Subject: Internet of
IoT Processing Topologies and Types
Module-3
3.1 Data Format
• The Internet is a vast space where huge quantities and varieties of data are generated
regularly and flow freely.
• As of January 2018, there are a reported 4.021 billion Internet users worldwide.
• The massive volume of data generated by this huge number of users
• Data-generating sources, non-human data generation sources such as sensor nodes and
automated monitoring systems further add to the data load on the Internet
• Huge data volume is composed of a variety of data such as e-mails, text documents
(Word docs, PDFs, and others), social media posts, videos, audio files, and images
Figure 1. The various data generating and storage sources connected to the Internet and the
plethora of data types contained within it.
Data can be broadly grouped into two types based on how they can be accessed and
stored:
1) Structured data
2) unstructured data.
3.1.1 Structured Data:
• Text data that have a pre-defined structure
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, Subject: Internet of
• Structured data are associated with relational database management systems (RDBMS)
• Primarily created by using length-limited data fields such as phone numbers, social
security numbers, and other such information
• Even if the data is human or machine generated, these data are easily searchable by
querying algorithms as well as human generated queries.
• This type of data is associated with flight or train reservation systems, banking systems,
inventory controls, and other similar systems
• Structured Query Language (SQL) are used for accessing these data in RDBMS.
• Structured data holds a minor share of the total generated data over the Internet.
3.1.2 Unstructured Data
• All the data on the Internet, which is not structured, is categorized as unstructured.
• Data types have no pre-defined structure and can vary according to applications and
data-generating sources.
• Human-generated unstructured data include text, e-mails, videos, images, phone
recordings, chats, and others.
• Machine-generated unstructured data include sensor data from traffic, buildings,
industries, satellite imagery, surveillance videos, and others.
• Data type does not have fixed formats associated with it, which makes it very difficult
for querying algorithms to perform a look-up.
• Querying languages such as NoSQL are generally used for this data type.
3.2 Importance of Processing in IoT
• The vast amount and types of data flowing through the Internet necessitate the need for
intelligent and resourceful processing techniques.
• This necessity has become even more crucial with the rapid advancements in IoT,
which is laying enormous pressure on the existing network infrastructure globally
• The data to be processed is divided into three types based on the urgency of processing:
1) Very time critical
2) Time critical
3) Normal
1) Very time critical:
• Data from sources, which need immediate decision support, are deemed as very critical.
• Data have a very low threshold of processing latency, typically in the range of a few
milliseconds.
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IoT Processing Topologies and Types
Module-3
3.1 Data Format
• The Internet is a vast space where huge quantities and varieties of data are generated
regularly and flow freely.
• As of January 2018, there are a reported 4.021 billion Internet users worldwide.
• The massive volume of data generated by this huge number of users
• Data-generating sources, non-human data generation sources such as sensor nodes and
automated monitoring systems further add to the data load on the Internet
• Huge data volume is composed of a variety of data such as e-mails, text documents
(Word docs, PDFs, and others), social media posts, videos, audio files, and images
Figure 1. The various data generating and storage sources connected to the Internet and the
plethora of data types contained within it.
Data can be broadly grouped into two types based on how they can be accessed and
stored:
1) Structured data
2) unstructured data.
3.1.1 Structured Data:
• Text data that have a pre-defined structure
10
, Subject: Internet of
• Structured data are associated with relational database management systems (RDBMS)
• Primarily created by using length-limited data fields such as phone numbers, social
security numbers, and other such information
• Even if the data is human or machine generated, these data are easily searchable by
querying algorithms as well as human generated queries.
• This type of data is associated with flight or train reservation systems, banking systems,
inventory controls, and other similar systems
• Structured Query Language (SQL) are used for accessing these data in RDBMS.
• Structured data holds a minor share of the total generated data over the Internet.
3.1.2 Unstructured Data
• All the data on the Internet, which is not structured, is categorized as unstructured.
• Data types have no pre-defined structure and can vary according to applications and
data-generating sources.
• Human-generated unstructured data include text, e-mails, videos, images, phone
recordings, chats, and others.
• Machine-generated unstructured data include sensor data from traffic, buildings,
industries, satellite imagery, surveillance videos, and others.
• Data type does not have fixed formats associated with it, which makes it very difficult
for querying algorithms to perform a look-up.
• Querying languages such as NoSQL are generally used for this data type.
3.2 Importance of Processing in IoT
• The vast amount and types of data flowing through the Internet necessitate the need for
intelligent and resourceful processing techniques.
• This necessity has become even more crucial with the rapid advancements in IoT,
which is laying enormous pressure on the existing network infrastructure globally
• The data to be processed is divided into three types based on the urgency of processing:
1) Very time critical
2) Time critical
3) Normal
1) Very time critical:
• Data from sources, which need immediate decision support, are deemed as very critical.
• Data have a very low threshold of processing latency, typically in the range of a few
milliseconds.
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