent
• N-Tier, 3-Tier: MVC
Structure
• Object-Oriented: RMI
• Component-Based: CORBA
• Resource-Oriented: REST
Communication
• Service-Oriented: SOAP
• Message Bus: ESB
http://research.microsoft.com/pubs/117710/3-arch-styles.pdf
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10. 1. Internet protocols
2. Distributed System Evolution
1980 1991 1996 1998 2000
ONC RPC CORBA 1.x CORBA 2.0 REST
CORBA 2.2
XML-RPC
SOAP
Tightly coupled Loosely coupled
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11. 1. Internet protocols
3. Classification of web services
• Synchronous
• Asynchronous
• RSS feed
• RESTful service
• Human service
http://fr.slideshare.net/cesare.pautasso/jopera-eclipsebased-visual-composition-environment-featuring-a-general-language-for-heterogeneous-service-ccomposition
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12. 1. Internet protocols
4. Service Oriented: SOAP
SOAP is a Cross Platform Web Service
Development Using ordinary XML.
SOAP message content:
 An Envelope
 A Header
 A Body
SOAP message types:
 SOAP RPC-Style (Synchronous)
 SOAP Document-style (Asynchronous)
Client app code Client service code
Proxy/stub
Encoding
Protocol
Transport
Skeleton
Encoding
Protocol
Transport
attachementdataheader
Jaxb, direct XML
XML, Fast-infoset
HTTP, SIP, SMTP
UDP, TCP
WSDL
UDDI
WS-Trust, WS-Security,
WS-SecureConversation
WS-ReliableMessaging,
WS-AtomicTransactions
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13. 1. Internet protocols
5. Resource Oriented: REST
Representational State Transfer is composed
of state-full resources, manipulated through
uniform interface (CRUD).
REST Constraints:
 Client-Server: Components Independent
 Stateless: Visibility, reliability and scalability
 Cacheable: Efficiency but reduce reliability
 Layered system: System scalability
 Code on demand (opt): Extension after deployment
 Uniform Interface: Simple
Client
Web Service
(Backend)
Request
Response
API
Client app code Client service code
Proxy/stub
Encoding
Protocol
Transport
Skeleton
Encoding
Protocol
Transport
attachementdataheader
WADL
Jaxb, direct XML
XML, JSON
HTTP
TCP
DNS SSL HTTP session
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14. 1. Internet protocols
6. Compare SOAP vs REST
SOAP REST
• Exposes resources that represent data
• Uses VERBS (Methods: GET/POST/PUT/DELETE)
• Supports multiple data formats: XML, JSON…
• Only stateless communication
• GET-base URIs are cacheable
• Exposes operations that represent logic
• Uses only the verb POST
• Encodes everything in XML
• Supports stateless and state-full operations
• Not cached by any existing technology
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15. 2. Constrained device protocols
1. Universal Plug-and-Play
The UPnP technology is designed to support
zero-configuration, invisible net-working and
automatic discovery of the network devices.
classify the devices into two general categories:
 CD: Controlled device
 CP: Control Point
Both the CP and the CD can be implemented on
any platform like PCs and embedded systems.
Network
Host
Network
Host
Control
device
Controlled
point
Service: 1
-Actions
-State Variables
Service: 2
-Actions
-State Variables
http://download.springer.com/static/pdf/632/chp%253A10.1007%252F978-3-642-38082-2_26.pdf?auth66=1390154381_6a2d54b42f14fb298210f1a8dfcbe5ab&ext=.pdf
Discovery
Description
Control
Eventing
Presentation
AddressingAddressing
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16. 2. Constrained device protocols
2. Devices Profile for Web Services
 Introduced in 2004.
 Fully aligned with Web Services technology.
 Defines a minimal set of implementation
constraints on resource-constrained devices to
enable Secure:
 Web Service messaging
 Discovery
 Description
 Eventing.
On June, 2009, DPWS 1.1, WS-Discovery 1.1,
and SOAP-over-UDP 1.1 have been approved as
OASIS Standards.
DPWS Stack of Protocols
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Application Protocols
WS-Security ,WS-Policy, WS-Addressing ,
WS-Metadata Exchange
SOAP – WSDL – XML schema
HTTP
UDP
TCP
IP
WS-EventingWS-Discovery

17. 2. Constrained device protocols
3. Tiny SOA
The hardware platform based on MicaZ.
The Gateway and Server components
where developed using Java, and
Registry consisted of a MySQL database.
TinyVisor system showing:
 a the network selection dialog,
 b the network visualization in data,
 c the network visualization in graph,
 and d topology modes.
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18. 2. Constrained device protocols
4. Constrained Application Protocol
Eg: Ethernet link
IP
TCP
HTTP
Payload
Constrained link
IP
UDP
CoAP
Payload
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19. 3. Service Composition
1. Web process lifecycle
Annotation
Advertisement
Discovery
Selection
Composition
Execution
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20. 3. Service Composition
2. Composition Overview
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21. 3. Service Composition
3. Composition LandscapeWebService
Composition
Static
Orchestration WS-BPEL
Choreography WS-CDL, CHOReOS
Combined
Dynamic
Semantic Web
Service
RDF, DAML, OWL-S
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22. 3. Service Composition
4. Static Composition
1. Orchestration: a central process takes
control of the involved Web services and
coordinates the execution of different
operations.
2. Choreography: is a collaborative effort
focusing on the exchange of messages in
public business processes.
3. Combined: use one of the last method on
top of the other.
 Choreography between orchestrated
processes
 Orchestration of choreography-style
processes
coordinator
Web
service 1
Web
service 2
1
2
Web
service 33
4
5
Web
service 1
Web
service 3
Web
service 2
1
2
34
http://www.oracle.com/technetwork/articles/matjaz-bpel1-090575.html
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23. 3. Service Composition
5. Dynamic Composition
Specification
Matchmaking
Algorithms
Generation
CSL language
Composabilty
Model
Composition
plans
Web
service
registries
Ontological
organization and
description of
WS
High level
description
of desired
composition
Composite
Service
QoC
parametersComposition
plan cost
Orchestration
Service Composition for the Semantic Web - DOI 10.1007/978-1-4419-8465-4
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24. 3. Service Composition
6. Composition Representation
 Business Process Model and Notation
(BPMN) is a graphical representation for
specifying business processes.
 connecting objects:
1. Events
2. Gateway
3. Connections
4. Activities
1 2 3 4
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25. 3. Service Composition
7. Formal Methods
1. Automata:
◦ I/O automata: distributed computations.
◦ Team automata: components of groupware
systems, and their interconnections.
◦ Timed automata: real time systems.
2. Petri Nets: used to model concurrent
systems.
3. Process Algebras: describe and reason
about process behaviors.
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26. 3. Service Composition
8. Service Composition Summary
Industrial standard Formal methods
BPEL
(Static composition)
OWL-S
(Dynamic composition)
Automata Petri Nets
Process
Algebras
Service connectivity
Nonfunctional properties
Composition correctness
Automatic composition
Composition scalability
Exception handling
Compensation
Verification
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27. 3. Service Composition
9. RESTful web service composition
 WSDL/SOAP based Web service composition
has been extensively studied.
 However, RESTful web service composition is
less explored.
 Potential Solution:
 wrap RESTful web service behind SOAP/WSDL
http://fr.slideshare.net/cesare.pautasso/restful-service-composition-with-jopera
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28. 4. Semantic Web
1. Data Semantic
Huge amount of data from our
physical world that need to be:
 Annotated
 Published
 Stored (temporary or for
longer term)
 Discovered
 Accessed
 Processed
 Used in different applications
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29. 4. Semantic Web
1. Data Semantic
Wisdom
Knowledge
Information
Data
Raw
sensory
data
Structured
data (with
semantics)
Abstraction and
perceptions
Actionable
intelligence  Data is acquired from sensors.
 Information is collection of Data, it identify
trends and patterns.
 Adding other sources of information come
together to form knowledge.
 Wisdom is then born from knowledge plus
experience.
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30. 4. Semantic Web
2. Functional Semantic
 Appropriate Service Discovery.
 Semantic signature depend on functional
requirements.
 Intended function of each service is
represented as annotations using ontologies.
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31. 4. Semantic Web
3. Execution Semantic
Execution semantic encompasses:
 Message sequence, Execution flow
 Conversion pattern
 Preconditions, Post-conditions
 Invocation effects
 Activities coordination
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32. 4. Semantic Web
4. Quality of Service Semantic
 Multiple choices: Select suitable service
 Evaluation of alternative strategies
 Web processes can be designed according to
QoS metrics
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33. 5. Wireless ad hoc networks
1. State of the Art
1967 1978 1994 1998 2003 2004 2007
Wireless HARTZigBee 1.0
IEEE
802.15.4
Berkeley
Motes
UCLA
create
LWIM
REMBASS
DARPA
sponsored
DSN
https://www.cooperating-objects.eu/fileadmin/dissemination/joint-seminars/20100719-camp-wsn.pdf
http://www.fas.org/man/dod-101/sys/land/rembass.htm
-1998: WeC
-1999: René
-2000: Dot
-2001: Mica
-2002: Mica2
-2004: Telos
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34. 5. Wireless ad hoc networks
2. Components
1. Microcontroller (8, 16 or 32bit)
2. Transceiver + embedded/external antenna
3. Power source (Wired, Battery, Solar…)
4. Sensors
5. Indicator (opt): Led, Buzzer, LCD…
6. Actuator (opt): Relay, Motors,
Electrovanne...
 Environmental sensors: Temperature,
Humidity (soil, leaf, ambient), Soil moisture,
Wind (speed and direction), Pressure, Leaf, Ph,
Redox…
 Physical sensors: accelerometer, presence,
vibration, power, hall, ultrasound, water,
sound, bend, flex, strain, stress…
 Gas sensors: Co2, Co, CH4, O2, NH3, SH2,
NO2, Pollution…
 Optical sensors: Infrared, Sunlight, Radiation,
Ultraviolet, color…
 Biometric sensors: Electrocardiogram ECG,
Oximetry, Pulse, Fall, Sweat…
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35. 5. Wireless ad hoc networks
3. Hardware platforms
1. Sun SPOT™
2. Sentilla ™ JCeate
3. Crossboy ™ TelosB
4. Nano-RK FireFly ™
5. Tmote
6. Mica, Mica2, MicaZ
7. AVR® Series
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36. 5. Wireless ad hoc networks
4. Operating Systems
1. Tiny OS: based on event driven execution
2. Lite OS: Unix-like OS for WSN
3. Contiki: OS for low power wireless IoT devices
4. Squawk VM: JAVA Micro Edition VM developed for Sun SPOT
5. Mantis: multi-threaded operating system written in C for WSN
6. SOS: developed in C and follows event-driven programming model
7. SenOS: finite state machine based OS
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37. 5. Wireless ad hoc networks
5. Connectivity
1. Object Annotation: Barcode, 2D code
2. Short Range: RFID, NFC
3. IEEE 802.x:
1. 802.11: WiFi, WAVE/DSRC (2.4, 3.6, 5 and 60GHz)
2. 802.15.1: Bluetooth smart
3. 802.15.4: Zigbee, 6LoWPAN, ISA100.11, Wireless
HART
4. Proprietary: Z-Wave, INSTEON
5. Cellular: GSM, GPRS, GSM-Railway, UMTS, EDGE,
HSPA, LTE, LTE-Advanced
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38. 5. Wireless ad hoc networks
5. Connectivity (Object Annotation)
1. 1D code: Barcodes
2. 2D code:
1. QR Code ISO/IEC 18004 (Denso Wave)
2. AZTEC code ISO/IEC 24778 (Welch Allyn )
3. High Capacity Color Barcode (Microsoft)
4. Data Matrix/Semacode (Microscan Systems)
1 2 3 4
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39. 5. Wireless ad hoc networks
5. Connectivity (Short Range)
1. RFID (Radio Frequency Identification)
1. Tag identifier: 64-96 bit (provided by EPC-Global)
2. Frequency: 135Khz, 13.56Mhz, 433Mhz, 865-868(EU) MHz/902-928MHz(US), 2.45-5.8Ghz
3. Energy source:
• Active: plugged to power source
• Passive: use electromagnetic field to power the chip
2. NFC (Near field communication) builds upon RFID, Bidirectional communication:
1. Commerce: contactless payment systems
2. Bluetooth and Wi-Fi connections: bootstrap more capable wireless connections
3. Social networking: exchange contacts
4. Identity and access tokens: electronic identity documents and keycards
5. Smartphone automation and NFC tags: automate tasks
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40. 5. Wireless ad hoc networks
5. Connectivity (IEEE 802.15)
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41. 5. Wireless ad hoc networks
5. Connectivity (Cellular Network)
http://fr.slideshare.net/zahidtg/3gpp-lte-evolved-packet-system-application-to-femtos
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42. III. Applications
1. Intelligent Transport Systems
2. Industrial
3. Healthcare
4. Agriculture
5. Logistic
6. Smart Home
7. Smart Grid
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43. 1. Intelligent Transport Systems
 Automotive
V2V
V2R
 Railway
 Aeronautical
 Maritime
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44. 1. Intelligent Transport Systems
 WAVE (Wireless Access in Vehicular
Environments): Mode of operation used by
IEEE 802.11 devices to operate in the DSRC
band
 DSRC (Dedicated Short Range
Communications):
• ASTM Standard E2213-03, based on IEEE
802.11a
• Name of the 5.9GHz band allocated for the ITS
communications.
Physical
Data Link
Network
Transport
Session
Presentation
Application
WAVE
IEEE P1609
DSRC
IEEE 802.11p
ASTM2213
IEEE
P1556
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45. 1. Intelligent Transport Systems
V2V: VEHICLE-TO-VEHICLE
 Emergency services
 Dragnet controls
 Cruise control
 Automated highways
 Obstacle Discovery & Avoidance
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46. 1. Intelligent Transport Systems
V2R: VEHICLE-TO-ROADSIDE
 Smart parking
 Variable Speed limits
 Navigation Services
 Security & Safety
 Dangerous curves, Intersections
 Insurances & Enterprise fleet control
 Dynamic route optimization
 Dynamic traffic light sequence
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47. 2. Industrial process automation
 ISA-100.11a and WirelessHART (IEC 62591-1)
are two of the most important standards
available focused on applications of wireless
networks in process automation.
 Both protocols uses AES-128 encryption.
 ISA100.12: A Request for Proposals (RFP) to
achieve convergence between ISA100.11a and
WirelessHART was issued on Nov. 8, 2010.
ISA-100.11A WIRELESS HART
IEEE 802.15.4 (2.4Ghz)
Upper data link ISA100.11a
6LoWPAN (RFC 4944)
UDP (RFC 768)
ISA native and legacy
protocols (Tunneling)
TDMA – Channel hoping
Power optimized Redundant
paths mesh network
Auto-segmented transfer of
large data sets. reliable stream
transport
Command oriented.
Predefined data types and
application procedures
Physical
Data link
Network
Transport
Application
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48. 3. Healthcare
 Tele-medicine: Remote surgery.
 Post-operative or intensive care, Long-term
surveillance of old persons/chronically ill patients.
 EHR/EMR: Systematic collection of electronic
health information about individual patients.
 Patient, Staff and Object tracking using RFID.
 Sportsmen Care: Track steps, distance, and
calories burned. (Eg: Fitbit).
da Vinci Surgical System
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49. 4. Agriculture
SMART ANIMAL FARMING SMART VEGETATION
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50. 5. Logistic & Supply chain
 Quality of Shipment Conditions
 Item Location
 Storage Incompatibility Detection
 Fleet Tracking
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51. 6. Smart Home
 Light control
Dimmer
Intrusion
 Devices remote control
HVAC
Fridge, coffee machine..
 Remote care
Surveillance
 Security and safety
Face recognition
Fire detection
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52. 7. Smart Grid
 Reliability
 Flexibility
 Efficiency
 Sustainability
 Market-enabling
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53. 7. Smart Grid
 EN 13757-1: Data exchange
 EN 13757-2: Physical and link layer
 EN 13757-3: Dedicated application layer
 EN 13757-4: Wireless meter readout
 EN 13757-5: Routing layer
 EN 13757-6: Local bus
Manufacturer specific application
OMS DSMR
Application layer (EN-13757-3)
Routing layer (EN-13757-5) (optional)
Wireless (EN-13757-4)
Data link layer
Physical layer
Wired (EN-13757-2)
Data link layer
Physical layer
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54. IV. Challenges
1. Standardization, Heterogeneity & Interoperability
2. Security, Privacy & Trust
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55. 1. Standardization, Heterogeneity &
Interoperability
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 Standardization
 Physical layer (Spectrum management)
 Link layer (Topology)
 Bootstrapping
 Identification…
Constrained Resources
 Processing
 Memory
 Power
 Communication…

56. 2. Security, Privacy & Trust
Layer Advantage Drawback
Application layer security Fully controlled by application Only app. data is secured
Transport layer security
through TLS (over TCP) or DTLS
(over UDP)
Flexible and widely used No security below transport,
2 solutions for 2 protocols (TCP
and UDP)
Network layer security
Ipsec in tunnel or transport
mode
Flexible and works with any
transport layer,
Lowest layer at which end-to-
end security is possible
No security of link-layer header
Physical layer security
Encryption of every frame, e.g.
through 802.15.4 encryption
Cheap and done in H/W, Secures
the whole frame
Only hop-by-hop security
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57. V. Conclusions
1. Summary
2. Perspectives
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58. 1. Summary
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59. 2. Perspectives
 Protocol trends
 Collaboration: IEEE, IETF, ISA, ETSI, CENELEC…
 Evolution: Software-defined radio
 Scalability: Optimize spectrum use
 Web services
 Discovery
 Composition
 Semantic
 Low overhead
Security Issues
 Privacy concern, Eavesdropping
 Key Distribution & Management
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60. Thanks for your attention!
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