Efficient Virtual Universities via Cloud Computing Environment

VOL. 3, NO.11 Nov, 2012 ISSN 2079-8407

Journal of Emerging Trends in Computing and Information Sciences ©2009-2012 CIS Journal. All rights reserved.

http://www.cisjournal.org

1553

Efficient Virtual Universities via Cloud Computing Environment 1 Muzhir Shaban Al-Ani,

2 Mohammed Salah Ibrahim

1, 2 Anbar University, College of Computer, Iraq 1 [email protected], 2 [email protected]

ABSTRACT Cloud computing is a new field of processing that offers many facilities for business and scientific applications. The

primary purpose of this study is to propose an efficient solution of the ministry of higher education and scientific research

in Iraq. The proposed solution based on classification of the environment into main three clouds: governmental

universities, private universities and commissions and research centers. Theses clouds may be operated at real time and

any access can be replayed directly without any delay.

Keywords: Cloud computing, grid computing, virtual environment, virtual university.

1. INTRODUCTION Cloud computing has emerged as a viable

platform for running large-scale computation and data

analysis [1]. Cloud computing is the solution for:

researchers whose need on-demand high performance

computers, institutions that need to provide their

employers with all required applications in easy and

economy situations and for all others whose need to carry

their data without carry their computers.

Why would anyone want to rely on another

computer system to run programs and store data? Here are

just a few reasons [2]:

Clients would be able to access their

applications and data from anywhere at any

time. They could access the cloud computing

system using any computer linked to the

Internet. Data wouldn't be confined to a hard

drive on one user's computer or even a

corporation's internal network.

It could bring hardware costs down. Cloud

computing systems would reduce the need

for advanced hardware on the client side.

You wouldn't need to buy the fastest

computer with the most memory, because

the cloud system would take care of those

needs for you. Instead, you could buy an

inexpensive computer terminal. The terminal

could include a monitor, input devices like a

keyboard and mouse and just enough

processing power to run the middleware

necessary to connect to the cloud system.

You wouldn't need a large hard drive

because you'd store all your information on a

remote computer.

Corporations that rely on computers have to

make sure they have the right software in

place to achieve goals. Cloud computing

systems give these organizations company-

wide access to computer applications. The

companies don't have to buy a set of

software or software licenses for every

employee. Instead, the company could pay a

metered fee to a cloud computing company.

Servers and digital storage devices take up

space. Some companies rent physical space

to store servers and databases because they

don't have it available on site. Cloud

computing gives these companies the option

of storing data on someone else's hardware,

removing the need for physical space on the

front end.

Corporations might save money on IT

support. Streamlined hardware would, in

theory, have fewer problems than a network

of heterogeneous machines and operating

systems.

All of these reasons enable the cloud computing

to be the one choice for institutions and companies whose

want to achieve their works in fastest, economic and

efficient way.

2. PARALLEL COMPUTING The computing industry changed course in 2005

when Intel followed the lead of IBM’s Power 4 and Sun

Microsystems’ Niagara processor in announcing that its

high performance microprocessors would henceforth rely

on multiple processors or cores. The new industry

buzzword “multicore” captures the plan of doubling the

number of standard cores per die with every

semiconductor process generation starting with a single

processor. Multicore will obviously help

multiprogrammed workloads, which contain a mix of

independent sequential tasks, but how will individual

tasks become faster? Switching from sequential to

modestly parallel computing will make programming

much more difficult without rewarding this greater effort

with a dramatic improvement in power-performance.

Hence, multicore is unlikely to be the ideal answer [3].

In most parallel algorithms, the basic idea behind

the algorithm is to divide the task into subtasks and use

different processors to execute each subtask [4].

There are several parallel file systems for

example [5]:

GPFS: General Parallel File System for AIX

(IBM)

Lustre: for Linux clusters (Oracle)

mailto:[email protected]

mailto:[email protected]

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PVFS/PVFS2: Parallel Virtual File System

for Linux clusters (Clemson/Argonne/Ohio

State/others)

PanFS: Panasas Active Scale File System for

Linux clusters (Panasas, Inc.)

HP SFS: HP Storage Works Scalable File

Share. Luster based parallel file system

(Global File System for Linux) product from

HP

3. CLOUD COMPUTING Everyone has an opinion on what is cloud

computing. It can be the ability to rent a server or a

thousand servers and run a geophysical modeling

application on the most powerful systems available

anywhere. It can be the ability to rent a virtual server, load

software on it, turn it on and off at will, or clone it ten

times to meet a sudden workload demand. It can be

storing and securing immense amounts of data that is

accessible only by authorized applications and users [6].

Cloud computing has been coined as an umbrella

term to describe a category of sophisticated on-demand

computing services initially offered by commercial

providers, such as Amazon, Google, and Microsoft. It

denotes a model on which a computing infrastructure is

viewed as a “cloud,” from which businesses and

individuals access applications from anywhere in the

world on demand [7].

Many researchers and commercial spheres have

tried to define exactly what "cloud computing" is and

what unique characteristics it presents.

Gartner et al [8] defined Cloud Computing as a style of

computing in which dynamically scalable and often

virtualized resources are provided as a service over the

Internet.

Vaquero et al. [9] have stated “clouds are a large

pool of easily usable and accessible virtualized resources

(such as hardware, development platforms and/or

services). These resources can be dynamically

reconfigured to adjust to a variable load (scale), allowing

also for an optimum resource utilization. This pool of

resources is typically exploited by a pay-per-use model in

which guarantees are offered by the Infrastructure

Provider by means of customized Service Level

Agreements.”

A recent McKinsey and Co. report [10] claims

that “Clouds are hardware-based services offering

compute, network, and storage capacity where: Hardware

management is highly abstracted from the buyer, buyers

incur infrastructure costs as variable OPEX, and

infrastructure capacity is highly elastic.”

4. RELATED WORKS There are many works involve this field, some of

them are listed below:

Eddy Caron, et al. proposed the use of a Cloud

system as a raw computational on-demand resource for a

Grid middleware. They illustrate a proof of concept by

considering the DIET-Solve Grid middleware and the

EUCALYPTUS open-source Cloud platform [11].

Yogesh Simmhan, et al. proposed a Generic

Worker framework to deploy and invoke science

applications in the cloud with minimal user effort and

predictable cost-effective performance. Their framework

addresses three distinct challenges posed by the cloud: the

complexity of application deployment, invocation of cloud

applications from desktop clients, and efficient transparent

data transfers across desktop and the cloud [12].

Manuel R., et al. reported on an evaluation of

open source development tools for Cloud Computing. The

main tools examined are Eucalyptus, Apache Hadoop, and

the Django-Python stack. These tools were used at

different layers in the construction of a notional

application for managing weather data [13].

Sankaran Sivathanu, et al. presented the

measurement results of detailed experiments conducted on

a virtualized setup focusing on the storage I/O

performance. They categorize their experimental

evaluation into four components, each of which presenting

some significant factors that affect storage I/O

performance [14].

Victor Chang, et al. proposed how organizations

can achieve sustainability by adopting appropriate models.

Using the Jericho Forum’s Cloud Cube Model (CCM),

they classify cloud computing business models into eight

types: (1) Service Provider and Service Orientation; (2)

Support and Services Contracts; (3) In-House Private

Clouds; (4) All-In-One Enterprise Cloud; (5) One-Stop

Resources and Services; (6) Government Funding; (7)

Venture Capitals; and (8) Entertainment and Social

Networking[15] .

Kevin D. Foster, et al. described some of the

issues that need to be addressed to enable the application

of cloud computing in such systems, using high-level

generic use cases and requirements to illustrate the issues.

they also discuss how cloud computing can address some

of the perplexing problems that arise in the acquisition of

large-scale weapon systems as systems of systems, but can

also play a role in supporting changes in the workflows

employed by the war fighter to attain information

superiority within the battle space [16].

Luna M. Zhang, Keqin et al. Implemented six

innovative green task scheduling algorithms that have two

main steps: assigning as many tasks as possible to a cloud

server with lowest energy, and setting the same optimal

speed for all tasks assigned to each cloud server [17].

Paul Marshall, et al. proposed a cloud

infrastructure that combines on-demand allocation of

resources with opportunistic provisioning of cycles from

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idle cloud nodes to other processes by deploying backfill

virtual machines (VMs) [18].

Pramod A. Jamkhedkar, et al introduced the

notion and importance of usage management in cloud

computing. It provides an analysis of features and

challenges involved in deploying a usage management

framework over a distributed cloud environment to enable

automated and actionable interpretation, reasoning and

enforcement of usage policies [19].

Christian Baun, et al. (2011) described the design

of a better management solution – the KOALA cloud

management service – for cloud services and its

implementation [20].

The above works introduced the concepts of

cloud computing environment, in our work we suggest a

design of an efficient cloud computing environment that

will be applied at the ministry of higher education and

scientific research in Iraq, to share the information access

and managing of data.

5. THE PROPOSED ENVIRONMENT

Several studies present by many researchers to

establish university cloud such as University of Michigan

launched the CIRRUS Project © (Computing and

Information Resources for Research as a Utility Service)

The mission of the project is to build a foundation for a

vibrant and sustainable university cyber infrastructure.

This study is the first of a series of investigations to

explore issues surrounding cloud adoption on university

campuses [21].

Using cloud computing technology in scientific

research and teaching is so constructive, it provides many

aspects of the solution basis on the problem that uneven

distribution of educational resources in education fields.

Today's high perform and multi-core servers with huge

memory and disk storage capacity, through the use of

virtualization technology (a key component of cloud

computing) can take advantage of these resources to the

university to enhance the level of the teaching and

researching [22].

Today's education need to be innovative and

thrusting to take care of the various distractions and

attractions available for the students. Teaching methods

should include practice, intellectual, and graphics as never

before. This can be available and delivered by forming

university cloud. The university cloud shares the resource

available around the globe digitally [23].

In our environment we have proposed a cloud for

Ministry of Higher Education and Scientific Research

(MHESR) in Iraq. This ministry consists of 24 states

universities, 28 private colleges and 10 Commissions and

Research Centers [24]. The ministry site considered the

main cloud for the other Commissions, college and

universities. In order to illustrate the workflow of MHESR

cloud in detail we coding the universities/colleges into

integer numbers as shown in Table (1), Table (2) and

Table (3).

Table 1: Coding Governmental Universities in MHESR

University Code University Code

University of Baghdad. 1 University of Kufa. 13

University of Mousel. 2 University of Thi-Qar. 14

University of Basrah. 3 University of Tikrit. 15

University of Mustanseriya. 4 University of Babylon. 16

University of Technology. 5 Islamic University. 17

University of Al-Nahrain. 6 University of Al-Muthanna. 18

University of Al-Anbar. 7 University of Mysaan. 19

University of Karbala. 8 University of Sulaimani 20

University of Wassit. 9 Salahaddin University-Hawler 21

University of Deyala 10 University of Duhok 22

University of Al-Qadisiya. 11 Koya University 23

University of Al-Ta'ameem. 12 Hawler Medical University 24

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Table 2: Coding Private Colleges in MHESR

College Code College Code

Herediatary College University. 25 College of Humanity Studies University. 39

Al-Mansur College University. 26 Madianat Al-Ilm College. 40

Al-Rafidin College University. 27 Al-Shaikh Al-Tusi College. 41

Al-Mamun College University. 28 Al- Rsheed University College / Baghdad - 2010 42

Shatt Al-Arab College University. 29 Iraq University College / Basra – 2010 43

Maarif College University. 30 Sader Al- Iraq University College /Baghdad – 2010 44

Al-Hadba College University. 31 Al – Kalam University College / Kirkuk - 2010 45

Badgdad College University. 32 Al- Hussein University College for engineering /

Karbala – 2010

46

Yarmuk College University. 33 Al- Mustakbal University College/ Babil – Hila – 2010 47

Baghdad College Pharmacy. 34 Al- Hikma University College / Baghdad - 2010 48

Ahl-Al-Bait College. 35 Al-Imam University College/ Sallahuddin – balad -

2010

49

Islamic College University. 36 Al- Hila University College/ Babil - 2010 50

Tigris College. 37 Al- Hila University College 51

Shaikh Muhammad Al- Kasanzani College. 38 Al- Fiqih College / Najaf 52

Table 3: Coding the Commissions and Research Centers in MHESR

Commissions and Research Centers Code

Foundation of Technical Education 53

Iraqi Foundation for Computers and Information. 54

Iraqi Foundation for Medical Specializations. 55

Institute of Hereditary 56

Institute for urban and regional 57

Institute of Study of Accountancy and Finance 58

Laser Institute 59

Research Institute of embryo 60

Foundation of Technical Education (Erbil) 61

Foundation of Technical Education (Sulaimani) 62

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Depending on the codes in Table (1) Table (2)

and Table (3).we can construct the cloud structure for the

MHESR as shown in figure (1). Each university has

individual colleges (such as Baghdad University has 24

colleges and Anbar University has 20 colleges and so on)

and each university represents sites for their colleges.

Figure (1) illustrates the number of access which

clearly is huge, where each university contain number of

instructors, employers and students and all of those will

request to access the cloud site, this mean a lot of access to

the MHESR site will be happened may in part of second

and this will cause a big load on the cloud site and effect

on user satisfaction.

To solve a big load problem we suggest a clusters

(servers) solution. Where each server will contain

replicated lectures, documents and applications of the main

cloud (MHESR cloud). The clusters will be deployed

depends on the distance between the universities sites.

Eight clusters are constructed such

16

Cloud Site (Ministry of

Higher Education Site)

1

5

3 8

21

11

4

6

7

2

9 12

10

13

14

15

17

18 19

20

22

23

28

25

26

27

24

29

30

31

31

32

33

34

35

36

37

38

39 40

41

42

43

44

45

46

47

48

49

50

51

52

53 54

55

56

57

58

59

60

61

62

Fig 1: Structure of MHESR universities

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as; the universities at the middle of Iraq will be in cluster

and the universities at the east in cluster and so on, as

shown in figure 2. In this case the load will be controlled

and the ratio of loading has been decreased, but the

loading even now is not solved at all, so we suggest using

one of load balance algorithms built in each cluster to

solve load problem.

6. ARCHITECTED OF THE PROPOSED

APPROACH The proposed approach will be dividing into four

steps see figure (3), each steps will be achieve specific

mission as follow:

Registration Center (RC): in this step the

user(s) will request access to the MHESR

Site; in RC just the authenticated user will be

access. The authenticated users are the

students, employers and instructors whose

have an ID number registered in the database

of MHESR. The users will use this ID in

registration level to get user name and

password to access the cloud. The user(s)

will use the user name and password to log in

the MHESR site.

Load Balance (LB): as the site is for ministry,

there will be huge access from users whose

may want to use applications, lectures,

documents, and other things that must be

available in the ministry site. In order to

control huge access and control load that

could be happen, we suggest using one of

load balance algorithms such as round-robin

algorithm or a biasing algorithm.

Routing Protocol (RP): the routing protocol

will route the user to his request. Routing

protocols are used to find fast and short path

to the user request. We suggest using one of

routing protocol algorithm such IGRP or

EIGRP.

Cloud Site (MHESR Site)

1 5

3

21 11 2

9

16

12 10

13

14

15

18

20

22

23

28

25

26

24

29

30

31

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35

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59

Cluster 4

Cluster 3

Cluster 2

Cluster 5

Cluster 6

Cluster 7

8

19 27

34

44

53

54

60

Cluster 1

4

6

7

17

40 Cluster 8

61

62

Fig 2: Workflow of MHESR Cloud

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Data and Applications Access: in this step the

user will be able access the data and

applications which are located in the nearest

server that he requests it.

7. SYSTEM IMPLEMENTATION MHESR cloud system can be implemented via

the following steps:

Study the overall environment of higher

education and scientific research in Iraq.

Study the overall environment of all existing

universities.

Meeting the involved persons in a discussion

panel.

Cleaning the data to reach the valuable

information.

Dividing the project into phases to be more

adequate for implementation.

Starting the implementation via a single

university.

8. CONCLUSIONS This paper proposed an efficient cloud

environment for ministry of higher education and scientific

research in Iraq. The proposed method depended on

number of access that could happen from universities in

the ministry. The load has been controlled by replicate data

and applications in several servers deployed in middle,

east, west of Iraq. The load also controlled by suggesting

use load balance and routing protocol algorithms. The

propose approach has been presented clearly in workflows.

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and Lindner, “A Break in the Clouds: Towards a

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Server's locations

MHESR Site

User(s)

Access

Registration Center (RC) Register User Name and Password

Confirm User Name and Password

Log in

Load Balance (LB)

Routing Protocol (RP)

Data and Applications

Access

Fig 3: steps of MHESR Cloud

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http://computer.howstuffworks.com/cloud-computing/cloud-computing2.htm

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AUTHORS

1

Muzhir Shaban Al-Ani has received Ph.

D. in Computer & Communication Engineering

Technology, ETSII, Valladolid University, Spain, 1994.

Assistant of Dean at Al-Anbar Technical Institute (1985).

Head of Electrical Department at Al-Anbar Technical

Institute, Iraq (1985-1988), Head of Computer and

Software Engineering Department at Al-Mustansyria

University, Iraq (1997-2001), Dean of Computer Science

(CS) & Information System (IS) faculty at University of

Technology, Iraq (2001-2003). He joined in 15 September

2003 Electrical and Computer Engineering Department,

College of Engineering, Applied Science University,

Amman, Jordan, as Associated Professor. He joined in 15

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September 2005 Management Information System

Department, Amman Arab University, Amman, Jordan, as

Associated Professor, then he joined computer science

department in 15 September 2008 at the same university.

He joined in August 2009 Computer Science Department,

Anbar University, Anbar, Iraq, as Professor.

1Mohammed Salah Ibrahim Al-Obaidi Obtained

B.Sc. (2008), M.Sc. (2011) in field

of Computer Science from the

College of Computer, University of

Anbar. Worked as an administrator

in the Department of calculating in

Al-Safa Co. to oversee the

reconstruction works in Iraq (2007),

and worked with Afaq Co. as

accountant (2010). Now,

Mohammed is Faculty staff member

in Computer Science Department in College of Computer,

University of Anbar. His current interesting field focuses

on Cloud Computing, Wireless Network Management,

Artificial Intelligence and Network Security.

Documents

Efficient Virtual Universities via Cloud Computing Environment