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

Efficient Virtual Universities via Cloud Computing Environment 1

Muzhir Shaban Al-Ani, 2 Mohammed Salah Ibrahim 1, 2

1

Anbar University, College of Computer, Iraq [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.

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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.

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Why would anyone want to rely on another computer system to run programs and store data? Here are just a few reasons [2]: 

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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 companywide 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)

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

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http://www.cisjournal.org

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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Journal of Emerging Trends in Computing and Information Sciences ©2009-2012 CIS Journal. All rights reserved. http://www.cisjournal.org

idle cloud nodes to other processes by deploying backfill virtual machines (VMs) [18].

explore issues surrounding cloud adoption on university campuses [21].

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].

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].

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

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. University of Basrah. University of Mustanseriya. University of Technology. University of Al-Nahrain. University of Al-Anbar. University of Karbala. University of Wassit. University of Deyala University of Al-Qadisiya. University of Al-Ta'ameem.

2 3 4 5 6 7 8 9 10 11 12

University of Thi-Qar. University of Tikrit. University of Babylon. Islamic University. University of Al-Muthanna. University of Mysaan. University of Sulaimani Salahaddin University-Hawler University of Duhok Koya University Hawler Medical University

14 15 16 17 18 19 20 21 22 23 24

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Journal of Emerging Trends in Computing and Information Sciences ©2009-2012 CIS Journal. All rights reserved. http://www.cisjournal.org

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. Al-Rafidin College University. Al-Mamun College University. Shatt Al-Arab College University. Maarif College University. Al-Hadba College University. Badgdad College University.

26 27 28 29 30 31 32

40 41 42 43 44 45 46

Yarmuk College University. Baghdad College Pharmacy. Ahl-Al-Bait College.

33 34 35

Islamic College University. Tigris College. Shaikh Muhammad Al- Kasanzani College.

36 37 38

Madianat Al-Ilm College. Al-Shaikh Al-Tusi College. Al- Rsheed University College / Baghdad - 2010 Iraq University College / Basra – 2010 Sader Al- Iraq University College /Baghdad – 2010 Al – Kalam University College / Kirkuk - 2010 Al- Hussein University College for engineering / Karbala – 2010 Al- Mustakbal University College/ Babil – Hila – 2010 Al- Hikma University College / Baghdad - 2010 Al-Imam University College/ Sallahuddin – balad 2010 Al- Hila University College/ Babil - 2010 Al- Hila University College Al- Fiqih College / Najaf

47 48 49 50 51 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. Iraqi Foundation for Medical Specializations. Institute of Hereditary Institute for urban and regional Institute of Study of Accountancy and Finance Laser Institute Research Institute of embryo Foundation of Technical Education (Erbil) Foundation of Technical Education (Sulaimani)

54 55 56 57 58 59 60 61 62

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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.

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.

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

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

19

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24

45 23 29 28

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22

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20

21 56

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52

42

Cloud Site (Ministry of Higher Education Site)

33

43 49

25

6

50

11 62

58

37

32 17

16 13 12

9

35

7

36

59

14 39

48 57

31

40 31

2

10 41 15

47

51

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 19

27

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

18

34

54

38

Cluster 2

Cluster 1 53

60

29

44

8

30

61

23

26

7

Cluster 8

55

16

6 40

4 62

24

1 33

17

5

46

49 28

Cluster 5

Cluster 4

13

Cloud Site (MHESR Site) 22

58

37

45

52

50

51

48

41

2

35

56

47

9

43

Cluster 3

12

10

Cluster 6

36

25

32

21

11

59

57

3

20

14

Cluster 7

39

31

15

31

42

Fig 2: Workflow of MHESR Cloud 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.

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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

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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.

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Journal of Emerging Trends in Computing and Information Sciences ©2009-2012 CIS Journal. All rights reserved. http://www.cisjournal.org

MHESR Site User(s) Access

Register User Name and Password

Registration Center (RC)

Confirm User Name and Password Log in

Load Balance (LB)

Routing Protocol (RP)

Data and Applications Server's locations Access

Fig 3: steps of MHESR Cloud 

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

use load balance and routing protocol algorithms. The propose approach has been presented clearly in workflows.

REFERENCES [11]

L. M. Vaquero, L. Rodero-Merino, J. Caceres, M. and Lindner, “A Break in the Clouds: Towards a Cloud Definition”, SIGCOMM Computer Communication Review, vol. 39, no. 1, 2008.

[12]

Jonathan Strickland, “How Cloud Computing Works”. http://computer.howstuffworks.com/cloudcomputing/cloud-computing2.htm

[3]

Asanovic, Bodik et al, “The Landscape of Parallel Computing Research: A View from Berkeley”, Technical Report No. UCB/EECS-2006-183, 2006. http://www.eecs.berkeley.edu/Pubs/TechRpts/2006/ EECS-2006-183.pdf

[4]

R.Nedunchelian, K.Koushik, N.Meiyappan, V.Raghu, “Dynamic Task Scheduling Using Parallel Genetic Algorithms for Heterogeneous Distributed Computing”, 2004. http://ww1.ucmss.com/books/LFS/CSREA2006/GC A4489.pdf

[5]

Blaise Barney. ʺAn Introduction to Parallel Computingʺ. Lawrence Livermore National Labs. https://computing.llnl.gov/tutorials/parallel_comp/

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

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Journal of Emerging Trends in Computing and Information Sciences ©2009-2012 CIS Journal. All rights reserved. http://www.cisjournal.org

[6]

White Paper, “Introduction to Cloud Computing Architecture”, Sun Microsystems, Inc. 1st Edition, June 2009

[7]

R. Buyya, C. S. Yeo, S. Venugopal, J. Broberg and I. Brandic, Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility, Future Generation Computer Systems, 25:599_616, 2009.

[8]

Gartner. “Gartner Says Cloud Computing Will be As Influential As E-business”. http://www.gartner.com. June 26, 2008.

[9]

on Heterogeneous Cloud Servers”, IEEE/ACM International Conference on Green Computing and Communications, 2010. [18]

Paul Marshall, Kate Keahey and Tim Freeman, “Improving Utilization of Infrastructure Clouds”, 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, 2011.

[19]

Pramod A. Jamkhedkar, Christopher C. Lamb and Gregory L. Heileman, “Usage Management in Cloud Computing”, IEEE 4th International Conference on Cloud Computing, 2011.

L. M. Vaquero, L. Rodero-Merino, J. Caceres and M. Lindner, A break in the clouds: Towards a cloud definition, SIGCOMM Computer Communications Review, 39:50_55, 2009.

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Christian Baun, Marcel Kunze and Viktor Mauch, “The KOALA Cloud Manager Cloud Service Management the Easy Way”, IEEE 4th International Conference on Cloud Computing, 2011.

[10]

McKinsey & Co., Clearing the Air on Cloud Computing, Technical Report, 2009.

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[11]

Eddy Caron, Frederic Desprez and David Loureiro, “Cloud Computing Resource Management through a Grid Middleware: A Case Study with DIET and Eucalyptus”, IEEE International Conference on Cloud Computing, 2009.

Traci L. Ruthkoski, “Exploratory Project: State of the Cloud, from University of Michigan and Beyond”, 2nd IEEE International Conference on Cloud Computing Technology and Science, 2010

[22]

Yogesh Simmhan, Catharine van Ingen, Girish Subramanian and Jie Li , “Bridging the Gap between Desktop and the Cloud for eScience Applications”, IEEE 3rd International Conference on Cloud Computing, 2010.

GaiZhen YANG and Zemin ZHU, “The Application of Saas-based Cloud Computing in the University Research and Teaching Platform”, International Conference on Intelligence Science and Information Engineering, 2011

[23]

Padma Veni and Robert Masillamani, “Resource Sharing Cloud for Unversityclusters”, IEEE/ACM International Conference on Green Computing and Communications & IEEE/ACM International Conference on Cyber, Physical and Social Computing, 2010

[24]

Mistery of Higher Education Reseasch, official http://www.en.mohesr.gov.iq/

[12]

[13]

[14]

Manuel Rodriguez-Martinez, Jaime Seguel and Melvin Greer , “Open Source Cloud Computing Tools: A Case Study with a Weather Application”, IEEE 3rd International Conference on Cloud Computing, 2010. Sankaran Sivathanu, Ling Liu, Mei Yiduo and Xing Pu, “Storage Management in Virtualized Cloud Environment”, IEEE 3rd International Conference on Cloud Computing, 2010.

and

Scientifc Site:

AUTHORS 1

[15]

Victor Chang and Gary Wills, David De Roure, “A Review of Cloud Business Models and Sustainability”, 2010 IEEE 3rd International Conference on Cloud Computing, 2010.

[16]

Kevin D. Foster, John J. Shea, James Bret Michael and Thomas W. Otani, “Cloud Computing for Large-Scale Weapon Systems, IEEE International Conference on Granular Computing”, 2010.

[17]

Luna Mingyi Zhang and Keqin Li , “Green Task Scheduling Algorithms with Speeds Optimization

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.

Mohammed 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.

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