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Chapter 11
ADVANCES IN COMPUTING
The ever changing computing needs in various fields paved way to new paradigms of distributed
computing. Advances in computing have become data intensive and network-centric.
Cybernetics, which is the study of interaction between humans and machines, has made major
advances in Artificial intelligence.
Computational Intelligence, is a branch of AI that is helps machine to achieve human intelligence. Soft
computing methods are adopted to achieve this.
Distributed Computing
Distributed computing is the method of processing in which different parts of a program are run
simultaneously on two or more computers that are communicating with each other over a network.
Various distributed computing paradigms are
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Parallel computing
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Grid computing
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Cluster computing
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Cloud computing
The advantages of distributed computing are
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Economical : Distributed computing reduces overall cost
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Speed : As computational load is spread across various nodes speed of execution increases.
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Reliability: distributed systems can function even if one of its node fails
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Scalability: The number of nodes can be increased or decreased as and when the need arises.
Disadvantages are
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Complex: Additional programming required to set up distributed systems
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Security: Information passed around the network may be tracked and used for illegal purposes
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Network dependency : In case of network failure, the entire system becomes unstable.
Parallel computing
Parallel computing is a form of computation in which many calculations are carried out simultaneously.
It operates on the principle that large problems can be divided into small problems, that can be solved
concurrently. In parallel computing there will be many processors that share a common memory. Serial
computing is the conventional computing method where a single processor executes instructions one by
one. Application area: Weather forecasting, nuclear science, aerospace engineering etc.
Difference between parallel and serial computing
Serial Computing
A single processor is used
Parallel Computing
Multiple processors are used with a shared
memory
Aproblem is broken into a series of instructions A problem is divided into modules that can be
solved concurrently.
Instructions are executed sequentially
Instructions from each module executes
simultaneously in different processors.
Grid computing
Grid computing works on the principle of pooled resources over a network. Here different devices used
by different people are connected together to form a single huge powerful computer. This network is
called grid. All devices in this grid will have a program on them that allows the unused resources to be
used by others in the grid. There will be a server that break up processing tasks into independent parts
and sent it to different computers on the grid. When the computer finishes its task the result is sent
back to the server. Its advantage is that it makes better use of existing resources. Slower processing
speed and licensing issues across different serves are the major issues.
Application area: Weather forecasting, disaster management, bio-informatics etc.
Cluster Computing
Clusters are a group of personal computers , storage devices etc. liked together through LAN so as to
work like a powerful single computer. It provides low cost parallel processing and ensures fault
tolerance, ie ensures computational power is always available.
Linux is the common Operating System and it is used in high database applications, e-Commerce etc.
Fault diagnosis is a major issue.
Cloud computing
Cloud computing is a computing model where resources such as computing power, storage , software
etc are provided as services on the internet that can be accessed remotely.
Eg. Web based email accounts. The mails in our inbox are not stored in our computer. The inbox and
software to access it is stored in the cloud, that can be accessed through internet, from anywhere in the
world. Clouds are maintained by cloud service providers. Cloud computing is a subscription based
service. In order to use cloud computing an account with cloud service provider is necessary.
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The services offered by a cloud provider can be catagorised into
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Software as a Service (SaaS)
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Platform as a Service (PaaS)
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Infrastructure as a Service (IaaS)
SaaS : In SaaS model cloud providers install and operate application software in the cloud and cloud
users access the software from cloud clients. This avoids the need for installing and running the
application in user’s computer, thereby reducing cost of buying that software.
For eg: you can open Gmail attachments like Excel, Powerpoint etc even though your computer does not
have Ms Office suite. This is provided by the SaaS Google Docs.
PaaS: A PaaS provider gives subscribers access to the platform they require to design, develop and test
applications over internet. They offer a predefined combination of Os and application servers to meet
manageability and scalability of applications.
Eg: LAMP, XAAMP, Google’s App Engine etc.
IaaS: IaaS provides basic storage and computing capabilities as services over the network. Severs,
Storage systems , networking equipment, data centre space etc are available for customers as services.
Eg: Amazon Web services, NIC etc.
Advantages of cloud computing
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Cost saving: Companies can reduce capital and operational expenditures.
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Flexibility: Flexibility of cloud computing allows usage of extra resources at peak times to meet
user demands.
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Ease of maintenance: Cloud service providers do the system maintenance, thereby reducing
maintenance requirements.
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Mobility: As the system are accessible from anywhere, it provides better productivity.
Disadvantages
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Security and Privacy : Data or program sent over shared and publicly accessible systems, it is
prone to stealing or corrupting.
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Lack of standards: Since clouds have no standards they are not inter-operable
ARTIFICIAL INTELLIGENCE
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The term ARTIFICIAL INTELLIGENCE was coined by John MacCarthy in 1956, which is the science
and engineering of making intelligent machines.
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The central goal of AI is to achieve reasoning, knowledge, planning, learning, communication
(NLP), perception and ability to move and manipulate objects.
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The basic element of all intelligent systems is knowledge.
Alen turing test
The first definition of artificial intelligence was established by Alen Turing. Turing defines intelligent
behavior as the ability to achieve human-level performance in all cognitive tasks, sufficient to fool an
interrogator.Turing Test is the ultimate test to be passed by a machine to be called intelligent.
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To pass Turing test ,a system must possess capabilities such as
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Natural Language Processing (NLP) : Ability to communicate in any one language.
Automatic speech recognition , speech synthesis, machine translation, handwritten
character recognition are the applications that helps it in communicating in one’s own
natural language.
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Knowledge representation: To incorporate human knowledge
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Automated reasoning: to use knowledge to answer question and to draw new
conclusions
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Machine learning: to adapt to new situations and to detect and deduce patterns
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Computer vision: includes abilities like image acquisition, transformation, processing,
analysis, understanding and interpretation.
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Robotic activities: ability to move according to the changing environment.
Computational Intelligence is a subset of AI. Computational intelligence is the study of adaptive
algorithms to facilitate intelligent behavior in complex and changing environment so as to solve real life
problems.CI aims in achieving intelligence through soft computing. Soft computing is the methodology
to develop computers capable of human mind reasoning, that are tolerant of imprecision, uncertainty,
partial truth and approximation.
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Four major paradigms of CI are
1. Artificial Neural Networks( ANN) : ANN models biological neural systems in brain that
performs complex, nonlinear and parallel computing.
2. Evolutionary Computation: Evolutionary Computing is the collective name for a range of
problem–solving techniques based on principles of biological evolution such as natural selection and
genetic inheritance. It is widely used in real-world applications like data mining, fault diagnosis,
classification, scheduling, etc.
3.Swarm Intelligence: SI is the simulation of collective behavior of decentralized, self organized
systems, natural or artificial. It helps in understanding the natural systems like ant colonies, bird
flocking, bacterial growth, fish schooling etc.
4. Fuzzy Systems: A fuzzy system is a control system based on fuzzy logic—a mathematical
system that analyzes analog input values in terms of logical variables. Fuzzy logic allows reasoning with
uncertain facts to infer new facts. Thus fuzzy logic allow the modeling of common sense. Fuzzy systems
are used in automotives to control gear transmission, in home appliances, controlling traffic signals etc.