deepti project report - copy

8/2/2019 Deepti Project Report - Copy

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AProject Report on

Load Balancing in Cloud Computing

In Partial Fulfillment of the Requirement for8 th Semester, B.E. (Computer Science and Engineering)

Submitted by

DeeptiAgrawalSwati Nasre

Vibhuti Kumar UpadhyayMohammed TaslimAlam Ansari

Under the guidance of Prof . S.D. Chaudhari

DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING

J. L. CHATURVEDI COLLEGE OF ENGINEERING846, New Nandanvan Layout, Nagpur 440 009.

Session 2011-2012


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CERTIFICATE

This is to certify that the Project entitled

Load Balancing in Cloud Computing

is submitted by

DeeptiAgrawalSwati Nasre


to RashtrasantTukadojiMaharaj Nagpur University, in the partial fulfillment of

the requirement for Project in 8 th semester " Computer Science and Engineering "

for the academic year 2011 2012.

This report is a record of the work carried out by them and underwent requisite

directions as per the University Curriculum.

Under Guidance of

Prof . S.D. Chaudhari

Prof.S.D.Chaudharni Dr. S.S.Salankar(Head of Department) (Principal)


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i

i

ACKNOWLEDGEMENT

The success of any work depends on efforts of many individuals. Wewould like to take this opportunity to express our deep gratitude to thosewho extended their support and have guided us to complete this projectwork.

We wish to express our sincere and deepest gratitude to our guideProf.S.D. Chaudhari for his invaluable and unique guidance. We wouldalso like to thank her for the constant source of help, inspiration andencouragement in the successful completion of project. It has been ourprivilege and pleasure to work under her expert guidance.

We like to thank Prof.S.D.Chaudhari (HOD) for providing us thenecessary information about topic. We would again like to thank Dr.S.S.Salankar , Principal of our College, for providing us the necessaryhelp and facilities we needed.

We express our thanks to all the staff members of CSE Department whohave directly or indirectly extended their kind co-operation in thecompletion of our project Report.

Date:Place:

DeeptiAgrawal Swati Nasre



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INDEX

No . Chapters Page No.

1. Problem Definition 1 2. Introduction2.1 Cloud Computing2.2 Cloud Components2.3 Types of Clouds2.4 Virtualization2.5 Services provided by Cloud Computing2.6 Characteristics of Cloud Computing

2.7 Load Balancing

24579

1213

3. Platform, Tools & Techniques (Hardware &Software)

3.1 Back End3.2 Front End3.3 Hardware

15

4. Data Flow Diagrams 165. Project Methodology

5.1 The stages of SDLC5.2 Planning & Analysis stage5.3 Development stage5.4 Integration and testing stage

2020212631

6. Screen Shots 367. Advantages & Applications 428. Future Scope & Conclusion 439. Publications 44

10. Bibliography 47


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LIST OF TABLES

Tableno.

Table Title Page No.

5.1

5.2

5.3

Method Summary of CpuInfo class of

SIGAR.

Method Summary of Mem class of SIGAR.

Method Summary of SysInfo class of SIGAR.

26

26

27


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Problem Definition


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Problem Definition

The goal of a cloud-based architecture is to provide some form of elasticity,

the ability to expand and contract capacity on-demand. The implication is that at some

point additional instances of an application will be needed in order for the architecture

to scale and meet demand. That means there needs to be some mechanism in place tobalance requests between two or more instances of that application. The mechanism

most likely to be successful in performing such a task is a load balancer.

The challenges of attempting to build such architecture without a load

balancer are staggering. There's no other good way to take advantage of additional

capacity introduced by multiple instances of an application that's also efficient in

terms of configuration and deployment. All other methods require modifications and

changes to multiple network devices in order to properly distribute requests across

multiple instances of an application. Likewise, when the additional instances of that

application are de-provisioned, the changes to the network configuration need to be

reversed.

A load balancer provides the means by which instances of applications can be

provisioned and de-provisioned automatically, without requiring changes to the

network or its configuration. It automatically handles the increases and decreases incapacity and adapts its distribution decisions based on the capacity available at the

time a request is made.

Because the end-user is always directed to a virtual server, or IP address, on

the load balancer the increase or decrease of capacity provided by the provisioning

and de-provisioning of application instances is non-disruptive. As is required by even

the most basic of cloud computing definitions, the end user is abstracted by the load

balancer from the actual implementation and needs not care about the actual

implementation. The load balancer makes one, two, or two-hundred resources -

whether physical or virtual - appear to be one resource; this decouples the user from

the physical implementation of the application and allows the internal implementation

to grow, to shrink, and to change without any obvious effect on the user.

Choosing the right load balancer at the beginning of such an initiative is

imperative to the success of more complex implementations later. The right load


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balancer will be able to provide the basics required to lay the foundation for

more advanced cloud computing architectures in the future, while supporting even the

most basic architectures today. The right load balancer will be extensible.

Figure 1.1: A Typical Load Balancer used in Cloud Computing

Load balancing ensures that all the processor in the system or every node in

the network does approximately the equal amount of work at any instant of time. This

technique can be sender initiated, receiver initiated or symmetric type (combination of

sender initiated and receiver initiated types).

Our objective is to develop an effective load balancing algorithm maximize or

minimize different performance parameters (throughput, latency for example) for theclouds of different sizes (virtual topology depending on the application requirement).

The system will take the service as input which is requested by the

cloud customer and then the role of load balancer begins. It will communicate with

the clients present in its network and assign the load to the least loaded one.

Client

VirtualServer

PhysicalServe


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Introduction


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2.1 Cloud Computing

Cloud computing is the delivery of computing as a service rather than a product,

whereby shared resources, software, and information are provided to computers and other

devices as a utility (like the electricity grid) over a network (typically the Internet).

Cloud computing provides computation, software applications, data access, data

management and storage resources without requiring cloud users to know the location and

other details of the computing infrastructure.

End users access cloud based applications through a web browser or a light weight

desktop or mobile app while the business software and data are stored on servers at a remote

location. Cloud application providers strive to give the same or better service andperformance as if the software programs were installed locally on end-user computers.

At the foundation of cloud computing is the broader concept of infrastructure

convergence (or Converged Infrastructure) and shared. This type of data centre environment

allows enterprises to get their applications up and running faster, with easier manageability

and less maintenance, and enables IT to more rapidly adjust IT resources (such as servers,

storage, and networking) to meet fluctuating and unpredictable business demand.

In case of Cloud computing services can be used from diverse and widespread resources,

rather than remote servers or local machines. There is no standard definition of Cloud

computing. Generally it consists of a bunch of distributed servers known as masters,

providing demanded services and resources to different clients known as clients in a network

with scalability and reliability of data center. The distributed computers provide on-demand

services. Services may be of software resources (e.g. Software asa Service, SaaS) or physical

resources (e.g. Platform as a Service, PaaS) or hardware/infrastructure (e.g. Hardware as a

Service, HaaS or Infrastructure as a Service, IaaS ). Amazon EC2 (Amazon Elastic ComputeCloud) is an example of cloud computing services.

2.2 Cloud Components

A Cloud system consists of 3 major components such as clients, datacenter, and

distributed servers. Each element has a definite purpose and plays a specific role.


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Figure 2.1: Three components make up a cloud computing solution.

2.2.1 Clients

End users interact with the clients to manage information related to the cloud. Clients

generally fall into three categories:

Mobile: Windows Mobile Smartphone, Smartphones, like a Blackberry, or an iPhone.

Thin: They dont do any computation work. They only display the information.

Servers do all the works for them. Thin clients dont have any internal memory.

Thick: These use different browsers like IE or Mozilla Firefox or Google Chrome to

connect to the Internet cloud.

Now-a-days thin clients are more popular as compared to other clients because of

their low price, security, low consumption of power, less noise, easily replaceable and

repairable etc.

2.2.2 Datacenter

Datacenter is nothing but a collection of servers hosting different applications. An end

user connects to the datacenter to subscribe different applications. A datacenter may exist at a

large distance from the clients.


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Now-a-days a concept called virtualisation is used to install software that allows multiple

instances of virtual server applications.

2.2.3 Distributed Servers

Distributed servers are the parts of a cloud which are present throughout the Internet

hosting different applications. But while using the application from the cloud, the user will

feel that he is using this application from its own machine.

2.3 Type of Clouds

Based on the domain or environment in which clouds are used, clouds can be dividedinto following categories:

Public Cloud Private Cloud Hybrid Cloud Community cloud

2.3.1.Public Cloud

Applications, storage, and other resources are made available to the general public by

a service provider. Public cloud services may be free or offered on a pay-per-usage model.

There are limited service providers like Microsoft, Google etc owns all Infrastructures at their

Data Center and the access will be through Internet mode only. No direct connectivity

proposed in Public Cloud Architecture.

2.3.2. Private Cloud

Private cloud is infrastructure operated solely for a single organization, whether

managed internally or by a third-party and hosted internally or externally.

They have attracted criticism because users "still have to buy, build, and manage them" and

thus do not benefit from less hands-on management, essentially "[lacking] the economic

model that makes cloud computing such an intriguing concept".


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2.3.3. Hybrid Cloud

Hybrid cloud is a composition of two or more clouds (private, community or public)

that remain unique entities but are bound together, offering the benefits of multiple

deployment models.

2.3.4. Community cloud

Community cloud shares infrastructure between several organizations from a specific

community with common concerns (security, compliance, jurisdiction, etc.), whether

managed internally or by a third-party and hosted internally or externally. The costs are

spread over fewer users than a public cloud (but more than a private cloud), so only some of

the cost savings potential of cloud computing are realized.

Figure 2.2: Types of Cloud

2.4 VirtualizationIt is a very useful concept in context of cloud systems. Virtualisation means

something which isnt real , but gives all the facilities of a real. It is the software

implementation of a computer which will execute different programs like a real machine.

Virtualisation is related to cloud, because using virtualisation an end user can use

different services of a cloud. The remote datacenter will provide different services in a full or

partial virtualised manner.


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Two types of virtualization are found in case of clouds are:

Full virtualization Partial virtualization

2.4.1 Full Virtualization

In case of full virtualisation a complete installation of one machine is done on the

machine. It will result in a virtual machine which which will have all the softwarethat are

present in the actual server.

Figure 2.3: Full Virtualization

Here the remote datacenter delivers the services in a fully virtualised manner. Full

virtualization has been successful for several purposes:

Sharing a computer system among multiple users Isolating users from each other and from the control program Emulating hardware on another machine

2.4.2 Partial virtualization

In partial virtualisation, the hardware allows multiple operating systems to run on

single machine by efficient use of system resources such as memory and processor. e.g.

VMware software. Here all the services are not fully available, rather the services are

provided

partially.


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Figure 2.4: Partial virtualization.

Partial virtualization has the following advantages:

Disaster recovery: In the event of a system failure, guest instances are moved to

another hardware until the machine is repaired or replaced.

Migration: As the hardware can be replaced easily, hence migrating or moving the

different parts of a new machine is faster and easier.

Capacity management: In a virtualised environment, it is easier and faster to add

more hard drive capacity and processing power. As the system parts or hardware can

be moved or replaced or repaired easily, capacity management is simple and easier.

2.5 Services provided by Cloud computing

Service means different types of applications provided by different servers across the

cloud. It is generally given as as a service . Services in a cloud are of 3 types:

Software as a Service (SaaS) Platform as a Service (PaaS) Hardware as a Service (HaaS) or Infrastructure as a Service (IaaS)

2.5.1 Software as a Service (SaaS)


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In SaaS, the user uses different software applications from different servers through

the Internet. The user uses the software as it is without any change and do not needs to make

lots of changes or doesnt require integration to other systems. The provider does all the

upgrades and patching while keeping the infrastructure running.

Figure 2.5: Software as a service (SaaS).

The client will have to pay for the time he uses the software. The software that does a

simple task without any need to interact with other systems makes it an ideal candidate for

Software as a Service. Customer who isn t inclined to perform software development but

needs high-powered applications can also be benefitted from SaaS.

Some of these applications include:

Customer resource management (CRM) Video conferencing IT service management Accounting Web analytics Web content management

Benefits :

The biggest benefit of SaaS is costing less money than buying the whole application.

The service provider generally offers cheaper and more reliable applications as compared to


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It is also known as Infrastructure as a Service (IaaS). It offers the hardware as a

servicetoa organisation so that it can put anything into the hardware according to its will.

HaaS allows the user to rent resources as

Server space Network equipment Memory CPU cycles Storage space

Figure 2.7: Hardware as a service (HaaS)

Cloud computing provides a Service Oriented Architecture (SOA) and Internet of

Services (IoS) type applications, including fault tolerance, high scalability, availability,

flexibility, reduced information technology overhead for the user, reduced cost of ownership,

on demand services etc. Central to these issues lies the establishment of an effective load

balancing algorithm.

2.6 Characteristics of Cloud Computing

Virtualization: Virtualizationtechnology allows servers and storage devices to be shared

and utilization is increased. Applications can be easily migrated from one physical server

to another.

Multi-tenancy: Multi-tenancyenables sharing of resources and costs across a large pool

of users thus allowing for:

Centralization of infrastructure in locations with lower costs (such as real estate,

electricity, etc.)


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Peak-load capacity increases (users need not engineer for highest possible load-

levels)

Utilization and efficiency improvements for systems that are often only 10 20%

utilized.

Reliability: Reliability is improved if multiple redundant sites are used, which makes

well-designed cloud computing suitable for business continuity and disaster recovery.

Scalability: Scalability and Elasticity via dynamic ("on-demand")provisioning of

resources on a fine-grained, self-service basis near real-time, without users having to

engineer for peak loads.

Performance: Performance is monitored and consistent and loosely coupled

architectures are constructed using web services as the system interface.

Security: Security could improve due to centralization of data, increased security-

focused resources, etc., but concerns can persist about loss of control over certain

sensitive data, and the lack of security for stored kernels. Private cloud installations are

in part motivated by users' desire to retain control over the infrastructure and avoid losing

control of information security.

Maintenance: Maintenance of cloud computing applications is easier, because they do

not need to be installed on each user's computer and can be accessed from different

places.

2.7 Load balancing

It is a process of reassigning the total load to the individual nodes of the collective

system to make resource utilization effective and to improve the response time of the job

simultaneously removing a condition in which some of the nodes are over loaded while some

others are under loaded. A load balancing algorithm which is dynamic in nature does not

consider the previous state or behaviour of the system, that is, it depends on the present

behaviour of the system. The important things to consider while developing such algorithm

are : estimation of load, comparison of load, stability of different system, performance of

system, interaction between the nodes, nature of work to be transferred, selecting of nodes


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and many other ones. This load considered can be in terms of CPU load, amount of memory

used, delay or Network load.

2.7.2 Goals of Load balancing

The goals of load balancing are:

To improve the performance substantially

To have a backup plan in case the system fails even partially

To maintain the system stability

To accommodate future modication in the system

2.7.3 Types of Load balancing algorithms

Depending on who initiated the process, load balancing algorithms can be of three

categories:

Sender Initiated: If the load balancing algorithm is initialised by the sender

Receiver Initiated: If the load balancing algorithm is initiated by the receiver

Symmetric: It is the combination of both sender initiated and receiver initiated

Depending on the current state of the system, load balancing algorithms can be divided into 2

categories:

Static Load Balancing Algorithm Dynamic Load Balancing Algorithm

Here we will concentrate upon the later type of algorithm.

Dynamic Load balancing algorithm

In a distributed system, dynamic load balancing can be done in two different

ways: distributed and non-distributed. In the distributed one, the dynamic load

balancing algorithm is executed by all nodes present in the system and the task of load

balancing is shared among them. The interaction among nodes to achieve load

balancing can take two forms: cooperative and non-cooperative]. In the first one, the

nodes work side-by-side to achieve a common objective, for example, to improve the


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overall response time, etc. In the second form, each node works independently toward

a goal local to it, for example, to improve

the response time of a local task. Dynamic load balancing algorithms of

distributed nature, usually generate more messages than the non-distributed ones

because, each of the nodes in the system needs to interact with every other node. A

benefit, of this is that even if one or more nodes in the system fail, it will not cause the

total load balancing process to halt, it instead would affect the system performance to

some extent.


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Platform, Tools &Techniques(Hardware & Software)


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3.1 Back End

MySQL Version 5.1.36

3.2 Front End

Java 1.6 (jdk 1.6.0_04)

3.3 Hardware

Port Fast Ethernet Switch (DLink) LAN Wires


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Data Flow Diagrams


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Data Flow Diagrams

Figure: 4.1 The Data Flow Diagram of The System.


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NOT FOUND

FOUND

GOODBYE SYSTEMINFORMATION

WELCOME

YES

Figure 4.2. Flow Chart For getting details of clients connected to the server.

BIND TO MULTISOCKETADDRESS

CHECK FORCLIENT

CONNECTION

CHECKPROTOCOL

TYPE

REMOVE NAMEFROM DATABASE

ADD NAME TODATABASE

DOES ENTRYALREADY

EXIST?

INSERT NEWENTRY INTODATABASE

UPDATE THEDATABASE

UPDATE THE MAINWINDOW

EXIT

START


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FILE READ

FACTORIAL

Figure: 4.3. Flow Chart for Task Execution.

INPUT NUMBER FOR FACTORIALENTER THE FILE NAME

TYPE OFTASK

AA

SEARCH FORTHE

APPROPRIATECLIENT

ASSIGN JOB

SEARCH IN THE RMIREGISTRY

EXECUTE THE JOB

A

RERURN THE FACTORIALOF THE NUMBER

RETURN THE CONTENT OFFILE

EXIT

START


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END-OF-LIST

NO

YES

NO

YES

Figure 4.4. Flow Chart for Selecting the appropriate client for jobassignment.

START

GET THE DATABASEENTRIES

WHILE (CLIEINTINFORMATION DTO)

IS CPU USAGEMINIMUM

?

IS RAM USAGEMINIMUM

?

RETURN THE CLIENTNAME


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Project Methodology


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The stages of SDLC- Agile model:Agile Modeling is a practice-based methodology for modeling and documentation of

software-based systems. It is intended to be a collection of values, principles, and practices

for Modeling software that can be applied on a software development project in a more

flexible manner than traditional Modeling methods.

Agile software development is a group of software development methods based on

iterative and incremental development, where requirements and solutions evolve through

collaboration between self-organizing, cross-functional teams. It promotes adaptive planning,

evolutionary development and delivery, a time-boxed iterative approach, and encourages

rapid and flexible response to change. It is a conceptual framework that promotes foreseen

interactions throughout the development cycle.

Characteristics:

Agile methods break tasks into small increments with minimal planning and do not

directly involve long-term planning. Iterations are short time frames (timeboxes) that

typically last from one to four weeks. Each iteration involves a team working through a full

software development cycle, including planning,requirements analysis, design, coding, unit

testing, and acceptance testing when a working product is demonstrated to stakeholders. This

minimizes overall risk and allows the project to adapt to changes quickly.

Team composition in an agile project is usually cross-functional and self-organizing,

without consideration for any existing corporate hierarchy or the corporate roles of team

members.

Agile methods emphasize face-to-face communication over written documents when

the team is all in the same location.Agile development emphasizes working software as the

primary measure of progress. This, combined with the preference for face-to-face

communication, produces less written documentation than other methods.

Testing in Agile and Waterfall:One of the similarities of the agile and traditional methods, such as the waterfall

model of software design, is to conduct the testing of the software as it is being

developed.The key difference is that in the agile method, the customer and developers are in

close communication, whereas in the traditional method, the customer is initially represented

by the requirement and design documents.
http://en.wikipedia.org/wiki/Software_development_process_modelshttp://en.wikipedia.org/wiki/Software_development_process_models


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5.1 The Planning & Analysis Stage:

5.1.1 Opearational Feasibility Study:

The important things to consider while developing a load balancing algorithm are :estimation of load, comparison of load, stability of different system, performance of system,

interaction between the nodes, nature of work to be transferred, selecting of nodes and many

other ones. This load considered can be in terms of CPU load, amount of memory used, delay

or Network load.

Depending on the current state of the system, load balancing algorithms can be

divided into 2 categories as given below:

Static Load Balancing : It doesn t depend on the current state of the system. Prior knowledge

of the system is needed.

Dynamic Load Balancing : Decisions on load balancing are based on current state of the

system. No prior knowledge is needed. So it is better than static approach.

For the design of the dynamic load balancer we need some way of fetching out the

current state of the system frequently so that the balancing decision can be based upon it.

The entire system of balancing is divided into following 3 basic tasks:

Take out the information: The part of the dynamic load balancing algorithm responsible for

collecting information about the nodes in the system.

Select an appropriate system: It specifies the processors involved in the load exchange, i.e.

the part of the load balancing algorithm which selects a destination node for a transferred

task.

Execution of task: The part of the dynamic load balancing algorithm which selects a job for

transferring from a local node to a remote node.


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5.1.2 Technical Feasibility Study:

Specific Technology Keywords:

JAVA

Java is a high-level, third generation programming language, like C, FORTRAN,

Smalltalk, Perl, and many others. User can use Java to write computer applications that

crunch numbers, process words, play games, store data or do any of the thousands of

other things computer software can do.Compared to

other programming languages, Java is most similar to C. However although Java shares

much of C's syntax, it is not C. Knowing how to program in C or, better yet, C++, will

certainly help user to learn Java more quickly, but user don't need to know C to learn

Java. Unlike C++ Java is not a superset of C. A Java compiler won't compile C code, and

most large C programs need to be changed substantially before they can become Java

programs.What's most special about Java in relation to other programming languages is

that it lets One write special programs called applets that can be downloaded from the

Internet and played safely within a web browser.

. A Java applet cannot write to hard disk without permission. It cannot write to

arbitrary addresses in memory and thereby introduce a virus into your computer. It should

not crash system.

Java is the blend of the best elements of its rich heritages combined with the

innovative concepts required by its unique environment. It is the language grounded in

the needs and experiences of the people who devised it. Java is cohesive and logically

consistent. It gives the programmer full control. Its a language for professional

programmers. Java enhances and refines the object-oriented paradigm used by C++.

The original impetus for java was not the internet. Instead the primary motivation was

the nee d for platform independent. The goal for java developers was write once, run

anywhere any time forever .

Java code runs on variety of CPU under differing environments. It doesnt require

the expensive compiler to be built for each CPU separately.

In java there are clearly defined ways to accomplish a given task. It has various

packages and classes along with the grateful methods to implement vast requirements.

When developing a Java program it is important to select the appropriate Java Graphical

User Interface (GUI) components.


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Users have no way of checking these programs for bugs or for out-and-out

malicious behavior before downloading and running them. Java solves this problem by

severely restricting what an applet can do. Java was designed to make it much easier to

write bug free code. According to The most important part of helping programmers write

bug-free code is keeping the language simple.

Java is easy to learn:

Java was designed to be easy to use and is therefore easy to write, compile, debug,

and learn than other programming languages.

Java is object-oriented:

This allows you to create modular programs and reusable code.

Java is platform-independent:

One of the most significant advantages of Java is its ability to move easily from one

computer system to another. The ability to run the same program on many different systems

is crucial to World Wide Web software, and Java succeeds at this by being platform-

independent at both the source and binary levels.

Java is distributed:

Java is designed to make distributed computing easy with the networking capability

that is inherently integrated into it. Writing network programs in Java is like sending and

receiving data to and from a file.

Java is secure:

Java considers security as part of its design. The Java language, compiler, interpreter,

and runtime environment were each developed with security in mind.

Java is robust:

Robust means reliability. Java puts a lot of emphasis on early checking for possible

errors, as Java compilers are able to detect many problems that would first show up during

execution time in other languages.

Java is multithreaded:

Multithreaded is the capability for a program to perform several tasks simultaneously

within a program. In Java, multithreaded programming has been smoothly integrated into it,

while in other languages, operating system-specific procedures have to be called in order to

enable multithreading.


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The Sigar API

The Sigar API provides a portable interface for gathering system information such as:

System memory, swap, cpu, load average, uptime, logins Per-process memory, cpu, credential info, state, arguments, environment, open

files

File system detection and metrics Network interface detection, configuration info and metrics TCP and UDP connection tables Network route table This information is available in most operating systems, but each OS has their

own way(s) providing it.

SIGAR provides developers with one API to access this information regardless of the

underlying platform.The core API is implemented in pure C with bindings currently

implemented for Java, Perl, Ruby, Python, Erlang, PHP and C#.

MySQL 5.1

The following are the features that make MySQL worth sing in the project:

I. Partitioning:

This capability enables distributing portions of individual tables across a file system,

according to rules which can be set when the table is created.

II. Row-based replication:

Replication capabilities in MySQL originally were based on propagation of SQL

statements from master to slave. This is called statement-based replication .

III. Plugin API:

MySQL 5.1 adds support for a very flexible plugin API that enables loading and

unloading of various components at runtime, without restarting the server.

Although the work on this is not finished yet, plugin full-text parsers are a first step in

this direction. This permits users to implement their own input filter on the indexed text,

enabling full-text search capability on arbitrary data such as PDF files or other document

formats.

IV. Event scheduler:

MySQL Events are tasks that run according to a schedule. When you create an event,

you are creating a named database object containing one or more SQL statements to be


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executed at one or more regular intervals, beginning and ending at a specific date and

time.

V. Server log tables:

Before MySQL 5.1, the server writes general query log and slow query log entries to

log files.

JDBCJDBC is a Java-based data access technology (Java Standard Edition platform) from Sun

Microsystems, Inc.. It is not an acronym as it is unofficially referred to as Java Database

Connectivity. This technology is an API for the Java programming language that defines

how a client may access a database. It provides methods for querying and updating data in

a database. JDBC is oriented towards relational databases. A JDBC-to-ODBC bridge

enables connections to any ODBC-accessible data source in the JVM host environment.

JDBC allows multiple implementations to exist and be used by the same application. The

API provides a mechanism for dynamically loading the correct Java packages and

registering them with the JDBC Driver Manager. The Driver Manager is used as a

connection factory for creating JDBC connections.

JDBC connections support creating and executing statements. These may be update

statements such as SQL's CREATE, INSERT, UPDATE and DELETE, or they may be

query statements such as SELECT. Additionally, stored procedures may be invoked

through a JDBC connection.

NET BEANS 6.7

The following windows and tools are central to performing your daily

development tasks in the IDE:

Projects window Files window Runtime window Navigator window Source Editor GUI Builder Compiler


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long getUsed ()Get the Total used system memory.

double getUsedPercent ()Get the Percent total used system memory.

Table 5.2: Method Summary of Mem class of SIGAR.

SysInfo: this class has following methos that take out the information about OperatingSystem:

java.lang.String getDescription ()Get the description.

java.lang.String getMachine ()Get the machine.

java.lang.String getName ()Get the name.

java.lang.String getPatchLevel ()Get the patch_level.

java.lang.String getVendor ()Get the vendor.

java.lang.String getVendorCodeName ()Get the vendor_code_name.

java.lang.String getVendorName ()Get the vendor_name.

java.lang.String getVendorVersion ()Get the vendor_version.

java.lang.String getVersion ()Get the version.

Table 5.3: Method Summary of SysInfo class of SIGAR.

5.3.2. Module 2 Implementation of the Location Policy:

After receiving the details of all the clients connected in a network by using the

information policy, the location policy now transfers for the job to that respective

client. For this we use the following technology:

RMI:Java Remote Method Invocation

This is a technical literature study which purpose is to describe the basic parts

of Java Remote Method Invocation. Remote Method Invocation, abbreviated as RMI

provides support for distributed objects in Java, i.e. it allows objects to invoke

methods on remote objects. The calling objects can use the exact same syntax as for
http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/Mem.html%23getUsed()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/Mem.html%23getUsed()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/Mem.html%23getUsedPercent()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/Mem.html%23getUsedPercent()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getDescription()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getDescription()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getMachine()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getMachine()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getName()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getName()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getPatchLevel()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getPatchLevel()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getVendor()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getVendor()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getVendorCodeName()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getVendorCodeName()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getVendorName()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getVendorName()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getVendorVersion()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getVendorVersion()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getVersion()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getVersion()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getVersion()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getVendorVersion()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getVendorName()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getVendorCodeName()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getVendor()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getPatchLevel()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getName()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getMachine()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/SysInfo.html%23getDescription()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/Mem.html%23getUsedPercent()http://c/Users/PRASHU/Desktop/Cloudproject/hyperic-sigar-1.6.4/docs/javadoc/org/hyperic/sigar/Mem.html%23getUsed()


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local invocations. The Java RMI model has two general requirements. The first

requirement is that the RMI model shall be simple and easy to use and the second

requirement it that the model shall fit into the Java language in a natural way.

Distributed Object Application : An RMI application is often composed of two

separate programs, a server and a client. The server creates remotes objects and makes

references to those objects accessible. Then it waits for clients to invoke methods on

the objects. The client gets remote references to remote objects in the server and

invokes methods on those remote objects. The RMI model provides an distributed

object application to the programmer. It is a mechanism that the server and the client

use to communicate and pass information between each other. A distributed object

application has to handle the following properties:

Locate remote objects: The system has to obtain references to remote objects.

This can be done in two ways. Either by using RMIs naming facility, the

rmiregistry, or by passing and returning remote objects.

Communicate with remote objects: The programmer doesnt have to handle

communication between the remote objects since this is handled by the RMI

system. The remote communication looks like an ordinary method invocation for

the programmer.

Load class bytecodes for objects that are passed as parameters or return

values: All mechanisms for loading an objects code and transmitting data is

provided by the RMI system. Figure 2.1, below, illustrates an RMI distributed

application. In this example the RMI registry is used to obtain references to a

remote object. First the server associates a name with a remote object in the RMI

registry. When a client wants access to a remote object it looks up the object, by

its name, in the registry. Then the client can invoke methods on the remote object

at the server.


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Figure 5.1: An illustration of a distributed object application

Interfaces and Classes: Since Java RMI is a single-language system, the programming

of distributed application in RMI is rather simple. All interfaces and classes for the RMI

system are defined in the java.rmi package. Figure 2.2, below, illustrates the relationship

between some of the classes and interfaces. The RemoteObject class implements the

Remote interface while the other classes extend RemoteObject .

Figure 5.2: Interfaces and Classes in java.rmi package

The Remote Interface: A remote interface is defined by extending the Remote interface

that is provided in the java.rmi package. The remote interface is the interface that

declares methods that clients can invoke from a remote virtual machine. The remote

interface must satisfy the following conditions:

It must extend the interface Remote . Each remote method declaration in the remote interface must include the exception

RemoteException (or one of its superclasses) in its thrown clause.


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The RemoteObject Class: RMI server functions are provided by the class

RemoteObject and its subclasses RemoteServer , UnicastRemoteObject and Activatable .

Here is a short description of what the different classes handle:

RemoteObject provides implementations of the methods hashCode , equals and

toString in the class java.lang.Object .

The classes UnicastRemoteObject and Activatable create remote objects and export

them, i.e. the classes make the remote objects available to remote clients.

The RemoteException Class: The class RemoteException is a superclass of the

exceptions that the RMI system throws during a remote method invocation. Each remote

method that is declared in a remote interface must specify RemoteException (or one of

itssuperclasses) in its throws clause to ensure the robustness of applicatio ns in the RMI

system. When a remote method invocation fails, the exception RemoteException is

thrown. Communication failure, protocol errors and failure during marshalling or

unmarshalling of parameters or return values are some reasons for RMI failure.

RemoteException is an exception that must be handled by the caller of the remote method,

i.e. it is a checked exception. The compiler ensures that the programmer have handled

these exceptions.

Implementation of a simple RMI system: This is a simple RMI system with a client and

a server. The server contains one method ( helloWorld ) that returns a string to the client.

To build the RMI system all files has to be compiled. Then the stub and the skeleton,

which are standard mechanisms communication with remote objects, are created with the

rmic compiler. This RMI system contains the following files

HelloWorld.java: The remote interface.

HelloWorldClient.java: The client application in the RMI system. HelloWorldServer.java: The server application in the RMI system.

When all files are compiled, performing the following command will create the stud and

the skeleton:

rmicHelloWorldServer

Then the two classes will be created, HelloWorldServer_Stub.class and

HelloWorldServer_Skel.class , where the first class represents the client side of the RMI

System and the second file represents the server side of the RMI system.


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5.4 The Integration & Testing Stage:

MESSAGE

UPDATE

Figure 5.3: Integration of the system.

APPLICATIONMANAGER

DATABASE

COMMUNICATIONMANAGER

GUIMANAGER

RECEIVER MAIN WINDOW

WELCOME GOODBYE SYSTEMINFORMATION


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5.4.1 Integration of the system

The system is integrated in such a way that when its execution starts the application manager

is invoked. The application manager starts every time the application starts. The

application manager has two sub managers inside it named Communication manager and the

GUI manager.

The communication manager receives the packet coming from the node and tests it

for its category that is what the type of protocol is has that the data contained in.

The communication manager has 3 types of protocols namely Welcome protocol,

Goodbye protocol and SystemInformation protocol. The welcome protocol adds the name of

the client into the database, the Boodbye protocol deletes the name of client from the

database whereas the SystemInformation protocol updates database by adding current status

of the client machine. This is done by the handle protocol that is present inside all these three

protocols.

The operations performed by communication manager are taken into account by the

GUI manager that throws all the modifications done onto the screen and user sees the result.

5.4.2 Testing of the system

During the software development process, errors are inevitably introduced and some of them

are even amplified as a project progresses. Software Testing is the process of executing a

program or system with the intent of finding errors.

. Planning for software testing involves organizing testing at three levels unit, integration,

and high-order. The intent and scope of testing varies for these three levels. Planning for

software testing also involves procuring tools to automate testing and identifying the people

who will perform testing.

A problem with software testing is that testing all combinations of inputs and

preconditions is not feasible when testing anything other than a simple product. This means

that the number of defects in a software product can be very large and defects that occur

infrequently are difficult to find in testing.

More significantly, par functional dimensions of quality--for example, usability,

scalability, performance, compatibility, reliability--can be highly subjective; something that

constitutes sufficient value to one person may be intolerable to another.


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Software bugs will almost always exist in any software module with moderate size:

not because programmers are careless or irresponsible, but because the complexity of

software is generally intractable -- and humans have only limited ability to manage

complexity. It is also true that for any complex systems, design defects can never be ruled out

completely.

When Testing Is Carried Out?

A common practice of software testing is that it is performed by an independent group

of testers after the functionality is developed but before it is shipped to the customer. This

practice often results in the testing phase being used as project buffer to compensate for

project delays, thereby compromising the time devoted to testing. Another practice is to start

software testing at the same moment the project starts and it is a continuous process until the

project finishes.

. Testing is usually performed for the following purposes:

To improve quality

As computers and software are used in critical applications, the outcome of a bug can be

severe. Bugs can cause huge losses. Bugs in critical systems have caused airplane crashes,

allowed space shuttle missions to go awry, halted trading on the stock market, and worse.

Bugs can kill. In a computerized embedded world, the quality and reliability of software is a

matter of life and death.

Quality means the conformance to the specified design requirement. the minimum

requirement of quality, means performing as required under specified circumstances.

Debugging, a narrow view of software testing, is performed heavily to find out design defects

by the programmer. Finding the problems and get them fixed is the purpose of debugging in

programming phase.

For Verification & Validation

Testing can serve as metrics. It is heavily used as a tool in the Verification & Validation

process. Testers can make claims based on interpretations of the testing results, which either

the product works under certain situations, or it does not work. We can also compare the

quality among different products under the same specification, based on results from the

same test.


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We cannot test quality directly, but we can test related factors to make quality visible. Quality

has three sets of factors -- functionality, engineering, and adaptability. These three sets of

factors can be thought of as dimensions in the software quality space. Each dimension may be

broken down into its component factors and considerations at successively lower levels of

detail.

For reliability estimation

Software reliability has important relations with many aspects of software, including the

structure, and the amount of testing it has been subjected to. Based on an operational profile

(an estimate of the relative frequency of use of various inputs to the program testing can serve

as a statistical sampling method to gain failure data for reliability estimation.

The system is tested in steps, in line with the planned build and release strategies,

from individual units of code through integrated subsystems to the deployed releases and to

the final system. Testing proceeds through various physical levels of the application

development lifecycle. Each completed level represents a milestone on the project plan and

each stage represents a known level of physical integration and quality. These stages of

integration are known as test levels. Levels of testing include the following:

1. Unit Test - Verifies the program specifications to the internal logic of the program or

module and validates the logic.

2. Integration Test - Verifies proper execution of application components including

interfaces. Communication between modules within the sub-system is tested in a controlled

and isolated environment within the project. String testing is part of the Integration testing

level/phase which is both the detection as well as the correction of programming/code

generation problems. Once a series of components or unit, which must eventually work or

communicate with each other have been coded and unit tested, performance of an initial

"string" test is conducted. This "stringing" together of the components or units for execution

as a unit, tends to be a somewhat informal process directed at finding any communication or

parameter passing problems which may not yet have been detected. A "sign-off" should not

be given until the entirety of the connected/integrated units or components are working as a

smooth, seamless, and error free module.

3. System Test - Verifies proper execution of the entire application components including

interfaces to other applications. Both functional and structural types of tests are performed to

verify that the system is functionally and operationally sound.


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4. System Integration Test - Verifies the integration of all applications, including interfaces

internal and external to the organization, with their hardware, software and infrastructure

components in a production-like environment.

5. User Acceptance Test - Verifies that the system meets user requirements as specified. It

simulates the user environment and emphasizes security, documentation and regression tests.

6. Operability Test - Verifies that the application can operate in the production environment.

Operability tests are performed after, or concurrent with User Acceptance Tests.

When to stop testing?

Testing is potentially endless. We cannot test till all the defects are unearthed and

removed -- it is simply impossible. At some point, we have to stop testing and ship the

software. The question is when.

Realistically, testing is a trade-off between budget, time and quality. It is driven by profit

models. The pessimistic and unfortunately most often used approach is to stop testing

whenever some or any of the allocated resources -- time, budget, or test cases -- are

exhausted. The optimistic stopping rule is to stop testing when either reliability meets the

requirement, or the benefit from continuing testing cannot justify the testing cost. This will

usually require the use of reliability models to evaluate and predict reliability of the software

under test. Each evaluation requires repeated running of the following cycle: failure data

gathering -- modelling -- prediction. This method does not fit well for ultra-dependable

systems, however, because the real field failure data will take too long to accumulate.


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Figure 6.1: Main Window (1)

The output screen shows a scenario where there is only one client is connected to the

server.

The table on the screen shows the system details of the client connected to it.


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Figure 6.2: Main Window (2)

The output screen shows a scenario where there are three clients connected to the

server. The table on the screen shows the system details of the clients connected to it.


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Figure 6.3: Task Placement Window

This window allows the user to choose a task or application that he/she desires to use

on the cloud. Here weve two small applications: One is Factorial calculation and

another is the File Read Service.


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Figure 6.4: Factorial Task Placement

The figure shows that the task is placed to the client which was least loaded and gives

client-name and total time required for the execution along with the result.


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Figure 6.5: File Read Task Placement

The figure shows that the task is placed to the client which was least loaded and gives

client-name and total time required for the execution along with the result.


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Figure 6.6: The About Window


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Advantages & Applications


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Advantages

In complex and large systems, there is a tremendous need for load balancing. For

simplifying load balancing globally (e.g. in a cloud), one thing which can be done is,

employing techniques would act at the components of the clouds in such a way that the

load of the whole cloud is balanced.

Applications

This application is useful in all types of load balancing applications whether it is

sender initiated or receiver initiated or symmetric load balancing technique where the

parameters like CPU usage, memory usage, network load, etc. have got greater significance.

The application can also be modified so that it can modularize the task and assign its

subparts to different clients present in the network.

This module can be useful with both centralized and decentralized computing

environment. The modularization of the tasks into smaller subtasks speeds up the computing

process and improves the performance.


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Future Scope & Conclusion


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Future Work

Cloud Computing is a vast concept and load balancing plays a very important role in

case of Clouds. There is a huge scope of improvement in this area. We have discussed onlytwo divisible load scheduling algorithms that can be applied to clouds, but there are still other

approaches that can be applied to balance the load in clouds. The performance of the given

algorithms can also be increased by varying different parameters.

This module can further be refined by adding feature of modularizing of the

larger tasks into smaller ones so that services that need more time and hardware may be

executed by different clients on the network and thereby improving performance and

reducing execution time.

ConclusionCloud computing provides a Service Oriented Architecture (SOA) and Internet of

Services (IoS) type applications, including fault tolerance, high scalability, availability,

flexibility, reduced information technology overhead for the user, reduced cost of ownership,

on demand services etc. Central to these issues lies the establishment of an effective load

balancing algorithm.

A load balancer provides the means by which instances of applications can beprovisioned and de-provisioned automatically, without requiring changes to the network or its

configuration. It automatically handles the increases and decreases in capacity and adapts its

distribution decisions based on the capacity available at the time a request is made.


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Publications


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Paper 1: Deepti Agrawal, Swati Nasre, Vibhuti Kumar Upadhyay, Mohammed Taslim Alam Ansari Presented a paper on topic Load Balancing in Cloud Computing on a national level event SPITZE 2012 on 18/2/2012 held at J. L. Chaturvedi College of Engineering,

Nagpur.


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Load Balancing in Cloud ComputingDeepti Agrawal Vibhuti Upadhyay Md. Taslim Alam Ansari Swati Nasre B.E. (CSE) B.E. (CSE) B.E. (CSE) B.E. (CSE)

J. L. C. C. E., J. L. C. C. E., J. L. C. C. E., J. L. C. C. E.,Nagpur Nagpur Nagpur Nagpur

Abstract: Managing large compute clusters requiresbenchmarks with representative workloads toevaluate performance metrics such as taskscheduling delays and machine resourceutilizations, machine configurations, and schedulingalgorithms. Existing approaches to workloadcharacterization for high performance computingand grids focus on requirements for CPU, memory,disk, I/O and network. However, in addition toresource requirements, cloud computing workloadscommonly include task placement constraints. Taskplacement constraints (hereafter, just constraints)address machine heterogeneity, diverse applicationrequirements, application optimization, and faulttolerance. Constraints limit the machines on which atask can run. A load balancer provides the means bywhich instances of applications can be provisioned andde-provisioned automatically, without requiringchanges to the network or its configuration. Itautomatically handles the increases and decreases incapacity and adapts its distribution decisions based onthe capacity available at the time a request is made.Because the end-user is always directed to a virtualserver, or IP address, on the load balancer the increaseor decrease of capacity provided by the provisioningand de-provisioning of application instances is non-disruptive. As is required by even the most basic of cloud computing definitions, the end user is abstractedby the load balancer from the actual implementationand needs not care about the actual implementation.The load balancer makes one, two, or two-hundredresources - whether physical or virtual appear to beone resource; this decouples the user from the physicalimplementation of the application and allows theinternal implementation to grow, to shrink, and tochange without any obvious affect on theuser.

Introduction

Cloud computing is where software applications,processing power, data and potentially even artificialintelligence are accessed over the Internet. Today thecloud computing is gaining much more importance inthe IT field as it provide different types of servicesnamely Saas (Software as a service), Paas (Platformas a service) and Iaas (Infrastructure as a service )also known as Haas (Hardware as a service). Due toon demand service by the cloud vendor the use of cloud computing as tremendously increased and inturn there is a basic need to balance the load of thetask placed by the client. This requires certain

benchmarks like CPU Utilization, RAM utilization,Operating system needed. In order to understand

these concepts in better way consider the examplegiven below.

Figure 1: Illustration of the impact of constraints onmachine utilization in a Load Balancing in CloudComputing By combination of the line thickness andstyle. Task can be scheduled only on the machinesthat have the corresponding line thickness and style.Figure 1 illustrates the impact of constraints onmachine utilization in a compute cluster. There aresix machines M1, , M6 (depicted by squares) and

ten tasks T1, , T10 (Depicted by circles). There arefour constraints c1, , c4. Constraints are indicatedby the combinations of line thickness and line styles.In this example, each task requests a singleconstraint, and each machine satisfies a singleconstraint. A task can only be assigned to a machinethat satisfies its constraint; that is, the line style andthickness of a circle must be the same as itscontaining square. One way to quantify machineutilization is the ratio of tasks to styles. In thisexample, each task requests a single constraint, andeach machine satisfies a single constraint. A task canonly be assigned to a machine that satisfies its

constraint; that is, the line style and thickness of acircle must be the same as its containing square. Oneway to quantify machine utilization is the ratio of tasks to machines. Proposed Architecture: Theproposed architecture for load balancing comprisesof client side program, a central server program andclustered server program. The several clusterconnected with the central server sends its OS,RAM and CPU information to the central server.When the client issues any request the centralserver checks the configuration of the entiremachine and send the task for execution to thatmachine whose response time is less than a second.

Those clusters whose response time is very highwill not be given the task for execution as it canincrease the scheduling delay in the


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Application:1. Efficiently manages the task placement in computecluster.2. Efficiently manages the task placement in distributednetwork.

References:1. M. F. Arlitt and C. L. Williamson. Web serverworkload characterization: the search for invariants. InProceedings of the ACM SIGMETRICS international

conference on Measurement and modeling of computersystems, 1996.2. P. Barford and M. Crovella. Generating representativeweb workloads for network and server performanceevaluation. In Proceedings of the ACM SIGMETRICSinternational conference on Measurement and modelingof computer systems, 1998.3. M. Calzarossa and D. Ferrari. A sensitivity study of the clustering approach to workload modeling.SIGMETRICS Performance Evaluation Review, 1986.


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Bibliography


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deepti project report - copy

Documents