Cloud Computing Unit-1
Different Computing Paradigms:
Over the years different computing paradigms have been developed and used. In fact
different computing paradigms have existed before the cloud computing paradigm. Let us
take a look at all the computing paradigms below.
1. Distributed Computing :
Distributed computing is defined as a type of computing where multiple computer systems
work on a single problem. Here all the computer systems are linked together and the problem
is divided into sub-problems where each part is solved by different computer systems.
The goal of distributed computing is to increase the performance and efficiency of the system
and ensure fault tolerance.
In the below diagram, each processor has its own local memory and all the processors
communicate with each other over a network.
2. Parallel Computing:
Parallel computing is defined as a type of computing where multiple computer systems are
used simultaneously. Here a problem is broken into sub-problems and then further broken
down into instructions. These instructions from each sub-problem are executed concurrently
on different processors.
Here in the below diagram you can see how the parallel computing system consists of
multiple processors that communicate with each other and perform multiple tasks over a
shared memory simultaneously.
The goal of parallel computing is to save time and provide concurrency.
By: Preetham Paul Socrates P Assistant Professor SDC
,Cloud Computing Unit-1
3. Cluster Computing:
A cluster is a group of independent computers that work together to perform the tasks given.
Cluster computing is defined as a type of computing that consists of two or more independent
computers, referred to as nodes, that work together to execute tasks as a single machine.
The goal of cluster computing is to increase the performance, scalability and simplicity of the
system.
As you can see in the below diagram, all the nodes, (irrespective of whether they are a parent
node or child node), act as a single entity to perform the tasks.
4. Grid Computing:
Grid computing is defined as a type of computing where it is constitutes a network of
computers that work together to perform tasks that may be difficult for a single machine to
handle. All the computers on that network work under the same umbrella and are termed as a
virtual super computer.
The tasks they work on is of either high computing power and consist of large data sets.
All communication between the computer systems in grid computing is done on the ―data
grid‖.
The goal of grid computing is to solve more high computational problems in less time and
improve productivity.
By: Preetham Paul Socrates P Assistant Professor SDC
, Cloud Computing Unit-1
5.Utility Computing:
Utility computing is defined as the type of computing where the service provider provides the
needed resources and services to the customer and charges them depending on the usage of
these resources as per requirement and demand, but not of a fixed rate.
Utility computing involves the renting of resources such as hardware, software, etc.
depending on the demand and the requirement.
The goal of utility computing is to increase the usage of resources and be more cost-efficient.
6. Edge Computing:
Edge computing is defined as the type of computing that is focused on decreasing the long
distance communication between the client and the server. This is done by running fewer
processes in the cloud and moving these processes onto a user’s computer, IoT device or edge
device/server.
The goal of edge computing is to bring computation to the network’s edge which in turn
builds less gap and results in better and closer interaction.
7. Fog Computing:
Fog computing is defined as the type of computing that acts a computational structure
between the cloud and the data producing devices. It is also called as ―fogging‖.
This structure enables users to allocate resources, data, applications in locations at a closer
range within each other.
The goal of fog computing is to improve the overall network efficiency and performance.
By: Preetham Paul Socrates P Assistant Professor SDC
Different Computing Paradigms:
Over the years different computing paradigms have been developed and used. In fact
different computing paradigms have existed before the cloud computing paradigm. Let us
take a look at all the computing paradigms below.
1. Distributed Computing :
Distributed computing is defined as a type of computing where multiple computer systems
work on a single problem. Here all the computer systems are linked together and the problem
is divided into sub-problems where each part is solved by different computer systems.
The goal of distributed computing is to increase the performance and efficiency of the system
and ensure fault tolerance.
In the below diagram, each processor has its own local memory and all the processors
communicate with each other over a network.
2. Parallel Computing:
Parallel computing is defined as a type of computing where multiple computer systems are
used simultaneously. Here a problem is broken into sub-problems and then further broken
down into instructions. These instructions from each sub-problem are executed concurrently
on different processors.
Here in the below diagram you can see how the parallel computing system consists of
multiple processors that communicate with each other and perform multiple tasks over a
shared memory simultaneously.
The goal of parallel computing is to save time and provide concurrency.
By: Preetham Paul Socrates P Assistant Professor SDC
,Cloud Computing Unit-1
3. Cluster Computing:
A cluster is a group of independent computers that work together to perform the tasks given.
Cluster computing is defined as a type of computing that consists of two or more independent
computers, referred to as nodes, that work together to execute tasks as a single machine.
The goal of cluster computing is to increase the performance, scalability and simplicity of the
system.
As you can see in the below diagram, all the nodes, (irrespective of whether they are a parent
node or child node), act as a single entity to perform the tasks.
4. Grid Computing:
Grid computing is defined as a type of computing where it is constitutes a network of
computers that work together to perform tasks that may be difficult for a single machine to
handle. All the computers on that network work under the same umbrella and are termed as a
virtual super computer.
The tasks they work on is of either high computing power and consist of large data sets.
All communication between the computer systems in grid computing is done on the ―data
grid‖.
The goal of grid computing is to solve more high computational problems in less time and
improve productivity.
By: Preetham Paul Socrates P Assistant Professor SDC
, Cloud Computing Unit-1
5.Utility Computing:
Utility computing is defined as the type of computing where the service provider provides the
needed resources and services to the customer and charges them depending on the usage of
these resources as per requirement and demand, but not of a fixed rate.
Utility computing involves the renting of resources such as hardware, software, etc.
depending on the demand and the requirement.
The goal of utility computing is to increase the usage of resources and be more cost-efficient.
6. Edge Computing:
Edge computing is defined as the type of computing that is focused on decreasing the long
distance communication between the client and the server. This is done by running fewer
processes in the cloud and moving these processes onto a user’s computer, IoT device or edge
device/server.
The goal of edge computing is to bring computation to the network’s edge which in turn
builds less gap and results in better and closer interaction.
7. Fog Computing:
Fog computing is defined as the type of computing that acts a computational structure
between the cloud and the data producing devices. It is also called as ―fogging‖.
This structure enables users to allocate resources, data, applications in locations at a closer
range within each other.
The goal of fog computing is to improve the overall network efficiency and performance.
By: Preetham Paul Socrates P Assistant Professor SDC
