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IoT Enabling Technologies
Different technologies together
enable development of IoT applications. The IoT enabling technologies are:
●
Wireless Sensor Networks
●
Cloud Computing
●
BigData Analytics
● Communication Protocols
● Embedded Systems
A Wireless Sensor Network (WSN) is
a collection of devices which communicate through wireless channels. A WSN
consists of distributed devices with sensors which are used to monitor the
environmental and physical conditions.
A WSN consists of a number of end
nodes, routers and coordinators. End nodes can also act as routers. A
coordinator collects data from all the nodes and is connected to Internet user.
Examples of WSNs used in IoT
systems:
● Indoor air quality monitoring systems
● Soil moisture monitoring systems
● Surveillance systems
● Smart grids
● Structural health monitoring systems
Public cloud is generally
maintained by the cloud service provider. The management of the resources is
taken care by the cloud service provider. In a private cloud all the resources
are used by a single organization. Such organization has the complete control
on the cloud and can follow all the necessary regulations. Private cloud
offeres greater flexibility when compared to the public cloud.
A community cloud is one whose
resources are shared by two or more companies having shared goals. Such clouds
are generally used for conducting collaborated research. A combination of the
previous three clouds is a hybrid cloud. Big companies generally use hybrid
cloud. The companies generally store the sensitive data in the private cloud
and other non-sensitive data in the public cloud. These four types of cloud
deployments are summarized in the below figure.
Examples of WSNs used in IoT systems:
● Weather monitoring systems
● Indoor air quality monitoring
systems
● Soil moisture monitoring systems
● Surveillance systems
● Smart grids
● Structural health monitoring
systems
Cloud computing is a computing
model in which applications and services are delivered over Internet. The
resources provisioned by cloud can be compute, networking or storage. Cloud
allows the users to access resources based on utility model. The characteristics
of cloud computing are:
● On
demand: The resources
in the cloud are available based on the traffic. If the incoming traffic
increases, the cloud resources scale up accordingly and when the traffic
decreases, the cloud resources scale down accordingly.
● Autonomic: The resource provisioning in the
cloud happens with very less to no human intervention. The resources scale up
and scale down automatically.
● Scalable: The cloud resources scale up and
scale down based on the demand or traffic. This property of cloud is also known
as elasticity.
● Pay-per-use: On contrary to traditional
billing, the cloud resources are billed on pay-per-use basis. You have to pay
only for the resources and time for which you are using those resources.
● Ubiquitous: You can access the cloud
resources from anywhere in the world from any device. All that is needed is
Internet. Using Internet you can access your files, databases and other
resources in the cloud from anywhere.
Cloud computing offers three basic
service models using which users can subscribe to cloud resources. These
service models are:
● Infrastructure-As-A-Service (IAAS)
● Platform-As-A-Service (PAAS)
● Software-As-A-Service (SAAS)
These three service models can be
illustrated as shown below. IAAS model provides the core infrastructure to
companies for building their own applications. This core infrastructure
includes servers, storage, networking, etc. PAAS model offers development
runtimes for the users to build and deploy their application. SAAS model offers
already developed and deployed applications for the users to use. Examples of
SAAS offerings are Gmail, Facebook, DropBox, YouTube, etc.
Cloud computing supports four basic deployment models. These models differ in the way how the cloud is built and who are using the resources in the cloud. The four cloud deployment models are:
● Public cloud
● Private cloud
● Community cloud
● Hybrid cloud
In a public cloud the resources are shared between several users. Public cloud is generally maintained by the cloud service provider. The management of the resources is taken care by the cloud service provider. In a private cloud all the resources are used by a single organization. Such organization has the complete control on the cloud and can follow all the necessary regulations. Private cloud offeres greater flexibility when compared to the public cloud.
A community cloud is one whose
resources are shared by two or more companies having shared goals. Such clouds
are generally used for conducting collaborated research. A combination of the
previous three clouds is a hybrid cloud. Big companies generally use hybrid
cloud. The companies generally store the sensitive data in the private cloud
and other non-sensitive data in the public cloud.
BigData is a collection of data
coming from various types of sources. The data is often huge which cannot be
handled by the traditional databases and data warehouses. BigData is often
characterized by six Vs. They are:
● Volume:
Refers to the huge volume of data
aggregated from various sources.
● Variety: Refers to different types of
data. Data can be structured, semi-structured or unstructured.
● Velocity: Refers to the speed at which the
data is generated. Now-a-days the amount of data available on the Internet per
minute is several peta bytes or even more.
● Veracity: Refers to the degree to which the
data can be trusted. If the data collected is incorrect or has manipulated or
wrong values, the analysis of such data is useless.
● Value: Refers to the business value of
the collected. Even though we have huge amount of data, but it is not useful
for gaining profits in the business, such data is useless.
● Variability: Refers to the ways in which the
big data can be used and formatted.
The data analytics framework
consists of six steps namely: collection, cleaning, integration, analysis,
visualization and alerting. These six steps can be summarized as shown in the
below figure.
IoT Enabling
Technologies: Communication Protocols
Communications protocols form the
backbone for IoT systems. They allow devices to communicate with each other.
Protocols define the data exchange formats, data encoding and addressing
schemes for devices. Protocols also provide flow control, error control, and
other functions.
Embedded system can be imagined as
computing hardware with software embedded in it. An embedded system can be an
independent system or it can be a part of another larger system.
An embedded system is a
microcontroller or microprocessor based system which is designed to perform a
specific task. The key components include microcontroller/micrprocessor,
memory, networking units, I/O, and storage. It runs Real-Time Operating Systems
(RTOS).
An embedded system has three
components. They are:
● Hardware
● Software
● Real Time Operating system (RTOS)
that supervises the application software and provide mechanism to let the
processor run a process as per schedule by following a plan to control the
latencies
The characteristics of an embedded
system are:
● Single-functioned
● Tightly constrained
● Reactive and Real time
● Memory
● Connected
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