ABSTRACT

The use of Cloud Computing Services appears to offer significant

cost advantages. Particularly start-up companies benefit from these advantages,

since frequently they do not operate an internal IT infrastructure. But are costs

associated with Cloud Computing Services really that low? We found that

particular cost types and factors are frequently underestimated by practitioners.

In this paper we present a Total Cost of Ownership (TCO) approach for Cloud

Computing Services. We applied a multi-method approach (systematic literature

review, analysis of real Cloud Computing Services, expert interview, case study)

for the development and evaluation of the formal mathematical model. We

found that our model fits the practical requirements and supports decision

making in Cloud Computing.

EXISTING SYSTEM
The focus of the analysis lies in the cost comparison of different
Cloud Computing Services and service models. As a result, purchasing costs for servers
are not considered in the model. A change of a service provider corresponds to the

first adoption of a Cloud Computing Service: If aprovider change is taking place,

it should be considered as a deployment of a new Cloud Computing Service. The

reason for this is that the steps for the initial deployment of a Cloud Computing

Service are the same as that of a change here we does not consider cloud storage

hidden cost .
PROPOSED SYSTEM

The total cost of ownership approach is one of the most important cost-

oriented approach. The main focus of our model lies in the identification and

calculation of cost factors. The software tool is able to analyze the cost structure

of Cloud Computing Services and thus supports decision makers in validating

Cloud Computing Services from a cost perspective. TCO approach makes it

possible to analyze the costs or individual cost components of an IT artifact by

means of a predefined scheme. TCO is a software tool to calculate setting-up and

maintenance costs for a cloud(costs of storage, data transfer)computing.

MODULE DESCRIPTION:
1. Cloud Computing.

2. Fixing Pricing Scheme.

3. Calculating Cost Factor.

4. User Module.

• cloud computing
Cloud computing is a model for enabling convenient, ondemand

network access to a shared pool of configurable computing resources (for

example, networks, servers, storage, applications, and services) that can be

rapidly provisioned and released with minimal management effort or service-

provider interaction. It divide into three type

1.Application as a service.
2.Infrastructure as a service.

3.Platform as a service.

Cloud computing exhibits the following key characteristics:

1. Agility improves with users' ability to re-provision technological infrastructure

resources.

2. Cost is claimed to be reduced and in a public cloud delivery model capital

expenditure is converted to operational expenditure. This is purported to
lower barriers to entry, as infrastructure is typically provided by a third-party and
does not need to be purchased for one-time or infrequent intensive computing tasks.
Pricing on a utility computing basis is fine-grained with usage-based options and
fewer IT skills are required for implementation. The e-FISCAL project's state of the
art repository contains several articles looking into cost aspects in more detail, most
of them concluding that costs savings depend on the type of activities supported and
the type of infrastructure available in-house.

3. Virtualization technology allows servers and storage devices to be shared and

utilization be increased. Applications can be easily migrated from one physical server
to another.

4. Multi tenancy enables sharing of resources and costs across a large pool of

users thus allowing for:

5. Centralization of infrastructure in locations with lower costs (such as real

estate, electricity, etc.)

6. Utilization and efficiency improvements for systems that are often only 10–
20% utilized.

7. Reliability is improved if multiple redundant sites are used, which makes well-
designed cloud computing suitable for business continuity and disaster
recovery.
 8. Performance is monitored and consistent and loosely coupled architectures are
constructed using web services as the system interface.

9. 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. Security is often as good as or better than other
traditional systems, in part because providers are able to devote resources to solving
security issues that many customers cannot afford. However, the complexity of security is
greatly increased when data is distributed over a wider area or greater number of devices
and in multi-tenant systems that are being shared by unrelated users. In addition, user
access to security audit logs may be difficult or impossible. Private cloud installations are
in part motivated by users' desire to retain control over the infrastructure and avoid losing
control of information security.

10. 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.

• Fixing pricing scheme.

TCO approach makes it possible to analyze the costs or individual

cost components of an IT artifact by means of a predefined scheme. The cost

structure and identification of cost types have been initially created on the basis

of real Cloud Computing Services and the identified literature. Finally the results

of the expert interview approved and extended our model.

• Calculating cost factor.

 This calculation scheme is applied for calculate the storage inbound,

outbound, data transfer costs. The storage cost is calculation is depended on the

user storage capacity and time. Most cloud storage providers offer hourly

(usage-dependent) Component - based rates. The costs incurred depend on the

particular pricing.

• User Module:

The user can store own data in cloud storage area. They can view

cloud storage data at any time. They user should pay cost for the cloud storage.

H/W System Configuration:-

Processor - Pentium –III

Speed - 1.1 Ghz

RAM - 256 MB(min)

Hard Disk - 20 GB

Floppy Drive - 1.44 MB

Key Board - Standard Windows Keyboard

Mouse - Two or Three Button Mouse

Monitor - SVGA

S/W System Configuration:-

 Operating System :Windows95/98/2000/XP

Application Server : Tomcat5.0/6.X

Front End : HTML, Java, Jsp

Scripts : JavaScript.

Server side Script : Java Server Pages.

Database : Mysql

Database Connectivity : JDBC.

CONCLUSION
The TCO approach should be regarded as one part of a comprehensive IT cost

and as an additional method to evaluate a Cloud Computing Service. That need

to be considered for its practical application . First, we made some restrictive

assumptions that support us in taking a particular focus on Cloud Computing

Services. Thus, we hide cost types that focus for instance on an existing internal

IT infrastructure and their cost factors If a company plans to implement a private

Cloud these additional cost types are necessary for a complete evaluation. Since

our approach focuses strongly on the evaluation of Cloud Computing Services

that are frequently provided externally, we feel that these assumptions simplify

the cost evaluation approach and its applicability. Furthermore, we do not

consider quality or functional aspects of Cloud Computing Services within our

method. Implications for the scientific community are aiming at several new
fields that have not been discussed extensively in the scientific literature on

Cloud Computing yet. For instance, we found that current work strongly focuses

on risk and security aspects of Cloud Computing. However, we did not find an

approach that combines risk and security aspects by means of an TCO approach.

Additionally, benefits management in Cloud Computing is another new research

field that can for instance be explored by means of cost-benefit analyses [14] in

real world scenarios that reveal more insights on economic and managerial

success factors in Cloud Computing. Additionally, further research can tackle

some of the stated limitations. With regard to our TCO model we are planning to

anonymously collect and store data that has been applied to the software tool.

They can be statistically analyzed to better understand decision making in Cloud

Computing. Moreover, it is possible to include an AHP process for the

evaluation of quality of service compared to the results of the TCO model.