3. Internet of Things : Anytime, anywhere, by anyone and anything
– ITU, November 2005
Characteristics of IoT
Internet
of
Things
Computing
Anytime
Any content
Content
Anyone
Anybody
Collection
Any Service
Any Business
Communication
Any path
Any Network
Connectivity
Any place
Anywhere
Convergence
Anything
Any device
“We are heading into a new era
of ubiquity, where the users of
the Internet will be counted in
billions, and where humans
may become the minority as
generators and receivers of
traffic. Changes brought about
by the Internet will be dwarfed
by those prompted by the
networking of everyday objects
“ – UN report
26. IoT Technological Developments
Development Areas Before 2010 2010-2015 >2015
Identification
Technologies
•Different Schemes
•Domain specific IDs
•ISO, GS1, u-code, IPv6, etc
•Unified framework for unique identifiers
•Open framework for IoT
•URIs
•Identity Management
•Semantics
•Privacy-awareness
•“Things DNA” identifier
IoT Architecture
Technology
•IoT architecture specification
•Context-sensitive middleware
•Intelligent reasoning platforms
•IoT architecture developments
•Network of networks architecture
•Platforms interoperability
•Adaptive, context based
architectures
•Self-* properties
•Cognitive architectures
•Experiential architecture
Communication
Technology
•RFID, UWB, Wi-Fi, WiMax,
Bluetooth, ZigBee, ISA100,
6LoWPAN
•Ultra low power chipsets, system on chip
•On chip antennas
•Millimeter wave single chips
•Ultra low power single chip radios
•Ultra low power system on chip
•Mobility
•Heterogeneity
•Wide spectrum and spectrum
aware protocol
•Unified protocol over wide
spectrum
Network Technology •Sensor networks •Self aware & self organizing network
•Delay tolerant networks
•Storage networks and power networks
•Hybrid networking technologies
•Sensor network location transparency
•Network context awareness
•Network cognition
•Self learning, self repairing
network
Source: FP7 - Cluster of European Research Projects on the Internet of Things (CERP-IoT) - Strategic Research Agenda
27. IoT Technological Developments
Development Areas Before 2010 2010-2015 >2015
Software and
Algorithm
•Relational database integration
•IoT oriented RDBMS
•Event-based platforms
•Sensor middleware
•Sensor network middleware
•Proximity / localization algorithms
•Large scale, open semantic software
modules
•Composable algorithms
•Next generation IoT-based social
software
•Next generation IoT-based
enterprise applications
•Goal oriented software
•Distributed intelligence, problem
solving
•T-to-T collaboration environments
•User oriented software
•The invisible IoT
•Easy to deploy IoT software
•Things to Human collaborations
•IoT for all
Hardware •RFID tags and sensors
•Sensors build in mobile devices
•NFC in mobile phones
•Smaller and cheaper
•MEMs technology
•Multi protocol, multi standards
reader
•More sensors and actuators
•Secure, low cost tags, sensors
•Smart sensors (Bio-chem)
•More sensors and actuators (tiny
sensors)
•Nano-technology and new materials
Data & Signal
Processing Technology
•Serial data processing
•Parallel data processing
•Quality of services
•Energy, frequency spectrum aware
data processing,
•Data processing context adaptable
•Context aware data processing and
•data responses
•Cognitive processing and
•optimisation
Discovery and Search
Engine Technology
•Sensor network ontologies
•Domain specific name services
•Distributed registries, search and
•discovery mechanisms
•Semantic discovery of sensors and
sensor data
•Automatic route tagging and
•Identification
•Automatic route tagging and
•identification management centres
•Cognitive search engines
•Autonomous search engines
28. IoT Technological Developments
Development Areas Before 2010 2010-2015 >2015
Power and Energy
Storage Technologies
•Thin batteries
•Li-Ion
•Flat batteries
•Power optimized systems
•(energy management)
•Energy harvesting (electrostatic,
•piezoelectric)
•Short and medium range
•wireless power
•Energy harvesting (energy
conversion,
•photovoltaic)
•Printed batteries
•Long range wireless power
•Energy harvesting (biological,
•chemical, induction)
•Power generation in harsh
•environments
•Energy recycling
•Wireless power
•Biodegradable batteries
•Nano-power processing unit
Security and Privacy
Technologies
•Security mechanism and protocol
defined (RFID & WSN)
•Security mechanisms and protocols
for RFID and WSN
•devices
•User centric context-aware privacy
and policy
•Privacy aware data processing
•Virtualisation and anonymisation
•Security & Privacy profiles based on
needs
•Privacy needs automatic evaluation
•Context centric security
•Self adaptive security mechanisms
and protocols
Material Technology •Silicon, Cu, Al Metallization
•3D processes
•SiC, GaN
•Silicon
•Improved/new semiconductor
manufacturing processes /
technologies for
•higher temperature ranges
•Diamond
Standardization •RFID security
•Passive RFID with expanded
memory and read/write capability
•IoT standardization
•M2M
•Interoperability
•Standards for cross interoperability
with heterogeneous networks
Source: FP7 - Cluster of European Research Projects on the Internet of Things (CERP-IoT) - Strategic Research Agenda
30. IEEE 802.15.4
• Specifies a wireless link for low-power personal area
networks (LoWPANs)
• 802.15.4 is widely used in embedded applications, such
as environmental monitoring
• These applications generally require numerous low-cost
nodes communicating over multiple hops to cover a large
geographical area, and they must operate unattended for
years on modest batteries
32. IEEE 802.15.4 and IPv6
• Entire 802.15.4 MTU is 127 bytes
• Low Bandwidth (250 kbps), low power (1 mW) radio
• Small Packets to keep packet error rate low and permit
media sharing
• Often data payload is small
• Standard IPv6 header is 40 bytes [RFC 2460]
• IPv6 requires all links support 1280 byte packets [RFC
2460]
32
33. Benefits of 6LoWPAN Technology
• Low-power RF + IPv6 =
The Wireless Embedded Internet
• 6LoWPAN makes this possible
• The benefits of 6LoWPAN include:
– Open, long-lived, reliable standards
– Easy learning-curve
– Transparent Internet integration
– Network maintainability
– Global scalability
– End-to-end data flows
34. Why We Need It?
• Open system based interoperability between devices
• Leverage existing standards, rather than “reinventing the
wheel”
• Ability to work within the resource constraint of low-
power, low-bandwidth and low-memory
35. Challenges in 6LoWPAN Deployment
• No method exists to run IPv6 over IEEE 802.15.4
• Using IPv6 and other headers as it is may not fit
– 40 bytes of IPv6, 20 bytes of TCP, 8 bytes of UDP + other headers
• Existing routing protocol unsuitable
• Current service discovery method too bulky
• Fragmentation and reassembly layer
• Limited configuration & management on sensors
• Security issues
• Network management
– Memory, processor and packet size constraint of sensor, further
investigation required on using existing network management protocol
37. Research Motivation
• Interplanetary Internet (IPN) is a NASA research project led by Vint Cerf in 1998.
• The basic idea is to try to make data communications in space/ between planets.
• E.g. Communication between Earth and Mars
– Communication is greatly delayed
• The delay in sending or receiving data from Mars takes between
three-and-a-half to 20 minutes at the speed of light.
– Intermittent connectivity
• Planetary movement
• TCP is not suitable in space missions.
• A new set of protocol is needed to tolerate large delay
– IPN architecture was designed.
38. How to apply the IPN architecture to other
situations in which communications were
subject to delays and disruptions?
-IPN researchers-
Ø In 2002 - “Delay Tolerant Network Architecture: The
Evolving Interplanetary Internet” was introduced for
application on earth
39. Delay Tolerant Network (DTN)
• DTN is a set of protocols that act
together to enable a standardized
method of performing store-carry-and-
forward communications.
• Characteristics of DTN:
i. Intermittent connectivity
– No end-to-end path between source and
destination
ii. Long variable delay
– Long propagation delays between nodes
A
B
B
C
C D
Source
Store
Carry
Forward
Store
Carry
Forward
Destination
41. Wildlife Monitoring
• ZebraNet
– Goal: Track mobility patterns of zebras in Kenya, Africa.
– Custom tracking collar with GPS (node) is put on the neck of the zebra.
– Nodes record zebra’s location and stores in memory.
– Nodes carry the data until meet another node.
– Exchanges data with another zebra when in communication range.
– Mobile base station (MBS) collects data from collars when researchers are in the field.
- MBS is not fixed, rather it moves and is only intermittently available
41
P. Juang, H. Oki, Y. Wang, et al. Energy-Efficient Computing for Wildlife Tracking: Design Tradeos and Early Experiences with ZebraNet. In Proceedings of ASPLOS-X, Oct.
2002.
Physical presence of the researchers is no longer required at the deployment site in
order to collect and publish zebra mobility pattern data.
ØNetwork connectivity is intermittent and opportunistic
42. Communications in Rural Areas
• DakNet
Goal: Provide low cost internet connectivity to poor rural areas in India
A bus carrying a 802.11b
access point
Kiosks are built up in villages
and are equipped with digital
storage and short-range
wireless communications.
MAP transport data among public kiosks and a hub
Ønon-real time(asynchronous)internet access
Pentland, A., Fletcher, R. and Hasson, A. “DakNet: Rethinking Connectivity in Developing Nations”. IEEE Computer, vol. 37, no. 1 Jan. 2004, pp. 78–83.
44. Give it to me, I
have 1G bytes
phone flash.
I have 100M
bytes of data,
who can carry for
me?
I can also
carry for you!
Thank you but you
are in the opposite
direction!
Don’t give to me! I am
running out of storage.
Reach an
access point.
Internet
Finally, it
arrive…
Search La
Bonheme.mp3
for me
Search La
Bonheme.mp3
for me
Search La
Bonheme.mp3
for me
There is
one in my
pocket…
45. In 2006, Lilien, Kamal, and Gupta have
developed a similar paradigm as DTNs
with the name of Opportunistic Networks
(OppNets)
L. Lilien, Z.H. Kamal and A. Gupta (in cooperation with V. Bhuse and Z Yang), "Opportunistic Networks: The Concept and Research Challenges," Department of Computer
Science, Western Michigan University, Kalamazoo, Michigan, February 9, 2006.
46. Issues in DTN
• Mobility Model
– Network highly mobile and dynamic in nature
• What is the mobility pattern?
• Mobility patterns of assigned "carrier nodes”
• Routing
– The most challenging problem therefore lies in finding the route
between two disconnected devices.
• Trust
– Finding “carriers nodes" network that trust
• Most of the time we assume that the nodes cooperate with each other (i.e.
hosts do not refuse to deliver messages)
46