Iot M0dule 1

CONVERGENCE OF IT AND OT
 Until recently, information technology (IT) and operational technology (OT) have
for the most part lived in separate worlds.
 IT supports connections to the Internet along with related data and technology
systems and is focused on the secure flow of data across an organization.
 OT monitors and controls devices and processes on physical operational systems.
 These systems include assembly lines, utility distribution networks, production

facilities, roadway systems, and many more.
 Typically, IT did not get involved with the production and logistics of OT
environments.
 Management of OT is tied to the company.

Table below highlights some of the differences between IT and OT
networks and their various challenges.
IoT Network Architecture and Design
The unique challenges faced by IoT networks and how these challenges have driven new architectural
models.
 Drivers Behind New Network Architectures

 Comparing IoT Architectures.
 A Simplified IoT Architecture
 The Core IoT Functional Stack
 IoT Data Management and Compute Stack
DRIVERS BEHIND NEW NETWORK ARCHITECTURES

This begins by comparing how using an architectural blueprint to construct a house is similar to the
approach we take when designing a network.
 Take a closer look at some of the differences between IT and IoT networks, with a focus on the IoT
requirements that are driving new network architectures, and considers what adjustments are needed.
COMPARING IOT ARCHITECTURES
The oneM2M IoT Standardized Architecture:
In an effort to standardize the rapidly growing field of machine-to-machine (M2M)

communications, the European Telecommunications Standards Institute (ETSI) created the
M2M Technical Committee in 2008.
The goal of this committee was to create a common architecture that would help accelerate
the adoption of M2M applications and devices.
Over time, the scope has expanded to include the Internet of Things.
One of the greatest challenges in designing an IoT architecture is dealing with the
heterogeneity of devices, software, and access methods.
By developing a horizontal platform architecture, oneM2M is
developing standards that allow interoperability at all levels of the IoT
stack
The oneM2M architecture divides IoT functions into three major
domains:
 The application layer
 The services layer
 The network layer
Applications layer:
The oneM2M architecture gives major attention to connectivity
between devices and their applications.
This domain includes the application-layer protocols and attempts to

standardize northbound API definitions for interaction with business
intelligence (BI) systems.
Services layer:
This layer is shown as a horizontal framework across the vertical industry
applications.
At this layer, horizontal modules include the physical network that the IoT
applications run on, the underlying management protocols, and the hardware.
Network layer:
 This is the communication domain for the IoT devices and endpoints.
 It includes the devices themselves and the communications network that links
them.
Embodiments of this communications infrastructure include wireless mesh

technologies, such as IEEE 802.15.4, and wireless point-to-multipoint systems,
such as IEEE 801.11ah.
A SIMPLIFIED IOT ARCHITECTURE:
THE CORE IOT FUNCTIONAL STACK
 IoT networks are built around the concept of “things,” or smart objects performing functions and
delivering new connected services.
 From an architectural standpoint, several components have to work together for an IoT network to be
operational:
 “Things” layer
 Communications network layer
 Access network sublayer
 Gateways and backhaul network sublayer
 Network transport sublayer
 IoT network management sublayer
 Application and analytics layer
 The core IOT functional stack is divided in to 3 layers

1. Layer-1: Things
2.Layer-2:Communication Network layer
3.Layer-3:Applications layer
information about smart objects.
One architectural classification could be:
 Battery-powered or power-connected: This classification is based on

whether the object carries its own energy supply or receives
continuous power from an external power source.
 Mobile or static: This classification is based on whether the “thing”

should move or always stay at the same location. A sensor may be
mobile because it is moved from one object to another or because it is
attached to a movin
 Low or high reporting frequency:
• This classification is based on how often the object should report
monitored parameters.
• A rust sensor may report values once a month. A motion sensor may
report acceleration several hundred times per second.
 Simple or rich data: This classification is based on the quantity of
data exchanged at each report cycle
 Report range: This classification is based on the distance at which the
gateway is located. For example, for your fitness band to
communicate with your phone, it needs to be located a few meters
away at most.
 Object density per cell: This classification is based on the number of
smart objects (with a similar need to communicate) over a given area,
connected to the same gateway.
Layer-2: Communication Network Layer
Once you have determined the influence of the smart object form
factor over its transmission capabilities (transmission range, data
volume and frequency, sensor density and mobility), you are ready to
connect the object and communicate.
Compute and network assets used in IoT can be very different from
those in IT environments. The difference in the physical form factors
between devices used by IT and OT is obvious even to the most casual
of observers. What typically drives this is the physical environment in
which the devices are deployed. What may not be as inherently
obvious, however, is their operational differences. The operational
differences must be understood in order to apply the correct handling
to secure the target assets.
 Access Network Sublayer
• There is a direct relationship between the IoT network technology you
choose and the type of connectivity topology this technology allows
• Each technology was designed with a certain number of use cases in

mind (what to connect, where to connect, how much data to
transport at what interval and over what distance).
• These use cases determined the frequency band that was expected to
be most suitable, the frame structure matching the expected data
pattern (packet size and communication intervals), and the possible
topologies that these use cases illustrate.
• One key parameter determining the choice of access technology is
the range between the smart object and the information collector.
Below figure lists some access technologies you may encounter in the
IoT world and the expected transmission distances.
Range estimates are grouped by category names that illustrate the environment
or the vertical where data collection over that range is expected. Common groups
are as follows:
PAN (personal area network): Scale of a few meters. This is the personal space
around a person. A common wireless technology for this scale is Bluetooth.
HAN (home area network): Scale of a few tens of meters. At this scale, common
wireless technologies for IoT include ZigBee and Bluetooth Low Energy (BLE).
NAN (neighborhood area network): Scale of a few hundreds of meters. The term
NAN is often used to refer to a group of house units from which data is collected.
 FAN (field area network): Scale of several tens of meters to several hundred
meters. FAN typically refers to an outdoor area larger than a single group of house
units. The FAN is often seen as “open space” (and therefore not secured and not
controlled).
 LAN (local area network): Scale of up to 100 m. This term is very common in
networking, and it is therefore also commonly used in the IoT space when
standard networking technologies (such as Ethernet or IEEE 802.11) are used.
 Similar ranges also do not mean similar topologies. Some technologies
offer flexible connectivity structure to extend communication possibilities:
• Point-to-point topologies
• Point-to-multipoint
Comparison of the main solutions from an architectural angle:
Layer 3: Applications and Analytics Layer
Once connected to a network, your smart objects exchange information

with other systems.
 As soon as your IoT network spans more than a few sensors, the power
of the Internet of Things appears in the applications that make use of
the information exchanged with the smart objects.
Analytics Versus Control Applications:
• Analytics application:
- collects data from multiple smart objects
- processes the collected data
- displays information resulting from the data that was processed
application processes
Control application:
- controls the behavior of the smart object or the behavior of an
object related to the smart object.
- used for controlling complex aspects of an IoT network with a
logic that cannot be programmed inside a single IoT object
IOT DATA MANAGEMENT AND COMPUTE STACK
This model also has limitations, As data volume, the variety of objects
connecting to the network, and the need for more efficiency increase,
new requirements appear, These new requirements include the
following:
 Minimizing latency:
 Conserving network bandwidth:
 Increasing local efficiency: Collecting and securing data across a wide
geographic area with different environmental conditions may not be
useful. The environmental conditions in one area will trigger a local
response independent from the conditions of another site hundreds
of miles away.
Data management and compute stack are divided in to 3 layers
• The edge layer

• The fog layer
• The cloud layer
Fog Computing:
• Fog computing is a decentralized computing infrastructure in which
data, compute , storage and applications are located somewhere
between the data source and the cloud.
Edge Computing:
• Edge computing is also called “mist” computing.
• If clouds exit in the sky ,and fog sits near the ground then mist is what
actually sits on the ground.
• Thus, the concept of mist is to extend fog to the furthest point

possible, right into the IoT endpoint device itself.
The Hierarchy of Edge, Fog, and Cloud

Iot M0dule 1

Uploaded by

Copyright:

Available Formats

Iot M0dule 1

Uploaded by

Document Information

Original Title

Copyright

Available Formats

Share this document

Share or Embed Document

Sharing Options

Did you find this document useful?

Is this content inappropriate?

Copyright:

Available Formats

Iot M0dule 1

Uploaded by

Copyright:

Available Formats

CONVERGENCE OF IT AND OT

 OT monitors and controls devices and processes on physical operational systems.

 These systems include assembly lines, utility distribution networks, production

 Management of OT is tied to the company.

 Drivers Behind New Network Architectures

DRIVERS BEHIND NEW NETWORK ARCHITECTURES

In an effort to standardize the rapidly growing field of machine-to-machine (M2M)

This domain includes the application-layer protocols and attempts to

Embodiments of this communications infrastructure include wireless mesh

 The core IOT functional stack is divided in to 3 layers

One architectural classification could be:

 Battery-powered or power-connected: This classification is based on

 Mobile or static: This classification is based on whether the “thing”

• Each technology was designed with a certain number of use cases in

Once connected to a network, your smart objects exchange information

• The edge layer

• Edge computing is also called “mist” computing.

• Thus, the concept of mist is to extend fog to the furthest point

You might also like