SERVICE LEVEL AGREEMENT PARAMETERS FOR …ijsk.org/uploads/3/1/1/7/3117743/2_ecommerce_cloud.pdfECOMMERCE CLOUD AbdelSalam H ... then conclusion of this paper will be in Section 5

Feb. 2014. Vol. 4, No.6 ISSN 2305-1493 International Journal of Scientific Knowledge Computing and Information Technology

© 2012- 2014 IJSK & K.A.J. All rights reserved www.ijsk.org

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SERVICE LEVEL AGREEMENT PARAMETERS FOR

ECOMMERCE CLOUD

AbdelSalam H. Busalim

1 Ab Razak Che Hussin

1

1 Universiti Teknologi Malaysia, Faculty of Computing, Skudai, Jorhor Bahru, Malaysia (www.utm.my)

ABSTRACT

Nowadays Services Level Agreement (SLA) became an important aspect between the cloud consumer and

cloud provider, the dynamic nature of cloud computing needs to continue monitoring of the services. The

restricted choice of appropriate parameters in SLA affects the interacting of end user with cloud services

and creates risks of user data. End users are concerned about their data and how it will be stored in cloud

and how the data is recovered in the case of failure of disaster. However, none of SLAs consider the end

user view while conducting the SLA document. This paper discusses the importance of the parameters

which need to be included in SLA when ecommerce companies move to cloud services, In order to verify

and validate these parameters in ecommerce cloud, data were collected from105 respondents in faculty of

computing in Universiti Teknologi Malaysia. The results indicate that most of the selected parameters are

significant from the end users point of view.

Keywords: SLA, Cloud Computing, ecommerce cloud

1. INTRODUCTION

Cloud technology is becoming an

increasingly popular trend. As a new concept, cloud computing offer online software and hardware capabilities. It offers a secure online environment for data storage and various e-commerce services that maintain the latest technologies and continuous protections for clients. Many ecommerce companies are turning to cloud computing and services due to the cost-efficiency it offers. According to the Gartner group report, by 2013, 40 % of e-commerce companies will use a complete cloud services (SaaS) solution. It appears that cloud computing is set to change the ways in which businesses operate [1]. Form the business perspective, cloud computing offers a great number of benefits including reduced infrastructure and maintenance costs.

Many e-commerce companies and retailers have

moved to cloud services due to the many benefits

this shift offers in regards to cost effective and

easily accessible storage options, and elastic

computing and infrastructure. In 2012, the Gomez

application performance monitor report clearly

showed that among the 50 well known online

retailers, 40% use Amazon cloud-based

applications. However, there a number of risks

associated with this reliance on outside services,

especially from the perspective of end users. For e-

commerce cloud companies, the end user is an

important capital; therefore, satisfaction of the end

user is a major goal of e-commerce cloud service

providers. Among the risks the end user potentially

faces when engaging in cloud-based e-commerce, is

the issue of confidentiality of data, how data is

stored, and who has access to this data. Another

problem concerns privacy. The dynamic cloud

environment makes it difficult for cloud providers to

observe current data protection regulations and

privacy policies [2]. The majority of current cloud

contracts are little concerned with consumer privacy

and consumers are often poorly informed about

privacy issues [3].

One method of ensuring that the client receives the correct services best suited to its needs is the SLA, which has transformed from being a financial contract into a managerial tool to ensure the expectations of the customer are met [4]. For this mechanism to be effective there is a need for clear definitions of services, and suitable measuring parameters to measure the level of services. In the cloud computing environment, computer resources and infrastructures that are offered are scalable, and the platform, software and infrastructure provided in the form of services can be accessed anytime and anywhere. However, provisioning this paradigm of

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http://www.utm.my/



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cloud services requires specific SLAs for every type of services. This can be rather challenging in view of the diverse range of services offered by cloud computing services, the various levels of each service, and the diverse needs of clients. No two clients are identical.

This paper organized as follow. Section 2

highlights the literature review, Section 3 explains the methodology adopted by this paper, Section 4 will cover the results and discussion of the paper, then conclusion of this paper will be in Section 5.

2. LITERATURE REVIEW

A. Risks and Challenges in E-Commerce Cloud

In ecommerce cloud sellers ,a large number

of users information is stored in the cloud ,and

transmission and processing taking place in cloud,

therefore, the problems and risks more than

traditional e-commerce model [5]. Increasingly,

online retailers are relying on cloud services and

applications such as storage, computing, comparison

engines, product locators and dynamic imaging to

run their businesses. With this relying on outside

services high risks raised out . As a result, they are

losing control of the end user experience.

The confidentiality of the user’s data is one

of the main risks facing ecommerce cloud. In e-

commerce cloud, most of the business information

is stored in the cloud therefore, e-commerce

companies are not able to supervise and monitor

user's sensitive information. As virtualization

technology been used in cloud computing, e-

commerce companies using cloud services are not

clear about where the data been stored, and do not

even know the physical location of that data.[5]. The

European Network and Information Security

Agency (ENISA), conducted a survey for the main

cloud computing security issues. More than 70 % of

the SME (small and medium enterprises) in this

study are concerned by the first six criteria and more

specifically by confidentiality of data. Privacy are

another important issue in Cloud Computing. The

dynamic nature and structure of Cloud environment,

make it difficult for Cloud providers to follow the

current data privacy and protection rules. The main

reasons beyond this, the transnational nature of

Cloud Computing that has to face the national

nature regulation privacy[2].

Transparency towards cloud services users must be

the golden rule. Users do not know where the data

stored and by whom it will be finally processed. It

is compulsory for Cloud services providers to

inform the users about the way in which data are

processed . In the case of e-commerce Companies

concern about the end user personal data, these

important and private data may contain names,

addresses, e-mail addresses and credit card numbers

[2]. As known, that virtualization is one of the

backbone of cloud computing technology, therefore

there are some security risks in sharing machines for

instance, losing control over data location, and who

has the right to access to user data. [6]

B. Services Level Agreement (SLA)

To achieve high quality and performance

goals in services or products, it may need the

enterprise to establish and manage service level

agreement (SLA) between the enterprise which

provides the business service or product and the

consumers, companies are responsible for its

shareholders, expectations of the level of service to

be offered [7]. The main goal of establishing SLA

process is to improve the Quality of Experience of

the service or product to the enterprise customer and

reach the satisfaction level .

However Service level Agreement (SLA) is a

document describes the level of service expected by

a customer from a services provider, based on

metrics or policies by which that services are

measured, and penalties if any, should the agreed-

upon levels not be achieved. Usually, SLA is

between companies and external suppliers[8].A

service level agreement can be an extremely

effective communication tool for creating a common

understanding between two parties regarding

services , expectation , responsibilities and priorities

[9]. Cloud technology as new paradigm of

computing where available computing resources are

delivered as a service. These resources are generally

offered under the concept of pay-as-you-use,

therefore cloud services become attractive to cost

conscious customers. In order for Cloud providers to

provide customers with services that meet their

demands, both sides need to negotiate the client's

requirements and the provider's services

capabilities, and then they agree to certain

conditions and terms which is the services level

agreement [10]. The figure below shows the SLA

parties in cloud environment.




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Figure 1: SLA parties in cloud environment

.

The main purpose of SLAs is to set a

framework for the providing services and for the

cooperation among service providers and service

consumers[2]. However the concept of "everything-

as- services" offered by in cloud manner, this

paradigm has made the establishment of SLA more

challenging and makes the relation among the cloud

providers and users getting more complex.

C. Services Level Agreement Parameters

The SLA in cloud computing It consists of a

set of measurable attributes called SLA parameters

which are established by some objectively

measurable conditions, termed as Service Level

Objectives (SLOs)[11]. The parameters used to

measure and manage performance compliance to

SLA commitments are the key of successful

agreements and are a critical long term success

factor[12]. There are examples include the

parameters of throughput and timing, also the

percentage of availability of virtual machines and

other resources, these objectives can be written in

the SLA in the form below: [13].

Availability of a service X is 99.5%

Response time of a database query Q is

between 3 to 5 seconds

Throughput of a server S at peak load time

is 0.875.

There are several many studies have been

conducted related to SLA in cloud computing

environment. [11] pointed out that the SLAs

provided by the presented cloud providers are

relatively biased towards cloud providers and do

not provide any formal method of verifying if the

guarantees are complying or not, therefore the

author attempted to identify the SLA parameters

for Storage-as-a-Service in cloud delivery model

and also the objectives for measuring these

parameters and finally he proposed a monitoring

framework for compliance checking.[14] proposed

a framework to minimize the issues of

trustworthiness among the cloud service provider

and cloud consumer, by using a quantitative model

of trust. They identified and formalized several

parameters which has derived from SLA, these

parameters to estimate trust. In this framework, the

identified set of parameters have categorized into

two sets. The first set of parameters obtained from

the SLA description and named as Pre-SAL

parameters. These parameters are obtained in trust

estimation before signing the SLA contract, which

can to help to build the consumer’s initial trust on

the cloud provider. However, most of cloud service

providers focus only on small set of parameters,

namely Availability, request completion rate and

response time.[15] conducted a study to break

down the Cloud SLA into easy and understandable

components and compare the SLAs of the

considered public cloud provider. By comparing the

SLA of Amazon, Rackspace, Microsoft, Terremark

vCloud Express and Storm on demand, the study

highlighted that none of those providers offer nay

performance guarantee for the services

nevertheless, none of the providers automatically

credit the consumer for SLA violation, consumer

should detect the SLA violation. The problems and

unfulfilled expectations during accomplishing the

SLA are the result of , poor choice of

parameters[12].

As we mentioned in our previous paper [16] that In ecommerce cloud, to alleviate the risks and challenges facing the end user during using




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ecommerce cloud websites, suitable parameters need to be included in SLA to consider the end user perspective. The table below describes the extracted parameters for E-commerce cloud SLA, which can be used for Managing and monitoring the Quality of services delivered by cloud providers.

3. METHODOLOGY

This section basically illustrates the activities

for every phase in the research, which should be

carried out for this paper. There are four phase in

the research methodology which are illustrated in

the figure 2 below. From the literature review phase

we have found out some potential limitations in the

SLA parameters and frameworks provided by cloud

services providers, especially in the context of the

e-commerce cloud. The current SLAs mentioned

only the availability of the service and the

performance level of the services, in e-commerce

environment most of the companies have moved to

cloud service, however the ecommerce end user in

cloud computing environment facing risks during

communicating with ecommerce cloud

websites and, the SLA between the cloud provider

and ecommerce company does not consider these

risks, and the user should be aware for this SLA.

After identifying the main SLA parameters which is

based on the risk and challenging in ecommerce

cloud, a questionnaire is constructed to verify the

end user perceptions regarding the importance of

these parameters. This research is using quantitative

method for collecting data. The questionnaire

consist of two parts, the first part is the

demographic part and part B is questions which

related to parameters. Content validity process has

been conducted before distributing the

Parameters Description Citations

Availability The uptime of the services for the user in specific time

[15, 17] [18] [19] [11] [20] [21]

Scalability Ability to increase and decrease the storage space

[21] [19] [18]

Portability The services working on different devices or different platforms

[21] [19] [18]

Performance The duration of time to respond on user's requests

[17] [20] [19] [18] [15] [14]

Security The security of user data and the safety of the environment in the cloud

[17] [19] [18]

Reliability Services ability to operate over the time without failure

[21] [19] [18]

Usability The ability of the service to be attractive ,understandable, learnable, operable

[19] [21] [18]

Backup &

Recovery

How the Service store the image of user data and the ability to recover data in disaster.

[17] [18] [15] [14]

Data location Availability zones in which the data are stored

[18]




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questionnaire, by asking two experts in faculty of

computing in Universiti Teknologi Malaysia

(UTM), to make sure that the questionnaire is well

organized and the questions is easy to understand.

The final modified questionnaire has been distributed online using Survey Monkey tool. The

sample size of the respondents after distributing the

final questionnaire is 105 students, and the time for

collecting the data was around two weeks The

respondents are the postgraduate and undergraduate

students of computing faculty in UTM.

Figure2: Research framework

Table 2 shows the structure of part B in the final

questionnaire distributed. The structure of this part

of the questionnaire represents the parameters

which extracted from literature review. The first

column shows the parameters of SLA, the second

column shows the questions of each parameters

based on the objectives related to that parameter,

and the last column represent the ID of each

questions to make the process of analyzing easy

and achievable. The aim this part of the

questionnaire is to know the end user point view

regarding the proposed parameters and how these

parameters can reduce the risks in ecommerce

cloud Therefore, to validate the collected data form

questionnaire, SPSS statistical analysis software

has been used in this research.




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Table 2. Structure of the questionnaire

4. RESULTS AND DISCUSSION

A. Demographic Analysis

Most of the respondents are male, 80

students out of 105 which represent 76% of the

respondents where the rest of the respondent are

female with approximately 24% as it can been seen

in figure 3.

Figure 3. Information on respondent's gender




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Figure 4 shows the level of education of the

respondents, the highest number of the respondents

are Masters students which represent 69% of the

total respondents , where 18% of them are bachelor

degree students and 10% are Phd students.

While the rest are 1.9% are new undergrad

students. As mentioned earlier the scope of the

respondents was limited in student of faculty of

computing, in order to make sure the answers are

accurate regarding the parameters which can be

used in ecommerce cloud environment.

Figure 4: Education level of the respondents

Figure 5 explains the information of

respondent about how frequently they buy online.

Based on the graph below, the major number of the

respondent is buying once a month which represent

33.3%. The second is 28% which buy online once

in every year and 22.8% represent the frequency of

buying once in sex month, while 11.4% of the

respondents buy once in every week. The less

number represent 3.8% who are buy every day.

Figure 5: Frequency of buying online




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Another results shows the experience of the

respondents about cloud computing applications.

The major number of the respondents (54 students)

using cloud applications between 2 to 4 years

which represent 51.4% from the whole respondents.

While 33.3% of the respondents using cloud

from less than one year and the rest of the

respondents using cloud from 5 to 7 years which

represent 14.2%. From the figure above, it can be

pointed that majority of the respondents know very

well the concept of the cloud computing. Figure 6

illustrates these results.

Figure 6: Respondents experience in using cloud

B. Descriptive statistics

Cronbach's alpha method used to measure

the internal consistency, which means how closely

the item are related to each other as group . In

Cronbach's alpha the reliability should be more than

.70 in order to consider the items are. The result of

Cronbach's alpha reliability analyze is .961 as

shown the table below.

Table 3: Reliability Statistics for Questionnaire

Cronbach's

Alpha

Cronbach's

Alpha Based on

Standardized

Items

N of Items

.961 .965 31




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The tables below shows the Descriptive statistics

Analysis for the parameters The tables show the

Descriptive statistics for each variables in the

questionnaire as listed in table 1. In part B of the

questionnaire the weight is (1.Strongly Disagree,

2Disagree, 3 Neutral, 4 Agree, and 5Strongly

Agree).

Table 5. Descriptive Statistics

Variables N Mean Std.

Deviation

SEC1 88 4.34 .815

SEC2 84 4.58 .779

SEC3 87 4.54 .775

SEC4 86 4.36 .825

SEC5 87 4.52 .819

SEC6 85 4.49 .854

SEC7 87 4.45 .743

PRF1 88 4.02 .934

PRF2 87 4.30 .794

PRF3 85 4.18 .833

PRF4 87 4.07 .832

PRF5 85 4.25 .844

PRF6 88 4.20 .833

USE1 88 4.38 .778

USE2 86 4.33 .913

USE3 88 4.33 .827

Table 6. Descriptive Statistics

Variables N Mean Std.

Deviation

AVL1 88 4.43 .841

AVL2 87 4.45 .789

DLC1 85 3.33 1.189

DLC2 85 3.61 1.114

BKRC1 85 4.28 .781

BKRC2 85 4.22 .905

BKRC3 85 4.27 .892

BKRC4 84 4.18 .946

RBY1 85 4.19 .764

RBY2 85 3.51 .840

RBY3 85 4.08 .848

SBLY1 85 4.13 .753

SBLY2 84 4.31 .744

PROT1 85 4.41 .678

PROT2 83 4.40 .748




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According to Table 5 and 6 most of the items

have higher means which means all the items are

important and significant from the end user point of

view, we considered the items who have higher

means as most important for user perspective.

C. Factor Analysis

Factor analysis is data reduction technique,

which used to structure large number of items in

the questionnaire. Factor Analysis also used to

minimise the redundancy between items and to

group the items based on the inter correlation

between these items. Since this study to identify

the main important parameters for SLA cloud

commerce, factor analysis has been used to remove

the inappropriate items which are not suitable or

not belong to any parameters.

The first output of factor analysis showed in

table 7 is a Kaiser-Meyer-Olkin measure of

sampling adequacy and Bartlett‟s Test. In KMO and

Bartlett's Test the value should be greater than 0.5 in

order to consider the sample is adequate and suitable

for applying factor analysis. According to the table

above the value of KMO test for this study is .732

which greater than 0.5 meaning that ,the

questionnaire sample is suitable to conducting

factor analysis.

Table 7 : KMO and Bartlett's Test Analysis

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .732

Bartlett's Test of Sphericity

Approx. Chi-Square 2149.043

df 465

Sig. .000

The last output of the factor analysis is

Communalities Analysis. Table 8 and 9 below

explain the communalities before and after

extraction which highlight shows how much of the

variance for the variables accounted for by the

extracted factors. For example over 80% of variance

in Parameter NO.2 (security2) is accounted while

50% of the variance in parameters No.27 (reliability

3) is accounted. From the factor analysis results we

can highlight that all the parameters and their

objectives are significant and recognized are

important from the end users perspective, which

may improve the quality of the SLA between the

cloud providers and ecommerce seller by

considering the end user perspective during

conducting the negotiations process between the two

parties. Considering end use perspective toward

cloud services in the SLA can increase their trust

and also the reputation of the ecommerce seller well

be increased.




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Table 8. Communalities Analysis

Item Initial Extraction

SEC1 1.000 .711

SEC2 1.000 .804

SEC3 1.000 .823

SEC4 1.000 .715

SEC5 1.000 .808

SEC6 1.000 .808

SEC7 1.000 .676

PRF1 1.000 .697

PRF2 1.000 .785

PRF3 1.000 .811

PRF4 1.000 .632

PRF5 1.000 .756

PRF6 1.000 .692

USE1 1.000 .750

USE2 1.000 .809

USE3 1.000 .725

Table 9. Communalities Analysis

Item Initial Extraction

AVL1 1.000 .694

AVL2 1.000 .704

DLC1 1.000 .782

DLC2 1.000 .770

BKRC1 1.000 .653

BKRC2 1.000 .797

BKRC3 1.000 .820

BKRC4 1.000 .787

RBY1 1.000 .607

RBY2 1.000 .492

RBY3 1.000 .567

SBLY1 1.000 .759

SBLY2 1.000 .719

PROT1 1.000 .782

PROT2 1.000 .671




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5. CONCLUSION

Service Level Agreement has significant impact on

ecommerce websites which using cloud services,

SLA can guarantee the services provided to the

ecommerce websites and protecting ecommerce

user by applying appropriate parameters. This paper

introduced ecommerce cloud SLA parameters

which consider the ecommerce cloud end users,

these parameters has been selected based on the

risks facing the user during interacting with

ecommerce cloud, the parameters validated by

conducting a survey inside Faculty of computing in

UTM. The results indicates that all the parameters

are important from end user point of view.

However this research included only the student in

faculty of computing as respondents . Futures work

should cover wider variety of respondents

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SERVICE LEVEL AGREEMENT PARAMETERS FOR …ijsk.org/uploads/3/1/1/7/3117743/2_ecommerce_cloud.pdfECOMMERCE CLOUD AbdelSalam H ... then conclusion of this paper will be in Section 5