Internet of things (IoT) and iot and big data- Rouhollah Nabati

1. 1
Internet of Things
and
Big Data Analytics
Rouhollah Nabati
IAUSDJ.ac.ir
Fall, 2016

2. Table of
Contents
2 IoT
1 Motivations
3 Big Data

3. Why should I learn about IoT?
− Business trend
− Emerging technologies
− Growing IoT Services and Application
− It’s Importance. Why?
3

4. 4

5. Internet of Things (IoT) -1
− Extending the current Internet and providing
connection, communication, and inter-networking
between devices and physical objects, or
"Things," is a growing trend that is often referred
to as the Internet of Things.
− “The technologies and solutions that enable
integration of real world data and services into
the current information networking technologies
are often described under the umbrella term of
the Internet of Things (IoT)”
5

6. What is Internet of Things (IoT) - 2
− Things, in the IoT, can refer to a wide variety of
devices such as heart monitoring implants,
bio-chip transponders on farm animals,
automobiles with built-in sensors, or field
operation devices that assist fire-fighters in
search and rescue. Current market examples
include smart thermostat systems and
washer/dryers that utilize WiFi for remote
monitoring.

7. What is Internet of Things (IoT) - 3
− Due to the ubiquitous nature of connected objects in
the IoT, an unprecedented number of devices are
expected to be connected to the Internet. According
to Gartner, there will be nearly 26 billion devices on
the Internet of Things by 2020. ABI Research
estimates that more than 30 billion devices will be
wirelessly connected to the IoT by 2020. Per a recent
survey and study done by Pew Research Internet
Project, a large majority of the technology experts
and engaged Internet users who responded. 83%
agreed with the notion that the Internet/Cloud of
Things and embedded and wearable computing will
have widespread and beneficial effects by 2025. It is,
as such, clear that the IoT will consist of a very large
number of devices being connected to the Internet.

8. 8
Tip

9. 9
Moore’s Law

10. 10
Inside A transistor

11. 11

12. 12

13. 13
What is the technology instead?
− Parallel processing
− Distributed processing
− Your suggestions?
− We have no other choice!

14. 14

15. 15

16. 16
16
“Thing” connected to the internet
Image Courtesy: : CISCO

17. Terminologies similar to IoT
1. USN (Ubiquitous Sensor Networks)
2. M2M (Machine-to-Machine)
3. IoE (Internet of Everything) – Cisco’s favorite term
4. Cloud of Things
5. Web of Things

18. IoT related technologies
1. Embedded systems
2. Embedded systems OS(Contiki, Unix, …)
3. Communication technologies
4. Sensor technologies
5. Real time systems
6. Smart things and technologies
7. Machine-to-Machine Communications
8. Big Data Analytics

19. IoT Communication Technologies
1. Bluetooth
2. Zigbee
3. Z-Wave
4. NFC (Near-Field Communication)
5. RFID
6. WiFi – IEEE 802.15.11
7. IEEE 802.15.4 , 4e
8. 2G/3G/LTE
9. Wibro/Mobile WiMax
10.PLC (Power Line Communication)
11.Ethernet
12.What else?

20. RFID stands for Radio-Frequency IDentification
IoT Communication Technologies

21. WiFi IEEE 802.11
Very common
Widely used both in indoor
and outdoor environments
General purpose
Low cost
Highly interoperable
Maybe not a good solution
in some special conditions
IoT Communication Technologies

22. Barcode e QR Code
combining the use of RFID tags with both barcodes
and QR codes allows the consumer to connect to
the IoT with the simple scan of a smartphone or
tablet.
•Low cost
•No technological difficulties
•Several devices can read a barcode
•Starting point for more complex systems
•Example: price comparison, credit card
IoT Communication Technologies

23. Barcode
QR Code
IoT Communication Technologies

24. ZigBee IEEE 802.15.4
•Low cost
•Very long battery life
•Easy to deploy
•Can be used globally
•Secure
•Ideal for WPAN and mesh networks
•Support for multiple network topologies
IoT Communication Technologies

25. 25
Sensor devices are becoming widely available
- Programmable devices
- Off-the-shelf gadgets/tools

26. Top IoT Applications

27. IoT Technologies

28. Source: GSMA

29. General Electric says that a 1%
increase in efficiencies from the
Industrial Internet (part of the IoT)
will have huge savings.

30. Source: GE.

31. Networked
heating systems
Networked
surveillance systems
Connected
vehicles
Smart sensor
platforms
Network
capability of
devices
Low power
consumption
Small form
factor
Energy
harvesting
capability
Wireless
technologies
Applications
Appropriate
cost
Enablers
IP is a key driver of innovation

32. | Basel
Limitations of IPv4
IPv6 Basics
An IPv4 address walks into a bar and says: “Quick, give me a drink. I am exhausted!”

33. Limitations of IPv4
The modern Internet has grown beyond its original intent
21
st
Century Internet Pure IPv4 Implication
Types of Users Researchers, Scientists
Everyone
Encryption, authentication increasingly
important
Number of Hosts Millions Billions Not enough public, unique addresses to
share
Session Duration Always Connected,
Many Hosts
Address depletion. Long lived sessions
result in fewer available addresses
Level of Movement Stationary and Mobile Not designed for mobility beyond the LAN
Network Topology Flat Complex Increasingly complex network design

34. Question
IPv4 addresses are finished.
But how our new IP based devices(smart
phones, tablets and etc.) connect to the
internet as well?

36. | Basel
Capabilities of IPv6
IPv6 Basics
An IPv6 packet walks into a bar. Nobody talks to him.

37. Capabilities of IPv6
• More efficient packet header format
• Globally scalable address space
• Stateless and stateful address configuration
• Standardized support for Internet Security protocols
• Better support for prioritized delivery
• More efficient node discovery
• Extensibility

38. IPv4 vs. IPv6
Feature IPv4 IPv6
Address length 32 bits 128 bits
IPsec header support Optional Required
Prioritized delivery support Some Better
Fragmentation Hosts and routers Hosts only
Packet size 576 bytes 1280 bytes
Link-layer address resolution ARP (broadcast) Multicast Neighbor Discovery
Multicast membership IGMP Multicast Listener
Discovery (MLD)
Router Discovery Optional Required
Uses broadcasts Yes No
Configuration Manual, DHCP Automatic, DHCPv6
DNS name queries Uses A records Uses AAAA records
DNS reverse queries Uses IN-ADDR.ARPA Uses IP6.ARPA

39. IPv6 address space
• 128-bit address space
• 2128
possible addresses
• 340,282,366,920,938,463,463,374,607,431,768,211
,456 addresses (3.4 x 1038
or 340 undecillion)
• 6.65 x 1023
addresses for every square meter of the Earth’s
surface
• 128 bits to allow flexibility in creating a multi-level,
hierarchical, routing infrastructure
• 64-bit subnet prefix and a 64-bit interface identifier
IPv4(232
)contains 4,294,967,296

40. The Internet Engineering Task Force (IETF®
)
Standardization Efforts
The goal of the IETF is to
make the Internet work better.

41. IPv6 over the TSCH mode of IEEE
802.15.4e
6tisch@ietf.org
6tisch

42. Background
Low-power and Lossy Networks (LLNs)
interconnect a possibly large number
of resource-constrained nodes to form a
wireless mesh network
TSCH amendment to IEEE 802.15.4 in 2012
The 6LoWPAN, ROLL and CoRE IETF
Working Groups have defined protocols at
various layers of the protocol stack,
including an IPv6 adaptation layer

46. THING IT
[HW | SW]
THING-BASED
FUNCTION
[Local | Business
models known]
IT-BASED
SERVICE
[Global | Business
models required]
IoT Formula for Success
Example SERVICE: Send ambulance
in case of accident (detected by sensors)
Example FUNCTION:
Drive from A to B
A B
Source: University of St. Gallen, Prof. Dr. Elgar Fleisch

47. 47
More “Things” are being connected
Home/daily-life devices
Business and
Public infrastructure
Health-care
…

48. 48
People Connecting to Things
Motion sensor
Motion sensor
Motion sensor
ECG sensor
Internet

49. 49
Things Connecting to Things
- Complex and heterogeneous
resources and networks

50. 50
Wireless Sensor Networks (WSN)
Sink
node Gateway
Core network
e.g. InternetGateway
End-user
Computer services
- The networks typically run Low Power Devices
- Consist of one or more sensors, could be different type of sensors (or actuators)

51. 51
5151
Future Networks

52. Opportunities
52
Source: http://blog.trentonsystems.com/internet-of-things-crosses-business-personal-boundaries/

53. Technology trend
53

54. Smart product sales
54Source: Siemens, http://www.siemens.com/innovation/apps/pof_microsite/_pof-fall-2012/_html_en/facts-and-forecasts-growth-market-of-the-future.html

55. Global Data Generation
55
- Everyday around 20 quintillion (10^18) bytes of
data are produced (Source:
http://www-01.ibm.com/software/data/bigdata/).
- This data includes textual content (unstructured,
semi-structured, structured) to multimedia
content (images, video and audio), on a variety
of platforms (enterprise, social media, and
sensors).

56. Data Generation
56

57. Byte
Byte : one grain of rice

58. Kilobyte
Byte : one grain of rice
Kilobyte : cup of rice

59. Megabyte
Byte : one grain of rice
Kilobyte : cup of rice
Megabyte : 8 bags of rice

60. Gigabyte
Byte : one grain of rice
Kilobyte : cup of rice
Megabyte : 8 bags of rice
Gigabyte : 3 Semi trucks

61. Terabyte
Byte : one grain of rice
Kilobyte : cup of rice
Megabyte : 8 bags of rice
Gigabyte : 3 Semi trucks
Terabyte : 2 Container Ships

62. Petabyte
Byte : one grain of rice
Kilobyte : cup of rice
Megabyte : 8 bags of rice
Gigabyte : 3 Semi trucks
Terabyte : 2 Container Ships
Petabyte : Blankets Manhattan

63. One ByteExabyte
Byte : one grain of rice
Kilobyte : cup of rice
Megabyte : 8 bags of rice
Gigabyte : 3 Semi trucks
Terabyte : 2 Container Ships
Petabyte : Blankets Manhattan
Exabyte : Blankets west coast states

64. Byte : one grain of rice
Kilobyte : cup of rice
Megabyte : 8 bags of rice
Gigabyte : 3 Semi trucks
Terabyte : 2 Container Ships
Petabyte : Blankets Manhattan
Exabyte : Blankets west coast states
Zettabyte : Fills the Pacific Ocean
Zettabyte

65. Byte : one grain of rice
Kilobyte : cup of rice
Megabyte : 8 bags of rice
Gigabyte : 3 Semi trucks
Terabyte : 2 Container Ships
Petabyte : Blankets Manhattan
Exabyte : Blankets west coast states
Zettabyte : Fills the Pacific Ocean
Yottabyte : A EARTH SIZE RICE BALL!
Yottabyte

66. Hobbyist
Byte : one grain of rice
Kilobyte : cup of rice
Megabyte : 8 bags of rice
Gigabyte : 3 Semi trucks
Terabyte : 2 Container Ships
Petabyte : Blankets Manhattan
Exabyte : Blankets west coast states
Zettabyte : Fills the Pacific Ocean
Yottabyte : A EARTH SIZE RICE BALL!

67. Desktop
Hobbyist
Byte : one grain of rice
Kilobyte : cup of rice
Megabyte : 8 bags of rice
Gigabyte : 3 Semi trucks
Terabyte : 2 Container Ships
Petabyte : Blankets Manhattan
Exabyte : Blankets west coast states
Zettabyte : Fills the Pacific Ocean
Yottabyte : A EARTH SIZE RICE BALL!

68. Hobbyist
Internet
Byte : one grain of rice
Kilobyte : cup of rice
Megabyte : 8 bags of rice
Gigabyte : 3 Semi trucks
Terabyte : 2 Container Ships
Petabyte : Blankets Manhattan
Exabyte : Blankets west coast states
Zettabyte : Fills the Pacific Ocean
Yottabyte : A EARTH SIZE RICE BALL!
Desktop

69. Big Data
Byte : one grain of rice
Kilobyte : cup of rice
Megabyte : 8 bags of rice
Gigabyte : 3 Semi trucks
Terabyte : 2 Container Ships
Petabyte : Blankets Manhattan
Exabyte : Blankets west coast states
Zettabyte : Fills the Pacific Ocean
Yottabyte : A EARTH SIZE RICE BALL!
Hobbyist
Internet
Desktop
The Future!

70. Byte : one grain of rice
Kilobyte : cup of rice
Megabyte : 8 bags of rice
Gigabyte : 3 Semi trucks
Terabyte : 2 Container Ships
Petabyte : Blankets Manhattan
Exabyte : Blankets west coast states
Zettabyte : Fills the Pacific Ocean
Yottabyte : A EARTH SIZE RICE BALL!

71. The number
of Bits of information
stored in the digital
universe is thought to
have exceeded the
number of stars in the
physical universe in
2007.
Source

72. The NSA
is thought to analyze
1.6% of all global
internet traffic –
around 30 petabytes
(30 million gigabytes)
every day.
Source

73. The total amount
of data being
captured and stored
by industry doubles
every 1.2 years.
Source

74. Every minute
we send 204 million
emails, generate 1,8
million Facebook likes,
send 278 thousand
Tweets, and up-load
200,000 photos to
Facebook.
Source

75. Google alone
processes on average
over 40 thousand
search queries per
second, making it over
3.5 billion in a single
day.
Source

76. 76

77. New requirements in enabling technologies
Devices
Connectivity
Platforms
Internet
of Things
Connected things,
products,
services,
systems, etc.
Security
Networks
Apps &
Analytics
Databases
Source:
Machina Research 2014

78. So this brings us to…

79. Big Data isn’t big,
if you know how to
use it.

80. “There were 5 exabytes of
information created
between the dawn of
civilization through 2003,
but that much information
is now created every 2
days.”
Eric Schmidt, of Google, said in 2010

81. “Information is the oil
of the 21st century, and
analytics is the
combustion engine.”
Peter Sondergaard, Gartner Research

82. “You can have data
without information,
but you cannot have
information without
data.”
Daniel Keys Moran, computer
programmer and science fiction author

83. “Big data is not
about the data”
Gary King, Harvard University, making the
point that while data is plentiful and easy to
collect, the real value is in the analytics

84. Big data has been
used to predict crimes
before they happen – a
“predictive policing” trial in
California was able to identify
areas where crime will occur
three times more accurately
than existing methods of
forecasting.
Source

86. Characteristics of Big Data:
1-Scale (Volume)
• Data Volume
– 44x increase from 2009 2020
– From 0.8 zettabytes to 35zb
• Data volume is increasing exponentially
86
Exponential increase in
collected/generated data

87. Characteristics of Big Data:
2-Complexity (Varity)
• Various formats, types, and structures
• Text, numerical, images, audio, video,
sequences, time series, social media
data, multi-dim arrays, etc…
• Static data vs. streaming data
• A single application can be
generating/collecting many types of
data
87
To extract knowledge all these types of
data need to linked together
To extract knowledge all these types of
data need to linked together

88. Characteristics of Big Data:
3-Speed (Velocity)
• Data is begin generated fast and need to be
processed fast
• Online Data Analytics
• Late decisions  missing opportunities
• Examples
– E-Promotions: Based on your current location, your purchase history,
what you like  send promotions right now for store next to you
– Healthcare monitoring: sensors monitoring your activities and body 
any abnormal measurements require immediate reaction
88

89. Some Make it 4V’s
89

92. Read more about
IoT

93. 93

94. Any questions?