TYCS UNIT 1 Cloud Computing
What is Cloud?
▪ The term Cloud refers to a Network or Internet. In other words, we can say that
Cloud is something, which is present at remote location. Cloud can provide
services over public and private networks, i.e., WAN, LAN .
▪ Applications such as e-mail, web conferencing, customer relationship
management (CRM) execute on cloud.
What is Cloud Computing?
▪ Cloud Computing refers to manipulating, configuring, and accessing the
hardware and software resources remotely. It offers online data storage,
infrastructure, and application.
▪ Cloud computing refers to both the applications delivered as services over the
Internet and the hardware and system software in the datacenters that provide
those services.
▪ Cloud computing offers platform independency, as the software is not required
to be installed locally on the PC. Hence, the Cloud Computing is making our
business applications mobile and collaborative.
▪ Cloud computing is a model for enabling ubiquitous, convenient, on-demand
network access to a shared pool of configurable computing resources (e.g.,
networks, servers, storage, applications, and services) that can be rapidly
provisioned and released with minimal management effort or service provider
interaction.
Benefits of Cloud Computing:-
Cloud Computing has numerous advantages. Some of them are listed below -
i. Low Cost: To run cloud technology, users don't require high power computer
& technology as because the application will run on the cloud and not on
users' PC. Itonly required internet connectivity.
ii. Storage capacity: The Cloud storage capacity is unlimited & generally offers a
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TYCS UNIT 1 Cloud Computing
hugestorage capacity of 2000-3000 GBs or more based on the requirement.
iii. Low cost of IT infrastructure: As discussed earlier, the investment will be less if
anorganization uses Cloud technology; even the IT staffs and server engineers
are also not required.
iv. Increase computing power: Cloud servers have a very high-capacity of running
andprocessing tasks as well as the processing of applications.
v. Reduce Software Costs: Cloud minimizes the software costs as users don't
need topurchase software for organizations or every computer.
Characteristics Of Cloud Computing:-
1. On Demand Self Service
Cloud Computing allows the users to use web services and resources on
demand. Onecan logon to a website at any time and use them.
2. Broad Network Access
Since cloud computing is completely web based, it can be accessed from
anywhere andat any time.
3. Resource Pooling
Cloud computing allows multiple tenants to share a pool of resources. One can share
single physical instance of hardware, database and basic infrastructure.
4. Rapid Elasticity
It is very easy to scale the resources vertically or horizontally at any time.
Scaling ofresources means the ability of resources to deal with increasing or
decreasing demand.
The resources being used by customers at any given point of time are
automaticallymonitored.
5. Measured Service
In this service cloud provider controls and monitors all the aspects of cloud
service.Resource optimization, billing, and capacity planning etc. depend on it.
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Distributed System?
A distributed system is a collection of independent computers that appear to the users of the
system as a single coherent system. These computers or nodes work together, communicate over
a network, and coordinate their activities to achieve a common goal by sharing resources, data,
and tasks.
common distributed system architectures:
• Client-Server Architecture:
o In this setup, servers provide resources or services, and clients request them.
Clients and servers communicate over a network.
o Examples: Web applications, where browsers (clients) request pages from web
servers.
• Peer-to-Peer (P2P) Architecture:
o Each node, or “peer,” in the network acts as both a client and a server, sharing
resources directly with each other.
o Examples: File-sharing networks like BitTorrent, where files are shared between
users without a central server.
• Three-Tier Architecture:
o This model has three layers: presentation (user interface), application (business
logic), and data (database). Each layer is separated to allow easier scaling and
maintenance.
o Examples: Many web applications use this to separate user interfaces, logic
processing, and data storage.
• Microservices Architecture:
o The application is split into small, independent services, each handling specific
functions. These services communicate over a network, often using REST APIs or
messaging.
o Examples: Modern web applications like Netflix or Amazon, where different
services handle user accounts, orders, and recommendations independently.
• Service-Oriented Architecture (SOA):
o Similar to microservices, SOA organizes functions as services. However, SOA
typically uses an enterprise service bus (ESB) to manage communication between
services.
o Examples: Large enterprise applications in finance or government, where
different services handle various aspects of business processes.
• Event-Driven Architecture:
o Components interact by sending and responding to events rather than direct
requests. An event triggers specific actions or processes in various parts of the
system.
o Examples: Real-time applications like IoT systems, where sensors trigger actions
based on detected events.
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Example of a Distributed System
Any social media can have its Centralized Computer Network as its Headquarters and computer
systems that can be accessed by any user and using their services will be the Autonomous
Systems in the Distributed System Architecture.
• Distributed System Software: This Software enables computers to coordinate their
activities and to share the resources such as Hardware, Software, Data, etc.
• Database: It is used to store the processed data that are processed by each Node/System
of the Distributed systems that are connected to the Centralized network.
Characteristics of Distributed System
• Resource Sharing: It is the ability to use any Hardware, Software, or Data anywhere in
the System.
• Openness: It is concerned with Extensions and improvements in the system (i.e., How
openly the software is developed and shared with others)
• Concurrency: It is naturally present in Distributed Systems, that deal with the same
activity or functionality that can be performed by separate users who are in remote
locations. Every local system has its independent Operating Systems and Resources.
• Scalability: It increases the scale of the system as a number of processors communicate
with more users by accommodating to improve the responsiveness of the system.
• Fault tolerance: It cares about the reliability of the system if there is a failure in
Hardware or Software, the system continues to operate properly without degrading the
performance of the system.
• Transparency: It hides the complexity of the Distributed Systems to the Users and
Application programs as there should be privacy in every system.
Advantages of Distributed System
Below are some of the advantages of Distributed System:
• Scalability: Distributed systems can easily grow by adding more computers (nodes),
allowing them to handle increased demand without significant reconfiguration.
• Reliability and Fault Tolerance: If one part of the system fails, others can take over,
making distributed systems more resilient and ensuring services remain available.
• Performance: Workloads can be split across multiple nodes, allowing tasks to be
completed faster and improving overall system performance.
• Resource Sharing: Distributed systems allow resources like data, storage, and
computing power to be shared across nodes, increasing efficiency and reducing costs.
• Geographical Distribution: Since nodes can be in different locations, distributed
systems can serve users globally, providing faster access to resources based on location.
Disadvantages of Distributed System
Below are some of the disadvantages of Distributed System:
• Relevant Software for Distributed systems does not exist currently.
• Security possesses a problem due to easy access to data as the resources are shared to
multiple systems.
• Networking Saturation may cause a hurdle in data transfer i.e., if there is a lag in the
network then the user will face a problem accessing data.
• In comparison to a single user system, the database associated with distributed systems is
much more complex and challenging to manage.
• If every node in a distributed system tries to send data at once, the network may become
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overloaded.
Use cases of Distributed System
• Finance and Commerce: Amazon, eBay, Online Banking, E-Commerce websites.
• Information Society: Search Engines, Wikipedia, Social Networking, Cloud Computing.
• Cloud Technologies: AWS, Salesforce, Microsoft Azure, SAP.
• Entertainment: Online Gaming, Music, youtube.
• Healthcare: Online patient records, Health Informatics.
• Transport and logistics: GPS, Google Maps.
Web 1.0, Web 2.0, and Web 3.0
Web 1.0 was all about fetching and reading information. Web 2.0 is all
about reading, writing, creating, and interacting with the end user. It was famously called the
participative social web. Web 3.0 is the third generation of the World Wide Web, and is a
vision of a decentralized web which is currently a work in progress. It is all
about reading, writing, and owning.
What is Web 1.0?
Web 1.0 refers to the first stage of the World Wide Web evolution. Earlier, there were only a few
content creators in Web 1.0 with a huge majority of users who are consumers of content.
Personal web pages were common, consisting mainly of static pages hosted on ISP-run web
servers, or free web hosting services.
In Web 1.0 advertisements on websites while surfing the internet are banned. Also, in Web
1.0, Ofoto is an online digital photography website, on which users could store, share, view, and
print digital pictures. Web 1.0 is a content delivery network (CDN) that enables the showcase
of the piece of information on the websites. It can be used as a personal website. It costs the user
as per pages viewed. It has directories that enable users to retrieve a particular piece of
information. The era of Web 1.0 was roughly from 1991 to 2004.
Four Design Essentials of a Web 1.0 Site Include:
• Static pages.
• Content is served from the server’s file system.
• Pages built using Server Side Includes or Common Gateway Interface (CGI).
• Frames and Tables are used to position and align the elements on a page.
Features of the Web 1.0
• Easy to connect static pages with the system via hyperlinks
• Supports elements like frames and tables with HTML 3.2
• Also has graphics and a GIF button
• Less interaction between the user and the server
• You can send HTML forms via mail
• Provides only a one-way publishing medium
What is Web 2.0?
2004 When the word Web 2.0 become famous due to the First Web 2.0 conference (later known
as the Web 2.0 summit) held by Tim O’Reilly and Dale Dougherty, the term was coined by
Darcy DiNucci in 1999. Web 2.0 refers to worldwide websites which highlight user-generated
content, usability, and interoperability for end users. Web 2.0 is also called the participative
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social web. It does not refer to a modification to any technical specification, but to modify the
way Web pages are designed and used. The transition is beneficial, but it does not seem that
when the changes occur. Interaction and collaboration with each other are allowed by Web 2.0 in
a social media dialogue as the creator of user-generated content in a virtual community. Web 2.0
is an enhanced version of Web 1.0.
Web browser technologies are used in Web 2.0 development, and it includes AJAX and
JavaScript frameworks. Recently, AJAX and JavaScript frameworks have become very popular
means of creating web 2.0 sites.
Features of the Web 2.0
• Free sorting of information permits users to retrieve and classify the information
collectively.
• Dynamic content that is responsive to user input.
• Information flows between the site owner and site users using evaluation & online
commenting.
• Developed APIs to allow self-usage, such as by a software application.
• Web access leads to concerns different, from the traditional Internet user base to a wider
variety of users.
Usage of Web 2.0
The social Web contains several online tools and platforms where people share their
perspectives, opinions, thoughts, and experiences. Web 2.0 applications tend to interact much
more with the end user. As such, the end-user is not only a user of the application but also a
participant in these 8 tools mentioned below:
• Podcasting
• Blogging
• Tagging
• Curating with RSS
• Social bookmarking
• Social networking
• Social media
• Web content voting
What is Web 3.0?
It refers to the evolution of web utilization and interaction which includes altering the Web into a
database, with the integration of DLT (Distributed Ledger Technology blockchain is an
example) and that data can help to make Smart Contracts based on the needs of the individual. It
enables the up-gradation of the backend of the web, after a long time of focusing on the front-
end (Web 2.0 has mainly been about AJAX, tagging, and other front-end user-experience
innovation). Web 3.0 is a term that is used to describe many evolutions of web usage and
interaction among several paths. In this, data isn’t owned but instead shared but still is, where
services show different views for the same web / the same data.
Features of the Web 3.0
• Semantic Web: The succeeding evolution of the Web involves the Semantic Web. The
semantic web improves web technologies in demand to create, share and connect content
through search and analysis based on the capability to comprehend the meaning of words,
rather than on keywords or numbers.
• Artificial Intelligence: Combining this capability with natural language processing, in
Web 3.0, computers can distinguish information like humans to provide faster and more
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relevant results. They become more intelligent to fulfill the requirements of users.
• 3D Graphics: The three-dimensional design is being used widely in websites and
services in Web 3.0. Museum guides, computer games, e-commerce, geospatial contexts,
etc. are all examples that use 3D graphics.
• Connectivity: With Web 3.0, information is more connected thanks to semantic
metadata. As a result, the user experience evolves to another level of connectivity that
leverages all the available information.
• Ubiquity: Content is accessible by multiple applications, every device is connected to the
web, and the services can be used everywhere.
• DLT and Smart Contracts: With the help of DLT, we can have a virtually impossible-
to-hack database from which one can have value to their content and things they can own
virtually, this is the technology that enables a trustless society through the integration of
smart contracts which does not need to have a middle man to be a guarantor to make that
contract occur on certain cause its based on data from that DLT. It’s a powerful tool that
can make the world a far better place and generate more opportunities for everyone on
the internet.
Differences Between the Web 1.0, Web 2.0, and Web 3.0
S.
No. Web 1.0 Web 2.0 Web 3.0
1. Mostly Read-Only Wildly Read-Write Portable and Personal
2. Company Focus Community Focus Individual Focus
3. Home Pages Blogs / Wikis Live-streams / Waves
4. Owning Content Sharing Content Consolidating Content
5. WebForms Web Applications Smart Applications
6. Directories Tagging User behavior
7. Page Views Cost Per Click User Engagement
8. Banner Advertising Interactive Advertising Behavioral Advertising
9. Britannica Online Wikipedia The Semantic Web
10. HTML/Portals XML / RSS RDF / RDFS / OWL
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S.
No. Web 1.0 Web 2.0 Web 3.0
Data of many was
Data was personalized and
11. Data was not Focused. controlled by some
no use of mediatory.
mediatory.
Information sharing is
12. Interaction is the goal. Immersion is the goal.
the goal.
It connects information Focuses on relating
13. It aims to connect people.
as its primary goal. knowledge.
Introduction of web Intelligent web-based
14. Static websites
applications functions and apps
A simpler, more passive
15. An enhanced social Web A semantic web exists.
web.
Web and File Servers, Web 3.0 technologies
AJAX, JavaScript, CSS, and
HTML, and Portals are include blockchain,
16. HTML5 are examples of
technologies connected artificial intelligence, and
related technology.
to Web 1.0. decentralized protocols.
Associated
Technologies
• Web and File
Servers Associated Technologies
• Search Engines • Searching Using
Associated Technologies
(including Semantics
• Frameworks for
AltaVista and • Databases of
Ajax and JavaScript
17. Yahoo!) Information
• Microsoft.NET
• E-mail accounts • Ontologies
• Blogs
(Yahoo!, • Intelligent Digital
• Wikis and others.
Hotmail) Personal Assistants
• Peer-to-Peer File and others.
Sharing (Napster,
BitTorrent) and
others.
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TYCS UNIT 1 Cloud Computing
Parallel Computing :
It is the use of multiple processing elements simultaneously for solving any problem. Problems
are broken down into instructions and are solved concurrently as each resource that has been
applied to work is working at the same time.
Advantages of Parallel Computing over Serial Computing are as follows:
1. It saves time and money as many resources working together will reduce the time and cut
potential costs.
2. It can be impractical to solve larger problems on Serial Computing.
3. It can take advantage of non-local resources when the local resources are finite.
4. Serial Computing ‘wastes’ the potential computing power, thus Parallel Computing
makes better work of the hardware.
Types of Parallelism:
1. Bit-level parallelism –
It is the form of parallel computing which is based on the increasing processor’s size. It
reduces the number of instructions that the system must execute in order to perform a
task on large-sized data.
Example: Consider a scenario where an 8-bit processor must compute the sum of two 16-
bit integers. It must first sum up the 8 lower-order bits, then add the 8 higher-order bits,
thus requiring two instructions to perform the operation. A 16-bit processor can perform
the operation with just one instruction.
2. Instruction-level parallelism –
A processor can only address less than one instruction for each clock cycle phase. These
instructions can be re-ordered and grouped which are later on executed concurrently
without affecting the result of the program. This is called instruction-level parallelism.
3. Task Parallelism –
Task parallelism employs the decomposition of a task into subtasks and then allocating
each of the subtasks for execution. The processors perform the execution of sub-tasks
concurrently.
4. Data-level parallelism (DLP) –
Instructions from a single stream operate concurrently on several data – Limited by non-regular
data manipulation patterns and by memory bandwidth
Why parallel computing?
• The whole real-world runs in dynamic nature i.e. many things happen at a certain time
but at different places concurrently. This data is extensively huge to manage.
• Real-world data needs more dynamic simulation and modeling, and for achieving the
same, parallel computing is the key.
• Parallel computing provides concurrency and saves time and money.
• Complex, large datasets, and their management can be organized only and only using
parallel computing’s approach.
• Ensures the effective utilization of the resources. The hardware is guaranteed to be used
effectively whereas in serial computation only some part of the hardware was used and
the rest rendered idle.
• Also, it is impractical to implement real-time systems using serial computing.
Applications of Parallel Computing:
• Databases and Data mining.
• Real-time simulation of systems.
• Science and Engineering.
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• Advanced graphics, augmented reality, and virtual reality.
Limitations of Parallel Computing:
• It addresses such as communication and synchronization between multiple sub-tasks and
processes which is difficult to achieve.
• The algorithms must be managed in such a way that they can be handled in a parallel
mechanism.
• The algorithms or programs must have low coupling and high cohesion. But it’s difficult
to create such programs.
• More technically skilled and expert programmers can code a parallelism-based program
well.
Difference between Parallel Computing and Distributed Computing:
S.NO Parallel Computing Distributed Computing
Many operations are performed System components are located at different
1.
simultaneously locations
2. Single computer is required Uses multiple computers
Multiple processors perform Multiple computers perform multiple
3.
multiple operations operations
It may have shared or distributed
4. It have only distributed memory
memory
Processors communicate with each Computer communicate with each other
5.
other through bus through message passing.
Improves system scalability, fault tolerance and
6. Improves the system performance
resource sharing capabilities
Difference between Cloud Computing and Distributed Computing :
S.No. CLOUD COMPUTING DISTRIBUTED COMPUTING
Cloud computing refers to providing on Distributed computing refers to solve a
demand IT resources/services like problem over distributed autonomous
server, storage, database, networking, computers and they communicate between
01. analytics, software etc. over internet. them over a network.
In simple cloud computing can be said In simple distributed computing can be said
02. as a computing technique that delivers as a computing technique which allows to
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hosted services over the internet to its multiple computers to communicate and
users/customers. work to solve a single problem.
It is classified into 3 different types such as
It is classified into 4 different types such Distributed Computing Systems, Distributed
as Public Cloud, Private Cloud, Information Systems and Distributed
03. Community Cloud and Hybrid Cloud. Pervasive Systems.
There are many benefits of cloud
computing like cost effective, elasticity There are many benefits of distributed
and reliable, economies of Scale, access computing like flexibility, reliability,
04. to the global market etc. improved performance etc.
Cloud computing provides services such Distributed computing helps to achieve
as hardware, software, networking computational tasks more faster than using a
05. resources through internet. single computer as it takes a lot of time.
The goal of distributed computing is to
The goal of cloud computing is to distribute a single task among multiple
provide on demand computing services computers and to solve it quickly by
06. over internet on pay per use model. maintaining coordination between them.
Some characteristics of cloud computing Some characteristics of distributed
are providing shared pool of computing are distributing a single task
configurable computing resources, on- among computers to progress the work at
demand service, pay per use, same time, Remote Procedure calls and
provisioned by the Service Providers Remote Method Invocation for distributed
07. etc. computations.
Some disadvantage of cloud computing
includes less control especially in the Some disadvantage of distributed computing
case of public clouds, restrictions on includes chances of failure of nodes, slow
available services may be faced and network may create problem in
08. cloud security. communication.
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