Future Internet: Technologies, Applications & Perspectives

SABER FERJANI

http://www.publicpolicy.telefonica.com/blogs/wp-content/uploads/2013/04/Future-Internet.jpg

Outline1. State of the art2. Technologies3. Applications4. Challenges5. Conclusions

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I. State of the art1. Internet Evolution 2. Web Evolution3. Future Internet Constituents4. Future Internet Landscape

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250K 100M 500M 1000

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 introducedOfficial 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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Web1.0

Web2.0Web3.0

2. Web Evolution

Mostly Static HTML

Interactive, Social

Networking

WoT, M2M, Virtual-Real

world interaction

2003 2010 2015 20200.5

12.5

25

50

6.3 6.8 7.2 7.6

Connected devices (Billion) World population (Billion)

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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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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

NFCMobile Device

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II. Technologies1. Internet protocols2. Constrained device protocols 3. Service composition4. Semantic web5. Wireless ad hoc networks

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1. Internet protocols1. 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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1. Internet protocols2. Distributed System Evolution

1980 1991 1996 1998 2000

ONC RPC CORBA 1.x CORBA 2.0 REST

CORBA 2.2XML-RPC

SOAP

Tightly coupled Loosely coupled

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1. Internet protocols3. Classification of web services

• Synchronous • Asynchronous

• RSS feed

• RESTful service

• Human servicehttp://fr.slideshare.net/cesare.pautasso/jopera-eclipsebased-visual-composition-environment-featuring-a-general-language-for-heterogeneous-service-ccomposition

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1. Internet protocols4. 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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1. Internet protocols5. 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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1. Internet protocols6. 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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2. Constrained device protocols1. 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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2. Constrained device protocols2. 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

HTTPUDP

TCP

IP

WS-EventingWS-Discovery

2. Constrained device protocols3. 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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2. Constrained device protocols4. Constrained Application Protocol

Eg: Ethernet link

IP

TCP

HTTP

Payload

Constrained link

IP

UDP

CoAP

Payload

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3. Service Composition1. Web process lifecycle

Annotation

Advertisement

Discovery

Selection

Composition

Execution

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3. Service Composition2. Composition Overview

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3. Service Composition3. Composition Landscape

Web

Ser

vice

Co

mpo

sition Static

Orchestration WS-BPEL

Choreography WS-CDL, CHOReOS

Combined

Dynamic Semantic Web Service RDF, DAML, OWL-S

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3. Service Composition4. 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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3. Service Composition5. 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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3. Service Composition6. Composition Representation

Business Process Model and Notation (BPMN) is a graphical representation for specifying business processes.

connecting objects:1. Events2. Gateway3. Connections4. Activities

1 2 3 4

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3. Service Composition7. 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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3. Service Composition8. Service Composition Summary

Industrial standard Formal methodsBPEL

(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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3. Service Composition9. 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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4. Semantic Web1. 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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4. Semantic Web1. Data Semantic

Wisdom

Knowledge

Information

DataRaw

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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4. Semantic Web2. 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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4. Semantic Web3. Execution Semantic

Execution semantic encompasses:

Message sequence, Execution flow

Conversion pattern

Preconditions, Post-conditions

Invocation effects

Activities coordination

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4. Semantic Web4. 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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5. Wireless ad hoc networks1. State of the Art

1967 1978 1994 1998 2003 2004 2007

Wireless HART ZigBee 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.pdfhttp://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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5. Wireless ad hoc networks2. 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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5. Wireless ad hoc networks3. 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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5. Wireless ad hoc networks4. Operating Systems

1. Tiny OS: based on event driven execution2. Lite OS: Unix-like OS for WSN3. Contiki: OS for low power wireless IoT devices4. Squawk VM: JAVA Micro Edition VM developed for Sun SPOT5. Mantis: multi-threaded operating system written in C for WSN6. SOS: developed in C and follows event-driven programming model7. SenOS: finite state machine based OS

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5. Wireless ad hoc networks5. Connectivity

1. Object Annotation: Barcode, 2D code2. 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 HART4. Proprietary: Z-Wave, INSTEON 5. Cellular: GSM, GPRS, GSM-Railway, UMTS,

EDGE, HSPA, LTE, LTE-Advanced

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5. Wireless ad hoc networks5. 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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5. Wireless ad hoc networks5. 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),

2.45-5.8Ghz3. 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 systems2. Bluetooth and Wi-Fi connections: bootstrap more capable wireless connections3. Social networking: exchange contacts4. Identity and access tokens: electronic identity documents and keycards5. Smartphone automation and NFC tags: automate tasks

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5. Wireless ad hoc networks5. Connectivity (IEEE 802.15)

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5. Wireless ad hoc networks5. Connectivity (Cellular Network)

http://fr.slideshare.net/zahidtg/3gpp-lte-evolved-packet-system-application-to-femtos

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III. Applications1. Intelligent Transport Systems2. Industrial 3. Healthcare4. Agriculture5. Logistic6. Smart Home7. Smart Grid

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1. Intelligent Transport Systems Automotive

V2VV2R

Railway

Aeronautical

Maritime

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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

WAVEIEEE P1609

DSRCIEEE 802.11pASTM2213

IEEE P1556

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1. Intelligent Transport SystemsV2V: VEHICLE-TO-VEHICLE

Emergency services

Dragnet controls

Cruise control

Automated highways

Obstacle Discovery & Avoidance

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1. Intelligent Transport SystemsV2R: 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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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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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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4. AgricultureSMART ANIMAL FARMING SMART VEGETATION

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5. Logistic & Supply chain Quality of Shipment Conditions

Item Location

Storage Incompatibility Detection

Fleet Tracking

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6. Smart Home Light control

DimmerIntrusion

Devices remote controlHVACFridge, coffee machine..

Remote careSurveillance

Security and safetyFace recognitionFire detection

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7. Smart Grid

Reliability

Flexibility

Efficiency

Sustainability

Market-enabling

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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 layerPhysical layer

Wired (EN-13757-2)Data link layerPhysical layer

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IV. Challenges1. Standardization, Heterogeneity & Interoperability2. Security, Privacy & Trust

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1. Standardization, Heterogeneity & Interoperability

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Standardization Physical layer (Spectrum management) Link layer (Topology) Bootstrapping Identification…

Constrained Resources Processing Memory Power Communication…

2. Security, Privacy & TrustLayer 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 securityIpsec 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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V. Conclusions1. Summary2. Perspectives

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1. Summary

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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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Thanks for your attention!

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