NEW HORIZON COLLEGE OF ENGINEERING (ISO- 9001:2000

VISVESVARAYA TECHNOLOGICAL UNIVERSITY

“Jnana Sangama”, Belagavi – 590 018

A PROJECT REPORT ON

“Effective Resource Utilization Algorithm for Load Balancing in Cloud

Computing System”

Submitted in partial fulfillment for the award of the degree of

MASTER OF TECHNOLOGY

IN

COMPUTER SCIENCE AND ENGINEERING

BY

VENUGOPAL R

(1NH14SCS72)

Under the guidance of Ms. SURIYA REFAI BEGUM

(Sr. Assistant Professor, Dept. of CSE, NHCE)

DEPARTMENT OF COMPUTER SCIENCE AND

ENGINEERING

NEW HORIZON COLLEGE OF ENGINEERING

(ISO-9001:2000 certified, Accredited by NAAC ‘A’ ,

Permanently affiliated to VTU)

Outer Ring Road,Panathur Post, Near Marathalli,

Bangalore – 560103

ABSTRACT

Cloud computing is an emerging technology and becoming more popular. The number of

users in the cloud are increasing day by day, due to this high demand the load is becoming

more. The emerging technological demands of users call for expanding service model which

avoids problem of purchasing and maintaining IT infrastructure and supports for

computation-intensive services. This has directed to the development of a new computing

model termed Cloud Computing. In cloud computing, the computing resources are distributed

in various data centres worldwide and these resources are offered to the customers on demand

on a pay as usage basis. Currently, due to the increased usage of cloud, there is a tremendous

increase in workload. Though there are many load balancing schemes existing, still there is a

requirement for better load balancing algorithm that can utilize the cloud resources efficiently

and to minimize the response time. So this project proposes an efficient load balancing

algorithm to achieve effective resource utilization and minimizes the response time.

i

ACKNOWLEDGEMENT

A project work is a job of great enormity and it cannot be accomplished by an individual all

by them. Eventually I am grateful to a number of individuals whose professional guidance,

assistance and encouragement have made it a pleasant endeavor to undertake this project.

I have a great pleasure in expressing my deep sense of gratitude to founder Chairman, Dr.

Mohan Manghnani for having provided me with a great infrastructure and well-furnished

labs.

I take this opportunity to express my profound gratitude to the Principal, Dr. Manjunatha

for his constant support and encouragement.

I am grateful to Dr. Prashanth C.S.R, Dean Academics, Professor and Head of

Department CSE, New Horizon College of Engineering, Bangalore for his unfailing

encouragement and suggestion, given to me in the course of my project work.

I would like to express my heart full thanks to my guide Ms. Suriya Refai Begum, Senior

Assistant Professor, Dept. of CSE, New Horizon College of Engineering, Bangalore who

has always guided me in all aspects, way till its successful completion.

I would like to express my thanks to coordinator Ms. N Deepika, Assistant Professor, Dept.

of CSE, New Horizon College of Engineering, Bangalore who has always guided me in

detailed technical aspects during my project completion.

I am grateful to my Parents and Friends for their encouragement and support towards the

successful completion of my Post-Graduation.

VENUGOPAL R

(1NH14SCS72)

ii

TABLE OF CONTENTS

Sl. No. Title Pg. No.

ABSTRACT

ACKNOWLEDGEMENT

CONTENTS

LIST OF FIGURES

LIST OF TABLES

i

ii

iii

iv

v

1 Chapter 1 Introduction

1.1 General Information

1.1.1 Cloud Service Models

1.1.2 Cloud Enabling Technologies

1.1.3 Cloud Optimized Storage

1.1.4 Advantages of Cloud Computing

1.1.5 Disadvantages of Cloud Environment

1.1.6 Virtualization

1.1.7 Simulation is important for Cloud Computing

1.1.8 Introduction about CloudSim

1.1.9 CloudSim Architecture

1.2 Existing System

1.3 Proposed System

1.4 Flow of the Project

1.5 Summary

1

1

2

3

4

4

5

8

9

11

11

12

13

13

13

Chapter 2 Literature Survey

2.1 Introduction

2.2 Summary

14

14

14

3 Chapter 3 System Requirement Specification

3.1 Introduction

3.2 System Requirements

3.1.1 Functional Requirements

3.1.2 Non Functional Requirements

3.3 Summary

19

19

20

20

20

21

4

Chapter 4 System Architecture

4.1 Introduction

4.2 System Architecture

4.3 Summary

iii

22

22

22

23

5

Chapter 5 Low Level Design

5.1 Introduction

5.2 Data Flow Diagram

5.3 Use Case Diagram

5.4 Sequence Diagram

5.5 Summary

24

24

25

26

27

6 Chapter 6 Implementation

6.1 Introduction

6.2 Modules

6.1.1 Cloud Initialization

6.1.2 Virtual Machine Creation and Clustering

6.1.3 Task Creation and Assign

6.1.4 Task Scheduling

6.3 Summary

28

28

28

28

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29

29

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7 Chapter 7 Testing

7.1 Introduction

7.2 Testing Process

7.3 Test Cases

7.4 Summary

31

31

31

32

36

8 Chapter 8 Results 37

8.1 Results 37

9 Chapter 9 Conclusion 51

References

Appendix A Paper Published

Appendix B Plagiarism Report

iv

LIST OF FIGURES

1. Fig 1.1 Cloud deployment model 3

2. Fig 1.2 Enabling technologies 5

3. Fig 1.3 Two tiered architecture for internet application 8

4. Fig 1.4 Features of CloudSim 10

5. Fig 4.1 System architecture 22

6. Fig 5.1 Data flow diagram level 0 24



9. Fig 5.4 Use case diagram 26

10. Fig 5.5 Sequence diagram 27

11. Fig 8.1 Main controller 37

12. Fig 8.2 Create virtual machines 38

13. Fig 8.3 Updated VM details 39

14. Fig 8.4 Updated VM details to main controller 40

15. Fig 8.5 Created cluster 41

16. Fig 8.6 Assign virtual machine to cluster 42

17. Fig 8.7 Create number of tasks 43

18. Fig 8.8 Updated task details 44

19. Fig 8.9 Assign tasks to cluster 45

20. Fig 8.10 Task scheduling and processing 46

21. Fig 8.11 Tasks waiting in queue to process 47

22. Fig 8.12 Updated main controller details 48

23. Fig 8.13 Resource utilization graph 49

24. Fig 8.14 Minimize response time graph 50

v

LIST OF TABLES

1. Table 1 Test Case 1 32









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Effective Resource Utilization Algorithm for Load Balancing in Cloud Computing System

M.Tech, Dept of CSE, NHCE 2015-2016 Page 1

CHAPTER 1

INTRODUCTION

1.1 GENERAL INFORMATION

Cloud computing strategy offers customers where IT base like server, programming, storage

and stage for creating applications can be rapidly provisioned and discharged as required on a

pay as utilization premise contingent on their necessities. Cloud computing is a sort of parallel

and circulated framework consisting of a gathering of interconnected and virtualized computers

that are progressively provisioned as computing assets in view of administration level

agreements set up through transaction between the administration supplier and clients.

Fundamentally cloud computing gives taking after sorts of administration models

Software as a Service (SaaS) model, where clients can ask for software, use it and pay

just for the span of time it was utilized, rather than acquiring, introducing and keeping up

on their nearby machine. E.g. Google Docs.

Platform as a Service (PaaS) model, where complete assets expected to plan create,

testing, convey and facilitating an application are given as administrations without

burning through cash for buying and keeping up the servers, storage and programming.

E.g. Google App Engine.

Infrastructure as a Service (IaaS) model, where frameworks like a virtualized server,

memory, and capacity are given as administrations. E.g. Amazon Elastic Compute (EC2)

and Simple Storage Service (S3).

Cloud Computing has the accompanying resources:

Clients can scale up and downsize the assets powerfully as required.

Clients can pay just for how much the assets were utilized.

Administration supplier completely deals with the service.

Clients no more need to worry about buy, establishment, and upkeep of server and

programming upgrades.

No speculation on server, stockpiling, programming and permitting.

Clients can get to cloud from anyplace with a web connection.



At present, cloud computing is experiencing a few difficulties like security, Quality of

Service, load balancing, power consumption and so forth. As of now, as there is an expansion in

innovation and buyer requests, there is exorbitant workload, which requires the need of a load

balancer. Idea of load balancing among the servers in cloud importantly affects the execution.

The uneven appropriation of load among the servers brings about server overloading and may

prompt the crashing of servers. This reduces the execution. Load balancing is a system that

appropriates the load similarly among the servers which abstains from overloading\of servers,

server crashes and the execution corrupts. Load balancing is a vital component that gives great

response time, effective usage of resources. Thus, an effective load balancing is required.

Another problem in cloud computing is giving service that fulfills Service Level Agreements

(SLA). Service Level Agreement is an agreement between service provider and the client in

delivering Quality of Service. In cloud computing, Service Level Agreement is called as the

cloud providers consented to the level of execution for the specific parts of the services with the

suppliers. This requires an undertaking must be planned to such an extent that the response time

is degraded and give services to the client inside the scheduled time as indicated in Service Level

Agreements. In this manner, by seeing to SLA and accomplishing legitimate load balancing,

service suppliers can pull in the clients and can augment their benefit, generally clients move to

the next service suppliers. Along these lines giving both Quality of Service and load balancing

among the servers are the most difficult exploration issues. Henceforth, the proposed a structure

that schedules a task based on Service Level Agreements and furthermore keeps up the load

balancing among different servers, in this manner gives both great response time and efficient

resource utilization.

1.1.1 CLOUD SERVICE MODELS

Infrastructure-as-a-Service.

Consumers send their product, including OS and application on supplier's base.

Consumers have control over OS and sent applications.

Platform-as-a-Service.

Consumers send shopper made or obtained applications onto supplier's processing

stage.



Consumers have control over sent applications.

Software-as-a-Service.

Consumers utilize supplier's application running on cloud foundation.

Service suppliers only oversee figuring base.

Fig 1.1 Cloud Deployment Model

1.1.2 CLOUD ENABLING TECHNOLOGIES

Grid Computing- Form of circulated registering. Enables resources of different PCs in a

framework to wear down a singular task meanwhile.

Utility Computing- Service provisioning model that offers registering assets as a

metered administration.

Virtualization- Abstracts physical attributes of IT assets from asset clients. Empowers

asset pooling and making virtual assets from pooled assets.



Service Oriented Architecture (SOA) - Provides an arrangement of administrations that

can speak with one another.

1.1.3 CLOUD OPTIMIZED STORAGE

Provides quick flexibility, worldwide access and capacity limit on interest.

Enables self-administration and completely metered access to capacity.

Key qualities of cloud advanced stockpiling arrangement are:

Massively versatile

Unified namespace.

Metadata and arrangement based data administration.

Secure multi-tenancy.

Multiple access instruments.

1.1.4 ADVANTAGES OF CLOUD COMPUTING

Reduced IT cost- Reduces the in advance capital expenditure(CAPEX).

Business Agility- Provides the capacity to convey new assets rapidly and empowers

organizations to lessen time-to-market.

Flexible scaling- Enables shoppers to scale up, scale down, scale out or scale in the

interest for figuring assets effectively. Shoppers can singularly and consequently scale

figuring assets.

High accessibility- Ensures asset accessibility at different levels, contingent upon

customer's need and approach.



Fig 1.2 Enabling Technologies

1.1.5 DISADVANTAGES OF CLOUD ENVIRONMENT

Possible downtime

Distributed computing figuring makes your little business dependent on the

constancy of your Internet affiliation. When it's separated from the net, you are logged

off. In case your web access encounters general power outages or moderate speeds

appropriated figuring may not be reasonable for your business. Additionally, even the

most strong distributed computing organization suppliers persist server power outages

now and again.

Security issues

Most security issues stem from:

Loss of control

Absence of trust(component)

Multi-occupancy



These issues exist principally in third gathering administration models

Self-guided mists still have security issues, yet not identified with above

Vendor Lock-In

Notwithstanding the way that cloud association suppliers ensure that the cloud

will be adaptable to use and harden, trading cloud affiliations is something that has not

yet completely made. Affiliations may imagine that it difficult to move their affiliations

beginning with one shipper then onto the going with. Enabling and sorting out current

cloud applications on another stage may heave compatibility and reinforce issues. A

correct illustration, applications ended up being on Microsoft Development Framework

(.Net) may not work appropriately on the Linux stage.

The frequently referred benefits of distributed computing administration is the asset

versatility. A business client can scale all over its asset utilization as required without forthright

capital speculation or long haul duty. The Amazon EC2 administration, for instance, permits

clients to purchase the same number of virtual machine (VM) examples as they need and work

them much like physical equipment. On the other hand, the clients still need to choose the

amount of assets are essential and for to what extent. It accept numerous Internet applications

can benefit from an auto scaling property where their asset use can be scaled here and there

consequently by the cloud administration supplier.

A client just needs to transfer the application onto a solitary server in the cloud, and the

cloud administration will repeat the application onto more or less servers as its request travels

every which way. The clients are charged just for what they really utilize the supposed pay as

you go model. Fig 1.3 demonstrates the commonplace construction modeling of server farm

servers for Internet applications. It comprises of a heap adjusting switch, an arrangement of

utilization servers, and an arrangement of backend stockpiling servers. The front end switch is

commonly a Layer 7 switch which parses application level data in Web asks for and advances

them to the servers with the relating applications running. The switch some of the time keeps

running in a repetitive pair for adaptation to internal failure.

Every application can keep running on numerous server machines and the arrangement of

their running examples are regularly overseen by some grouping programming, for example,



Web-Logic. Every server machine can have different applications. The applications store their

state data in the backend stockpiling servers. It is vital that the applications themselves are

stateless so they can be imitated securely. The capacity servers might likewise get to be over-

burden, however the canter of this work is on the application level. The Google App Engine

administration, for instance, obliges that the applications be organized in such a two level

building design and uses the Big Table as its versatile stockpiling arrangement.

Some conveyed information preparing applications can't be mapped into such a layered

structural planning effortlessly and consequently are not the objective of this work. We accept

our structural engineering is illustrative of an expansive arrangement of Internet administrations

facilitated in the distributed computing environment. The stack equality course of action is done

by the essential controller and the balancers.

The standard controller first consigns employments to the appropriate cloud assignment

and thereafter compares with the balancers in each section to animate this status information.

Since the rule controller oversees information for each bundle, smaller data sets will incite the

higher planning rates. The balancers in each apportioning collect the status information from

every hub and thereafter pick the right strategy to pass on the occupations. This evaluation of

every hub load status is basic. The first undertaking is to define the pile level of each hub. The

center load degree is related to various static parameters and component parameters. The static

parameters join the amount of CPU's, the CPU taking care of paces, the memory size, etc.

Dynamic parameters are the memory use extent, the CPU utilization extent, the framework

exchange speed, and so forth.



Fig 1.3 Two Tiered Architecture for Internet Application

1.1.6 VIRTUALIZATION

In cloud giving administrations of web application the virtualization assumes critical part

for shortcoming confinement. It is one of the key empowering innovation for distributed

computing the primary objective of virtualization is to enhance the use of occasion, empower

adaptation to internal failure when occurrence occasion disappointment, also, simple to

regulation . Virtualization in PC innovation is making of virtual as opposed to real. Here it make

virtual machine examples for assets distribution. The virtualized assets can be gotten to by

gadgets, application, working framework, and by clients. Asset virtualization can be arranged

into servers, stockpiling, and working framework.

The capacity virtualization is permits straightforward provisioning stockpiling limit

furthermore, disentangles information adaptability and administration. The server virtualization

is utilizing virtual machine screen layer running between working framework and equipment.

The working framework virtualization utilized reflection of working framework asset utilizing

virtualization layer and that does not runs specifically on equipment. This third virtualization



suggests higher overhead as contrast with server virtualization. Because of this it can be utilized

just for application testing yet not for generation environment.

Here for web use of cloud it utilize server virtualization furthermore capacity

virtualization it will utilize in server farms for deficiency detachment. At the point when the

issue is happen amid running procedure of utilization servers virtualization pin focuses the real

bring about and area and supplant VM occasion by making another VM occurrence and

recuperated fizzled machine rapidly.

Advances in cloud technique have opened up numerous possible outcomes. Until now,

the fundamental concern of developers was the organization and facilitating of utilizations,

remembering the securing of assets with a settled ability to handle the normal movement because

of the interest for the application, and additionally the establishment, arrangement and upkeep of

the entire supporting stack. With the coming of the cloud, application sending and facilitating has

gotten to be adaptable, less demanding and less expensive due to the compensation per-use

charge back model offered by cloud service suppliers.

1.1.7 SIMULATION IS IMPORTANT FOR CLOUD COMPUTING

Distributed computing is a best-fit for applications where clients have heterogeneous,

dynamic, and contending Quality of Service (QoS) necessities. Diverse applications have

distinctive execution levels, workloads and element application scaling necessities, however

these qualities, service models and organization models make an ambiguous circumstance when

it utilize the cloud to host applications. The cloud makes complex provisioning, sending, and

design.

Cloud administration suppliers offer versatile, on-interest, and measured foundation,

platforms and programming services. In the general cloud, occupants have control over the

Operating System, stockpiling and conveyed applications. Assets are provisioned in various

geographic districts. In the general cloud arrangement demonstrate, the execution of an

application sent in different regions involves concern towards associations. Verification of ideas

in public cloud environment give a superior understanding however cost a great deal regarding

limit building and asset utilization even in the compensation per-use model. CloudSim is a

toolbox for the demonstrating and recreation of Cloud figuring environment acts the hero. It



gives framework and behavioral displaying of the cloud processing parts. Reenactment of cloud

situations and applications to assess execution can give helpful experiences to investigate such

dynamic, enormously conveyed, and adaptable situations.

Advantages of simulation are:

Adaptability of characterizing arrangements

Convenience and customization

Cost advantages - Developing, designing, testing, and then re-designing, re-building, and

re-testing any application on the cloud can be costly. Simulations take the building and

modifying eliminate of the loop by utilizing the model as of now made as a part of the

configuration stage.

CloudSim is a toolbox for demonstrating and reproducing cloud situations and to survey

asset provisioning calculations.

Fig 1.4 Features of CloudSim



1.1.8 INTRODUCTION ABOUT CLOUDSIM

CloudSim is a re-enactment device that permits cloud designers to test the execution of

their provisioning strategies in a repeatable and controllable environment, free of expense. It

tunes the bottlenecks before genuine organization. It is a simulator device. Subsequently, it

doesn't run any genuine programming. It characterized as running a model of domain in a model

of equipment, where innovation particular subtle elements are abstracted. CloudSim is a library

for the reproduction of cloud situations. It gives crucial classes to describing data centers, virtual

machines, applications, clients, and approaches for the administration of different parts of the

framework, for example, planning and provisioning. Utilizing these parts, it is anything but

difficult to assess new systems overseeing the utilization of mists, while considering

arrangements, planning calculations, load balancing approaches, and so on. It can likewise be

utilized to survey the skill of procedures from different viewpoints, for example, cost, application

execution time, and so on. It additionally supports the assessment of Green IT arrangements. It

can be utilized as a building hinder for a reproduced cloud environment and can include new

approaches for scheduling, load balancing and new situations. It is sufficiently adaptable to be

utilized as a library that permits you to include a craved situation by composing a system.

CloudSim used in organizations, Research and Development centers and industry based

programmers can test the execution of a newly developed application in a controlled and easy to

setup environment.

1.1.9 CLOUDSIM ARCHITECTTURE

The CloudSim layer gives backing to modeling and simulations of cloud situations

including committed administration interfaces for memory, stockpiling, data transfer capacity

and virtual machines. It additionally arrangements hosts to virtual machines, application

execution administration and element framework state checking. A cloud administration supplier

can execute altered methodologies at this layer to think about the effectiveness of various

arrangements in Virtual Machine provisioning. The user code layer exposes basic entities such as

the number of machines, their specifications, as well as applications, virtual machines, number of

users, application types and scheduling policies.



The important aspects of the CloudSim framework are:

Regions - It displays geographical areas in which cloud administration suppliers allocate

assets to their clients. In cloud investigation, there are six regions that compare to six

continents in the planet.

Data Centers - It displays the framework administrations gave by different cloud service

suppliers. It encapsulates an arrangement of processing hosts or servers that are either

heterogeneous or homogeneous in nature, in light of their equipment setups.

Data center qualities - It displays data with respect to server farm asset designs.

Hosts - It demonstrates physical assets.

The user base - It displays a group of the clients considered as a solitary unit in the

simulation, and its principle duty is to produce movement for the simulation.

Cloudlet - It determines the arrangement of client requests. It contains the application ID,

name of the client base that is the originator to which the reactions must be steered back,

and additionally the extent of the solicitation execution orders, information and yield

records. It shows the cloud based application services. CloudSim orders the many-sided

quality of an application as far as its computational prerequisites. Every application

administration hasta pre-allotted direction length and information exchange overhead that

it needs to do amid its life cycle.

Service broker - It decides which data center should be selected to give the services to

the requests from the client base.

VMM allocation policy - It displays provisioning arrangements on the most proficient

method to distribute virtual machines to hosts.

Virtual Machine scheduler - It shows the time or space shared, booking a strategy to

apportion processor centers to virtual machines.

1.2 EXISTING SYSTEM

In previous approach, the computing assets are conveyed in different server farms

worldwide and these assets are offered to the clients on interest on compensation as use premise

yet the expanded use of cloud, there is an enormous increment in workload. The uneven



dispersion of load among the servers brings about server overloading and may prompt the server

crash. This influences the execution.

1.3 PROPOSED SYSTEM

In this approach, Cloud computing service provider proposed two phase scheduling

algorithm comprises of Service Level Agreements based Scheduling Algorithm and Idle Server

Monitoring Algorithm and augment their benefit by giving Quality of Service (QOS) and

Providing both QOS and load adjusting among the servers. So this framework is designed to

offer both Quality of Service (QOS) and load balancing among the servers in cloud.

1.4 FLOW OF THE PROJECT

This chapter briefly discussed about the limitations of the existing system and outcomes

of the proposed system. Chapter 2 discusses about the background studies done for the project,

third chapter explains about the architecture of the proposed system, fourth chapter discusses the

dataflow diagrams and the use case diagrams, fifth chapter discusses about the implementation

which discusses about the modules and language used for implementation, sixth chapter explains

about different testing done. Last chapter discusses the conclusion and future enhancement.

1.5 SUMMARY

This chapter discusses about the introduction of project. It explains about existing system

and issues observed in existing system. And brief explanation about proposed system and

advantages of proposed system. This chapter also discusses about the flow of view of proposed

system.



CHAPTER 2

LITERATURE SURVEY

2.1 INTRODUCTION

It is the study of conceptual data and study background work related to the project. It

describes the existing systems and techniques used to detect the disease. Comparing all the

techniques helps in identifying the better technique to detect the leaf disease. It makes the work

easy by knowing about the existing system used to detect the plant disease.

[1] Cloud Computing and emerging IT platforms – Vision, hype, and reality for delivering

computing as fifth utility.

Cloud computing is another and promising worldview conveying. It services as figuring utilities.

As Clouds are intended to give services to external clients, suppliers should be made up for

sharing their assets and capacities. This paper proposed architecture for market oriented

allocation of assets within Clouds. It likewise displayed a vision for the production of worldwide

Cloud trade for exchanging administrations. Additionally, it talked about some illustrative stages

for Cloud registering covering the best in class. Specifically, it displayed different Cloud

endeavors by from the business sector situated point of view to uncover its rising potential for

the formation of outsider services to empower the fruitful selection of cloud computing, for

example, meta-arrangement base for worldwide cloud trades and give superior substance

conveyance through Storage Clouds.

[2] Load balancing in a three level cloud computing network

Cloud computing is an Internet based advancement in which powerfully versatile and frequently

virtualized assets are given as an administration over the internet has turned into a critical issue.

It refers to a class of frameworks and applications that utilize disseminated assets to play outta

capacity in a decentralized way. It is to use the computing assets on the system to encourage the

execution of complicated tasks that require expansive scale computation. Hence, the selecting

hubs for executing a task in the cloud computing must be considered, and to abuse the viability

of the assets, they must be appropriately chosen by properties of the assignment. In this study, a



two-stage scheduling algorithm under a three level distributed computing system is progressed.

The proposed scheduling calculation joins Opportunistic Load Balancing (OLB) and Load

Balance Min-Min (LBMM) planning algorithms that can use all the more better executing

productivity and keep up the load balancing of framework.

[3] Three phase Scheduling in a Hierarchical Cloud Computing Environment

The three stages planning that included BTO, EOLB and EMM is co-ordinate. The distribution

of assignments depended on the related data from hubs gathered by the operator. The

examination comes about because of the make traverse demonstrate that the proposed script

consolidating EOLB with EMM clearly improves the execution of a framework. The mix of

OLB and EMM improves the framework execution around half while the blend of EOLB and

EMM upgrades execution around 20%. At the end of the day, the proposed planning perceives

the load balances of hubs and improves the whole execution of a framework.

[4] Performance Evaluation of Adaptive Virtual machine Load balancing Algorithm

Another Virtual Machine load balancing algorithm is proposed which is actualized in CloudSim

is a conceptual distributed computing environment utilizing java language. Proposed algorithm

finds the normal response time of each resource and sends the ID of virtual machine having least

response time to the server farm controller for portion to the new demand. As indicated by this

investigation, it infer that on the off chance that it select a proficient virtual machine then it

impacts the general execution of the cloud Environment furthermore diminishes the normal

response time.

[5] Effective Load balancing algorithm in virtual machine Cloud Computing

The origination of Cloud computing has reshaped the field of circulated frameworks as well as

on a very basic level changed how organizations potential broaden today. Load balancing is a

center and testing issue in Cloud Computing. The most effective method to utilize Cloud

registering assets proficiently and pick up the greatest benefits with productive load balancing

algorithm is one of the cloud processing service providers extreme objectives. In this paper

firstly an investigation of various virtual machines load balancing calculations was done other



Virtual Machine load balancing calculation has been proposed and actualized in virtual machine

environment of distributed computing so as to accomplish better reaction time and cost.

[6] Analysis of Load balancing in Cloud Computing

Cloud computing is high utility programming being able to change the IT programming industry

and making the product considerably more attractive. It has additionally changed the way IT

organizations used to purchase and outline equipment. The flexibility of assets without paying a

premium for huge scale is extraordinary ever. The expansion in web activity and distinctive

administrations are expanding step by step making load balancing a major examination point.

Cloud computing is another innovation which utilizes virtual machine rather than physical

machine to host, store and system the diverse segments. Load balance is utilized for assigning

load to various virtual machines in a manner that none of the nodes gets stacked vigorously or

delicately. The load balancing should be done legitimately in light of the fact that disappointment

in any of the node can prompt inaccessibility of information.

[7]Layered Approach for SLA Violation Propagation in Self – manageable Cloud

Infrastructures

Distributed computing speaks to a promising computing paradigm where computing assets must

be assigned to programming for their execution. Self-sensible Cloud frameworks are required to

accomplish that level of adaptability on one hand, and to go along to clients prerequisites

determined by method for Service Level Agreements (SLAs) on the other. Such frameworks

should consequently react to evolving part, workload, and ecological conditions minimizing

client collaborations with the framework and forestalling infringement of agreed SLAs. Be that

as it may, distinguishing proof of sources in charge of the conceivable SLA violation and the

choice about the receptive activities important to keep SLA violation is a long way from

insignificant. To begin with, this paper shows a novel methodology for mapping low-level asset

measurements to SLA parameters fundamental for the distinguishing proof of disappointment

sources. Second, it devise a layered Cloud engineering for the base up proliferation of

disappointments to the layer, which can respond to detected SLA infringement dangers. In

addition, it exhibit a correspondence model for the engendering of SLA infringement dangers to



the suitable layer of the Cloud base, which incorporates mediators, intermediaries, and

programmed administration deplorer.

[8] Priority based Resource Allocation model for Cloud Environment

Now a days, Cloud computing is on demand as it offers dynamic adaptable asset

allocation, for solid and ensured services in pay as you utilize way, to Cloud service clients. So

there must be an arrangement that all assets are made accessible to asking for clients in proficient

way to fulfill clients need. This asset provisioning is finished by considering the Service Level

Agreements (SLA) and with the assistance of parallel handling. Latest work considers different

procedures with single SLA parameter. Thus by considering different SLA parameter and asset

allocation by acquisition system for high need task execution can enhance the resource usage in

Cloud. It proposed an algorithm which considered Pre-emptible assignment task execution and

different SLA parameters, for example, memory, system transfer speed, and required CPU time.

An acquired exploratory result demonstrates that in a circumstance where asset dispute is savage

algorithm gives better usage of resources.

[9] Resource provisioning Techniques in Cloud Computing Environment

In Cloud Computing, Resource provisioning implies the determination, organization, and run-

time administration of programming and equipment resources for guaranteeing ensured

execution for applications. These procedures are utilized to enhance response time, execution,

spare vitality, Quality of Service (QOS), SLA. A definitive objective of resource provisioning is

to boost benefit from the Cloud Service Provider's Perspective and from the Cloud User's

Perspective to less cost. There are numerous difficulties in the current asset provisioning

systems. A mechanism that conquers the difficulties of the current strategies must be utilized.

Design must be proposed so it works for Data concentrated HPC applications furthermore for

genuine workload. Systems must be proposed to proficiently make of cloud assets, so that QoS is

met and SLA infringement in minimized in half and half mists when powerfully provisioned.

Additionally these provisioning components must be utilized for both SaaS and IaaS clients.



[10] Efficient Virtual machine Load balancing Algorithm for Cloud System

A Novel Virtual Machine Load Balancing Algorithm is proposed and after that actualized in

Cloud Computing environment utilizing CloudSim toolbox, in java programming. In this

algorithm, the VM appoints a changing measure of the accessible handling energy to the

individual application services. These Virtual Machines of various handling powers, the tasks are

assigned or allocated to the most capable Virtual Machine and after that to the least etc.

Subsequently, it enhanced the given execution parameters, for example, response time and data

processing time, giving a proficient virtual machine Load balancing algorithm. That is

"Weighted Active Load Balancing Algorithm" in the Cloud Computing system.

2.2 SUMMARY

This chapter describes the study of contextual data and theoretical background related to

current project. It helps to discover the existing system and find the background study for this

project and it also compares the previous solution.



CHAPTER 3

SYSTEM REQUIREMENT SPECIFICATION

3.1 INTRODUCTION

System Requirement Specification (SRS) is a focal report, which outlines the foundation

of the item headway process. Maybe the System Requirement Specification (SRS) ought to be

changed; in any case it gives a foundation to continue with creation evaluation. In direct words,

programming need determination is the starting phase of the item change activity. The System

Requirement Specification (SRS) implies unraveling the musings in the brains of the clients – the

data, into a formal file – the yield of the essential stage. Thusly the yield of the stage is an

arranged of formally decided necessities, which in a perfect world are done and unfaltering,

while the information has none of these properties.

HARDWARE SPECIFICATION

Hardware : Pentium-IV System

Speed : 2.4 GHz

RAM : 4GB

Hard Disk : 80 GB

SOFTWARE SPECIFICATION

Operating System : Windows

Technology : Java

IDE : My Eclipse



3.2 SYSTEM REQUIREMENTS

Requirements are the Constraints or Services that is expected from the system. It consists of

two requirements.

Functional requirements

Non – Functional requirements

3.2.1 FUNCTIONAL REQUIREMENTS

Initialize the CloudSim.

Create Virtual Machines.

Cluster the Virtual Machines.

Create tasks

Assign task to Virtual Machines.

Separate the task based on the instructions.

Allot Virtual Machines to task.

Put the unassigned tasks to queue.

Schedule the task.

3.2.2 NON – FUNCTIONAL REQUIREMENTS

Usability -The connections are accommodated every structure. The client is encouraged

to view and make entries in the structures. Acceptances are given in every field to stay

away from conflicting or invalid entries in the applications or system.

Security - Application will be reasonable to be utilized just as a part of secure system, so

there is less possibility of instability over the usefulness of the application.

Maintainability - The establishment and operation manual of the task will be given to

the client, so they can work and keep up the application itself.

Availability - Framework will be accessible around the clock except time required for

the backup data.



Portability -The application is created in Java, JSPs and Servlet. It is compact to other

working framework gave JDK is accessible to the Operating System.

Integrity -The project is designed in a coordinated development environment, where

every class, individuals, qualities is composed under java bundle. Assembling and

troubleshooting the primary class will coordinate every one of the classes in like manner

for the best possible assemblage of the undertaking work.

Extensibility -The project is additionally open for any future change and thus the work

could be characterized as the one of the extensible work.

Performance - High speed of interaction and processing between the modules of the

application.

Reliability - Application will work appropriately in a predefined domain and for a given

time term.

Safety - It improves framework security in the outline design, advancement, use, and

upkeep of programming.

3.3 SUMMARY

This chapter specifies the hardware and software specification. It also describes the

system requirements of the project.



CHAPTER 4

SYSTEM ARCHITECTURE

4.1 INTRODUCTION

Architecture is an important part of Software Development Life Cycle (SDLC). It is the

second phase that underscores on the prerequisites that are analyzed in the Requirements

Analysis by building models that give an underlying look at what the genuine framework

resemble. This phase begins after the analyzed requirements are documented. This is blue print

for the System. The design is done in two levels: System Design or top level design, Logic or

detail design.

4.2 SYSTEM ARCHITECTURE

Fig 4.1 System Architecture



Far reaching systems are always dis-incorporated into sub-structures that give some

related plan of organizations. The initial arrangement system of perceiving these sub-systems

and setting up a structure for sub-system control and correspondence is called Architecture

diagram and the yield of this framework method is a depiction of the item development

demonstrating.

The building design technique is concerned with setting up a fundamental assistant

framework for a system. It incorporates perceiving the genuine fragments of the structure and

correspondences between these parts. In the going with sub-fragments it plunge into the design

points of view and the sub systems incorporated into this item package.

4.3 SUMMARY

The main objective of this chapter describes design of architecture requirements of the

proposed system. System architecture is the procedure of describing the architecture,

components and modules of the proposed system required to satisfy the specified requirements.



CHAPTER 5

LOW LEVEL DESIGN

5.1 INTRODUCTION

Dataflow diagram are an instinctive method for demonstrating how information is

prepared by a framework. A utilization case plot in the Unified Modeling Language (UML) is a

sort of behavioral graph portrayed by and produced using a Use-case examination. Sequence

diagram are a simple and natural method for depicting the conduct of a framework by survey the

co-operation in the middle of framework and environment.

5.2 DATA FLOW DIAGRAM

Information stream models are an instinctive method for demonstrating how information

is prepared by a framework. At the investigation level, they ought to be utilized to model the

route in which information is handled in the current framework. The documentations utilized as a

part of these models speaks to utilitarian preparing, information stores and information

developments between capacities. Information stream models are used to show how data travels

through a progression of taking care of steps. The data is traded at each movement before

continuing ahead to the accompanying stage. These taking care of steps or changes are venture

limits when data stream graphs are used to clear up an item arrange.

Levelf0:

Fig 5.1 DatafFlowfDiagramfLevelf0



Levelv1:

Fig 5.2 DatavFlowvDiagramvLevelv1

Levelv2:

Fig 5.3 DatavFlowvDiagramvLevelv2

5.3 USE CASE DIAGRAM

A use case diagram in the Unified Modeling Language (UML1) is a sort of behavioral

graph portrayed by and produced using a Use-case examination. Its outline is to exhibit a

graphical chart of the convenience gave by a structure with respect to on-screen characters, their

destinations (addressed as use cases), and any conditions between those use cases. The standard

inspiration driving a usage case diagram is to show what structure limits are performed for which

entertainer. Parts of the entertainers in the system can be depicted.



Fig 5.4 Use Case Diagram

5.4 SEQUENCE DIAGRAM

A gathering graph is an affiliation layouts those unpretentious components how

operations are done, what messages are sent and when. The things incorporated into the

operation are recorded from left to perfectly fine when they take part in the message progression.

Progression charts are a straightforward and regular strategy for portraying the behavior of a

structure by study the participation amidst system and environment.



Fig 5.5 Sequence Diagram

5.5 SUMMARY

This chapter describes complete and detailed design, specification and flow of the

proposed system.



CHAPTER 6

IMPLEMENTATION

6.1 INTRODUCTION

In this stage, the outline or plan changes are presented and made operational in a

particular circumstance. The stage is presented after the system has been attempted and

recognized by the customer and structure chairman. Practices in this stage fuse notification of

use to end customers, execution of the as of now described planning course of action, data entry

or discourse, and post use review.

6.2 MODULES

6.2.1 CLOUD INITIALIZATION

CloudSim gives a summed up and extensible simulation system that empowers

consistent demonstrating and simulation of application execution. By utilizing cloudSim,

programmers can concentrate on particular frameworks plan issues that they need to research,

without getting worried about points of interest identified with cloud-based foundations and

services. At first cloudSim is instated. When cloudSim is initialized, after that it can make the

VMs and begin the reproduction.

6.2.2 VIRTUAL MACHINE CREATION AND CLUSTERING

Once the cloudSim is initialized, set of Virtual Machines(VMs) are created. Each VM is

assigned with a broker ID, MIPS, number of CPU, RAM, bandwidth, size etc. Each virtual

machine is object of virtual machine class present in cloudSim simulation tool. Once the VMs

are created next step is to update the details to the main controller. Once the main controller

receives all the VM details, next step is to cluster the VMs based on the MIPS and number of

CPU into high, medium and low cluster. Once main controller assign the VMs, their expected

cluster, it divides the VMs into three separate clusters and assigns to task scheduling machine.



6.2.3 TASK CREATION AND ASSIGN

Once all the VMs are ready, we create the tasks and updates to the main controller. Each

task contains, total number of instructions, arrival time and deadline. Once the main controller

receives the task details, it calculates the VMs that can complete the task. Based on total number

of instructions and deadline of task and MIPS, number of CPU of VMs the expected VM cluster

is calculated. Once the task’s expected VM cluster is calculated, main controller assign the tasks

to the VM clusters and if total numbers of tasks are more than the available VMs then it put the

tasks in the queue of the respective clusters.

6.2.4 TASK SCHEDULING

Once the process starts the VM of each cluster starts executing the tasks from their

cluster. After is complete the task, then it’s being assigned a new task from the queue and

continue execution. The algorithm of the task scheduling rules is described below.

ALGORITHM

Step 1: Group Virtual Machines (VM) into different clusters based on the high server cluster,

medium server cluster and low server cluster.

Step 2: If a task Ti arrives, Service Level Agreement (SLA) based scheduling algorithm decides

the first consideration of a task by considering execution time and deadline.

Step 3: Then the algorithm SLA allocate the task Ti to the particular cluster based on the

computing priority as follows:

i) If task Ti is a high priority task, it is assigned to high server cluster.

ii) If task Ti is medium priority task, it is assigned to a medium server cluster.

iii) If task Ti is low priority task, it is assigned to a low server cluster.

Stepd4:



i) If task Ti is allocated to high servers cluster, then idle server monitoring algorithm

checks for empty virtual machine Vi in its cluster. If it found, it allocate that particular

task Ti to virtual machine Vi. Otherwise, the task Ti will be allocated to idle virtual

machine Vi in medium servers cluster or low servers cluster and if any VM becomes idle

in high servers cluster, task will be moved to idle virtual machine Vi in the high servers

cluster. If no empty VM is found in the medium cluster or low cluster, then put the task

in the queue of high servers cluster.

ii) If task Ti is allocated to medium servers cluster, then idle server monitoring algorithm

first searches for an empty virtual machine Vi in high servers cluster. If found, it

allocates its task Ti to the identified virtual machine Vi. Otherwise, it checks for empty

virtual machine Vi in its cluster, if it found allocates the tasks to that corresponding

virtual machine Vi. If not found, the task Ti will be allocated to empty virtual machine

Vi in low servers cluster and if any VM becomes empty in medium server cluster, task

will be moved to the idle virtual machine Vi in the medium server cluster. If no idle VM

is found in the lower servers cluster then put the task in the queue of medium server

cluster.

iii) If task Ti is allocated to low servers cluster, idle server monitoring algorithm first

searches for an idle Virtual Machine Vi in high servers cluster, if it found it assigns that

particular task in the high servers cluster. If idle VM is not found, then it searches for

idle VM in medium servers cluster. If it found, it allocates its task Ti to the particular

virtual machine Vi. Otherwise, it checks for idle virtual machine Vi in its cluster, if it

found allocate the tasks to the corresponding virtual machine Vi. If not found, the tasks

Ti are put into queue.

Stepg5: Stepsv2 tov4 do again for every approaching task assignment.

6.3 SUMMARY

This chapter describes the software used to execute the project. It describes each module

and algorithms used for each module. This chapter discusses how each algorithm works.



CHAPTER 7

TESTING

7.1 INTRODUCTION

Testing is the procedure used to determine the quality of programming software. It is the

procedure breaking down a produce thing to distinguish the distinction among existing and

required conditions and to assess the elements of the product thing programming testing is a

movement that ought to be done all through the entire advancement process. Software Testing is

one of the verification and validation, programming rehearses:

Verification - It is the way toward assessing a framework or system to determine if the

results of a given development stage fulfill the condition forced towards the begin of that

stage. It incorporates testing and audits. Software testing is an experimental specialized

examination directed to work.

Validation - It is the way toward assessing a framework or part amid or at end of the

improvement procedure to figure out if it fulfills determined necessities. Toward the end

of improvement acceptance exercises are utilized to assess whether the elements that

have been incorporated with the product fulfill the client requirements and are traceable

to client necessities.

7.2 TESTING PROCESS

Testing should be done as shown below:

Unit testing



It tests the negligible software segment or module. Every unit of the product is tried

to check that the point by point plan for the unit has been accurately actualized. In an

article situated environment, this is for the most part at the class level, and the

insignificant unit tests incorporate the constructors and destructors.

Integration testing

It uncovered deformities in the interfaces and association between coordinated

segments (modules). Dynamically bigger gatherings of tried programming segments

comparing to components of the compositional configuration are coordinated and

tried until the product fills in as a framework.

System Testing

It tests a totally coordinated framework to confirm that it meets its necessities.

Framework joining testing confirms that a framework is incorporated to any outside

or outsider frameworks characterized in the framework prerequisites.

7.3 TEST CASES

Tablef1: TestfCasef1












Tablef7: TestvCasev7



Tablev8: TestvCasev8

Tablev9: TestvCasev9

7.4 SUMMARY

This chapter describes about several kinds of testing has done for proposed system before

producing the software. And also describes about testing for user acceptance of the proposed

system.



CHAPTER 8

RESULTS

This section manages implementation subtle elements of the venture. Use stage

comprises of the considerable number of procedures required in getting new programming or

prerequisite working legitimately in its environment, including foundation, setup, running,

testing and taking off of principal changes.

8.1 RESULTS

Fig 8.1 Main Controller

The above figure consist of virtual machine details and task details. It is the starting phase

of project and it contains switches to every other function. In this phase first it needs to initialize

cloudsim to process the project.



Fig 8.2 Create Virtual Machines

This is the second phase of a project and it creates number of virtual machines to

schedule and execution.



Fig 8.3 Updated VM Details

This figure shows that updated number of virtual machines to VM Details. It contains Virtual

machine ID, broker ID, MIPS, number of processors, RAM, bandwidth and size of a virtual

machine.



Fig 8.4 Updated Virtual Machine Details to Main Controller



Fig 8.5 Created Cluster



Fig 8.6 Assign Virtual Machine to Cluster



Fig 8.7 Create Number of Tasks



Fig 8.8 Updated Task Details



Fig 8.9 Assign Tasks to Cluster



Fig 8.10 Task Scheduling and Processing



Fig 8.11 Tasks Waiting in Queue to Process



Fig 8.12 Updated Main Controller Details



Fig 8.13 Resource Utilization Graph



Fig 8.14 Minimize Response Time Graph



CHAPTER 9

CONCLUSION

The main aim of the project is to balance the load among the servers by using Service

Level Agreement (SLAs) based scheduled algorithm and idle server monitoring algorithm. SLA

algorithm schedules the tasks among different virtual machines in the respective cluster and idle

server monitoring algorithm balances the load among the various virtual machines and within the

cluster. The project result shows that the proposed algorithm minimizes response time, reduces

waiting time, effective utilization of resources and achieves better load balancing among the

virtual machines.



REFERENCES

[1] Zhen Xiao, Senior Member, IEEE, Weijia Song, and Qi Chen, “Dynamic Resource

Allocation Using Virtual Machines for Cloud Computing Environment”, IEEE Transactions on

parallel and distributed systems, vol. 24, June 2013.

[2] Xiaocheng Liu, Chen Wang, Bing Bing Zhou, Junliang Chen, Ting Yang, Zomaya, and A. Y.

Zomaya, “Priority-Based Consolidation of Parallel Workloads in the Cloud”, IEEE Transactions

on Parallel and Distributed Systems, vol. 24, September 2013.

[3] A B M Moniruzzaman et.al, “An Experimental Study of Load Balancing of Opennebula

open-source cloud computing Platform”, 3rd International conference on Informatics,

Electronics and Vision (ICIEV), IEEE computer Society, 2014.

[4] Zhen Xiao, Senior Member, IEEE, Weijia Song, and Qi Chen, “Dynamic Resource

Allocation Using Virtual Machines for Cloud Computing Environment”, IEEE Transactions on

parallel and distributed systems, vol. 24, no. 6, June 2013.

[5] SG Domanal, G.Reddy, “Load Balancing in cloud computing using Modified Throttled

algorithm”, IEEE international conference on cloud computing in Emerging Markets (CCEM),

2013.

[6] B.Subramani, “A New Approach for Load Balancing in Cloud Computing”, IEEE, May

2013.

[7] Luiz F.Bittencourt,Edmundo R.M.Madeira,and Nelson L.S da Fonseaca,”Scheduling in

Hybrid Clouds”, IEEE Communications Magazine, Sept - 2012.

[8] Amandeep, “Analysis of Load Balancing Techniques in Cloud Computing”, International

Journal of Computers & Technology, vol.4, April, 2013.

[9] Gaochao Xu, Junjie Pang, Xiaodong FuJaya, Bharathi Chintalapati,Srinivasa Rao T.Y.S. “ A

Load Balancing Model Based on Cloud Partitioning for the Public Cloud” IEEE transactions on

cloud computing, 2013.



APPENDIX A

PAPER PUBLISHED











APPENDIX B

PLAGIARISM REPORT

Documents

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