VIRTUALIZATION AND CLOUD COMPUTING 37

Running Head: VIRTUALIZATION AND CLOUD COMPUTING
VIRTUALIZATION AND CLOUD COMPUTING
Name of the Student
Name of the University

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Table of Contents
Chapter 1: Introduction..............................................................................................................4
1.1. Background.....................................................................................................................4
1.2.Motivation........................................................................................................................4
1.3. Research Aim and Objectives.........................................................................................5
1.4. Research Questions.........................................................................................................6
1.5. Research Methodology....................................................................................................6
1.6. Research Outlines............................................................................................................7
1.7. Conclusion.......................................................................................................................7
Chapter 2: Description...............................................................................................................9
2.1. IaaS Software..................................................................................................................9
2.1.1. Amazon Services....................................................................................................11
2.1.2. Access Credentials.................................................................................................12
2.2. MapReduce and Apache Hadoop..................................................................................13
2.2.1. MapReduce............................................................................................................13
2.2.2. Apache Hadoop......................................................................................................13
2.2.3. Apache Hadoop by an Example.............................................................................13
Chapter 3: Literature Review...................................................................................................15
3.1. Introduction...................................................................................................................15
3.2. Background data on Cloud Computing.........................................................................15

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3.3. Amazon Simple Storage Service...................................................................................17
3.4. MapReduce Functions effort-based..............................................................................20
3.5. Motivation of the Project..............................................................................................21
3.6. Conclusion.....................................................................................................................21
Chapter 4: Design Parameters & Analysis...............................................................................23
4.1. Autoscalable AMIs........................................................................................................23
4.1.1. Requirements..........................................................................................................24
4.1.2. Meeting the Requirements.....................................................................................26
4.2. Hadoop Load Monitoring..............................................................................................28
4.2.1. Heartbeat................................................................................................................29
4.2.2. System Metrics.......................................................................................................29
4.2.3. Ganglia...................................................................................................................29
4.2.4. Amazon CloudWatch.............................................................................................30
4.2.5. Conclusion..............................................................................................................30
Chapter 5: Evaluation...............................................................................................................32
5.1. Generating Test Load....................................................................................................32
5.1.1. HDFS Synthetic Load Generator...........................................................................32
5.1.2. Apache Hadoop Sort Benchmark...........................................................................32
5.1.3. Identifying Relevant Metrics..................................................................................33
5.2. Autoscaling Framework................................................................................................33
5.2.1. Load Average Autoscaling.....................................................................................33

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5.2.2 Amazon AutoScaling..............................................................................................33
5.2.3. Custom Scaling Framework...................................................................................34
5.2.4. Scaling the Cluster Down.......................................................................................34
5.2.5. Apache Hadoop and Cluster Changes....................................................................34
Chapter 6: Conclusion, Recommendation and Future Works..................................................36
6.1. Conclusion.....................................................................................................................36
6.2. Recommendation for Further Research........................................................................37
6.3. Future Scope..................................................................................................................39
References................................................................................................................................40

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Chapter 1: Introduction
1.1. Background
Cloud computing has been used all over the world because of the versatility and
flexibleness for Data storing and transferring the data keeping required secrecy. This
technology provides demanded IT products and a service, where virtualization has a major
role to play, that is distributes computing on internet and delivery of computer service
provided over internet [94 p.164]. Virtualization in Cloud Computing provides services to the
cloud clients. This is a brand new concept of business paradigm that has its basic concept in
multi-tenancy, virtualization and shared infrastructure. The concept of IT directs to the
configuring, manipulating and accessing of online applications, offering online storage,
infrastructure and application. It is based of computing resources, combination of software
and hardware which are delivered as network service [81]. Deployment Models and Service
Models are two working model for cloud computing. Service model is also called the
reference model. Service model is divided in to IaaS, PaaS and Saas service cloud.
1.2. Motivation
Cloud computing and virtualization startups have several reasons to move from an
intranet based, models dependent of capital-purchase of infrastructure in IT to some cloud-
based service and utility style demand [10]. This manages the shifting computing
requirements by giving better flexibility in the service provided to the organization. The
cloud based infrastructure is much more versatile from both service and security perspective.
Scalability in cloud computing provides greater flexibility by managing the shifting
computer in requirements in the services they have purchased. This is a more versatile service
in terms of scalability than in local, intranet-based infrastructure [14]. Reliability in the terms

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where the cloud vendors creates greater redundancy in the system than the organization can
help in building onto the intranet, the cloud vendor hence spreads the infrastructure
investment price across entire base of the customers allocating necessary resources [59].
Virtualization since the cloud-based IT infrastructure can be geographically dislocated and
virtualized. It infrastructure startups have been freed from being considered as the physical
location of its data centers and business operations decisions. Affordability within the
traditional infrastructure startups is generally not received. Then marginal cost provided to
the cloud computing features like enhancement of security or many other unaffordable
services are offered for free to the startups using the cloud computing options [95 p. 169].
There are even security options are provided and somewhat are still required in the
cloud services: User data hiding from other users (individual or organization) of the same
cloud service, securing the data from the cloud provider itself, securing and hiding
computation within several servers and securing the computation between unauthorized and
unreliable parties [3].
1.3. Research Aim and Objectives
Here, in this report we are going to discuss the IaaS approaches to migrating in cloud
based organization database to the cloud, an approach to migrating database to the cloud
service. Discussing the advantages and disadvantages of each approach and recommend with
reason why this approach has been selected. Discussing further optimizing the resources of
the compute by allocating it and considering the dynamic processing workload deserves
investigation and finally the MapReduce programming model supporting that distributes
computing large data sets on clusters of computing resources.

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1.4. Research Questions
1) Optimizing resources that have been allocated and then considering dynamic
processing workload deserves investigation.
2) An Infrastructure used for the scalability of computing resources.
3) Effective sentiment analysis of twitter data by using map reduce programming
4) Does the MapReduce program model supports the distribution of large dataset
computing on the computer resources of cluster level?
1.5. Research Methodology
Cloud computing has been spoken as a vital topic because of the innovative
implementation and approach. The most vital point about cloud computing was that, there
was a presence of redefined computing that could be included in anything that people do or
want to do. There is a consistent discussion on cloud computing such that to represent a shift
in paradigm. In this chaptermain focus point is the implementation of specific procedure and
framework which would be used in presence of the research work [46].Ones the security
issue relate aspect would be resolved any other aspects are resolved, the cloud computing
could enable the enterprise forexpandsion. Expansion can be in various fields such as its
infrastructure, outsource the whole infrastructure, resulting in a better flexibility, a wider
choice of resources related to computing and significant cost saving.What appears as a
emerging is the taxonomy of cloud computing includes: infrastructure as a service
(INFRASTRUCTURE AS A SERVICE); platform as a service (PLATFORM AS A
SERVICE) and software as a service (SOFTWARE AS A SERVICE) [9].Consideration such
as data privacy, network performance, security and economics are likely to be a donating
sector in both within the organization and outside the organization. Cloud computing has
gained acceptance and popularity. There are many concepts through which cloud computing
can be related.

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1.6. Research Outlines
The two types of research approaches are Inductive and deductive. The planning and
framing out the appropriate theories is the main function of inductive approach, this helps in
the fulfillment of the main objectives of the approach. Whereas, in the deductive approach the
research support are generally conducted. Hence, the research theories are based on the
previously studied theories and models [6].
At first the research subject has been covered by the researcher and then the
researcher aims at planning and framing the exact model and theory related to previous study.
The main aim of the exploratory design of research is to evaluate different context of the area
in which research is to be done. The researcher adopts the inductive approach and then
divides the research work into various parts. According to the data that could be defined in
the terms of information sets, can be considered to be useful and relevant to the research.
According to inductive approach of research, it has an effect over a longer time period [28].
Therefore, these collection of information can be utilized in the particular study is one of the
most significant aspect conduct any particular work of research.
In the case of deductive approach the procedure of comparison are detected and are
compared over the researches theory and hence frames new models or theories accordingly
[16].This had stated that exploratory design usage does not ensure assurance may or may not
be addressed of the conclusive solutions at the end of the research in particular.
1.7. Conclusion
In this chapter, we have discussed the basic concept of cloud computing and
virtualization along with the need and requirement of this cloud services. Virtualization in
Cloud Computing provides services to the cloud clients. This is a brand new concept of
business paradigm which is based on the concept of multi-tenancy, virtualization and shared