Challenges of Infrastructure in Cloud Computing for Education

Field: A Systemmatic Literature Review

Nurma Ayu Wigati, Ari Wibisono and Achmad Nizar Hidayanto

Faculty of Computer Science, Universitas Indonesia, Depok, Indonesia

Keywords: Cloud Computing, Eductional Sector, Infrastructure as a Service (IaaS), Resource, Security, Finance,

Kitchenham, Challenges.

Abstract: The usage of cloud computing is needed for educational sector, especially in universities to ease all of

administration and learning access to everyone. So that, the development infrastructure cloud computing need

to concern the aim of the university. Infrastructure as a Service (IaaS) in cloud computing has problems, like

resource, security, and finance. This study follows Kitchenham protocol to explore the challenges in the cloud

computing as a infrastructure service for education field literature systematically, then reviewed their

techniques which can use to all of university in Indonesia. This study recommends that the management of

IaaS should be considered well to get result development of cloud computing optimally.

1 INTRODUCTION

Cloud computing is defined as a services that together

provide ways to deliver cloud services. In higher

education, cloud computing services are commonly

used to provide the means for students to collaborate

and interact in a distributed learning space (Al-

Samarraie & Saeed, 2018). Cloud computing

technology is one of the services provided by the use

of IT in it to facilitate human work in various fields

to be more efficient and effective, such as in

education (Njenga, Garg, Bhardwaj, Prakash, &

Bawa, 2019). Universities and colleges usually do not

have sufficient fund to install and continuously

maintain state-of-the-art ICT technologies for

learning environment that can support students, staff,

researchers and developer (Elamir, Jailani, & Bakar,

2013). Thus, cloud computing and its applications are

vital to the future of distance education worldwide.

The rate at which ICT technologies change, will

continue to place pressure on institutions’ budget.

Increasing bandwidth availability has enable cloud

computing to be a potential solution in reducing ICT

cost and freeing them from the expense and hassle of

hardware and software maintenance. Several

universities in UK have adopted Google Apps due to

cost and unreliable in-house email systems. Even

universities and schools in poor countries in Africa

are using cloud computing supported by Google and

Microsoft.

Based on the conditions and problems that have

been described, the output of study is expected to

identify and map the right solutions to be carried out

when implementing cloud computing infrastructure

in educational sector. To answer the expected

research objectives, our work is organized as follows:

Section 1 shows why we choose to raise the issue of

the challenges faced in cloud computing

infrastructure as a service, Section 2’s regarding the

theoretical basis of cloud computing infrastructure as

a service (IaaS) and its chalenges. Section 3 is about

research methodology which tells the workmanship

of the research on how the research was conducted.

Section 4’s regarding the results and analysis that

shows the results of research that has been done and

how the analysis of the outputs on these results. In

Section 5, the authors provide conclusions from this

literature study.

2 RELATED WORKS

Cloud computing (CC) also presents new security

challenges (A. M. Ibrahim & Hemayed, 2019). In

education field, we have some problems about cloud

computing. Education institutions will continue to

enhance infrastructure and curriculum to attract

Wigati, N., Wibisono, A. and Hidayanto, A.

Challenges of Infrastructure in Cloud Computing for Education Field: A Systemmatic Literature Review.

DOI: 10.5220/0010522603510358

In Proceedings of the 23rd International Conference on Enterprise Information Systems (ICEIS 2021) - Volume 1, pages 351-358

ISBN: 978-989-758-509-8

351

students (Sun, 2020). Scholars and researchers have

done lots of studies concern the cloud computing

adoption model and proposed a suitable way for

different categories of cloud computing such as

layout, implementing, challenges and so many.

Students, staff and lecturers in the studied area suffer

enough due to the problem of data storage for their

academic purposes (Juma & Tjahyanto, 2019).

Unfortunately, these methods require the suspension

of the cloud computing applications due to the

mandatory shutdown of the associated virtual

machines (Lin, Wang, Liang, & Qi, 2011).

3 METHODOLOGY

The need for cloud computing infrastucture as a

service is needed to support the profits to be obtained

by university (Lis & Paula, 2015). This study needs

to map the problems arising from cloud computing

infrastructure as a service (IaaS) implementation over

the past 5 years using Kitchenham’s SLR and are

expected to be grouped in a more structured way in

Figure 1 (Suryono, Purwandari, & Budi, 2019).

Figure 1: Methodology by Kitchenham.

3.1 Identification Requirement and

Organization of Review Protocol

It is categotized as the planning stage to search for

keywords of the problems, the research questions to

be submitted in this study is “What are the challenges

that have been proposed in the paper article that is

reviewed in the implementation infrastructure using

cloud computing in the education field?”

Meanwhile, the Review Protocol is used to map

keywords such as what will be used and not used in

the SLR that is done and this looks like in table 1.

Table 1: Research Question Structure.

Review Protocol Scope

Population cloud computing, education

filed

Intervention challenges, implication,

infrastructure

Comparison n/a

Outcome challenges of infrastructure

in cloud computing

3.2 Selection Database

The selection process can be shown in table 2. The

inclusion criteria are should be relevant with the

search keywords, written in English, published in

2015 – 2020, include all of education domain, contain

the impact or challenge of cloud computing, and

accesible. The exclusion criteria are articles that have

no relevance with the search keyword, not include

education domain, not contain the cloud computing

topics, not accessible, duplicate articles, and review

articles.

Table 2: Database Result.

Database

Initiation

Stage

1st Stage 2nd Stage

ACM

Digital

Library

915 120 14

Emerald

Insight

43 23 4

IEEE

Xplore

36 7 2

Science

Direct

83 55 10

Scopus 773 145 23

3.3 Measurement of Paper Quality

This paper quality test measurement is used to select

the final paper used as an analysis, this can be seen in

table 3.

Plannin

lementation

ort

1. Synthesis Data

1. Selection Database

2. Measurement of Paper Quality

3. Extraction Data

1. Identification Requirement of Systemmatic

Literatur Review (SLR)

2. Or

anization of Review Protocol

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352

Table 3: Article Quality Assessment Checklist.

Checklist Checklist Question

Does the article describe the objectives of

the research clearly?

Does the article provide literature review,

background, and context of the research?

Does the article show related works from

previous studies in order to highlight the

main contributions of the research?

Does the article explain the architecture of

the idea or method used?

C5 Does the article deliver results?

Does the article produce relevant

conclusion with the objective of the

research?

Does the article recommend future work or

improvement?

C8 Indexes (Q1/Q2/Q3/Q4/conf)

3.4 Extraction Data & Synthesis Data

Result of extraction data with summary and analysis

with implication or impact, challenges, and solution.

4 RESULTS & DISCUSSION

We reviewed the paper and determined the database

that we used, then qualified it. Table 4 showed the

resource and database we reviewed in the 2nd stage,

but we could not use them. The quality of articles

result with did not have 4.5 scores can be seen in table

5. For that purpose, an 8-item checklist on a five-point

scale:” not at all” (0), “very little” (0.25), “a little”

(0.5), “yes, but not adequate enough” (0.75), and

“adequately” (1). Therefore, the possible range of

scores is 0–8. We choose to include articles that

scored more than 4.5 for further analysis in Figure 2.

Table 4: Database and Paper Resource.

Database Resource Paper

Scopus (Peniak, Franekova, & Zolotova, 2016)

Scopus (X. He & Tian, 2017)

Scopus (Yong, Zhang, Chen, & Zhou, 2017)

Table 5: Article Quality Assesment Result.

Source 1 2 3 4 5 6 7 8 Total

(Peniak

et al.,

2016)

1 1 0 0 0 0,25 0,5 1 3,75

(X. He

& Tian,

2017)

1 1 0,5 0,5 0,25 0 0 1 4,25

(Yong

et al.,

2017)

1 1 0,25 0 0,25 0 0,25 1 3,75

We got total all of the documents with

Kitchenham methodology were 1850 for initiation

stage, 350 for 1st stage, and 53 for 2nd stage. This

final stage, we used as an analysis. There are 3

literatures which do not fulfill the requirements. The

techniques used in IaaS are convolutional neural

networks, genetic algorithms, SDN approaches,

LSTM-RNN networks, deep neural networks, cloud

e-learning for technology (CLEM), GPU accelerated

algorithm, CMBA, and SVM approach.

Figure 2: Requirement by Keyword.

After that, we collected the article which we done

with synthesis that development of infrastructure in

cloud computing as a service still has problems, such

as security can not accomodate maximal yet (no

backup), amount of the data used is greater, of course

server development increase by complex, and the cost

is expensive when using complex data because it

requires a lot of space.

Cloud computing has delivered services

efficiently (Ashouraie & Jafari Navimipour, 2015),

(Rao, Ma, & He, 2018), (Singh & Chen, 2019),

(Jayanetti & Buyya, 2019). Data centers application

(“challenges” or “issue”) and (“education” or

“university”) and (“cloud computing”) and

(“solution”) and (“infrastructure as a service”)

and (“storage” or “data center” or “network”)

Challenges of Infrastructure in Cloud Computing for Education Field: A Systemmatic Literature Review

353

play important role to support network diverse to

array of requirements from latency-sensitive

application such as web servers with a distributed

data processing and virtual machine live-migration

(Sharma, Javadi, Si, & Sun, 2017), (Chaufournier,

Ali-Eldin, Sharma, Shenoy, & Towsley, 2019). One

of algorithm such as PLBA and SVM algorithm can

be implemented (Hamza, Abderaouf, Abdelhak, &

Okba, 2017), (Gao & Yu, 2017). Another algorithm

like GPU for allocating virtual infrastructure in cloud

data centers can be handle large data center (Nesi,

Pillon, de Assunção, & Koslovski, 2018). The

technology of cloud computing virtualization

provides efficient resources for end users (Metwally,

Jarray, & Karmouch, 2015). The characteristics of

cloud computing include manageability, scalability

and availability (Jun, Jie, & DingHong, 2019),

(Allison, Turner, & Allen, 2015). Cloud computing

mainly provides three service delivery models and

one of the type’s IaaS (Shaik & Baskiyar, 2018).

There are several problems to be considered while

managing resources, such as, type of resource

required (physical/logical), allocation, brokering,

provisioning, mapping, adaptation and estimation

(Diouani & Medromi, 2019), (Alqahtany, Clarke,

Furnell, & Reich, 2016), (J. He & Zhang, 2017),

(Manvi & Krishna Shyam, 2014). Virtual machine

introspection (VMI) is a technique whereby an

observer can interact with a virtual machine client

from the outside through the hypervisor (Dykstra &

Sherman, 2012).

Capabilities complexity can be handled by the

traffic scheduling detection to fix the problem

(Yazidi, Abdi, & Feng, 2018). Many resources need

to build the architecture the cloud computing data

servers (Ataie et al., 2019). So, we can minimalized

the financial by concerned with acquiring broadband

connectivity to the cloud (Atiewi, Abuhussein, &

Saleh, 2018). The efficiency allocation cloud

computing also offers the usage of CPU core,

memory, and disk storage based on cloud providers

(Alshamrani, 2018). On the e-learning development,

the role of cloud computing about availability,

reliability, cost, flexibility, ease of use, and waiting

time must be considered (Yuvaraj, 2016). Because it

has the high influence and significant to teachers and

students who use it (Rajabion, Wakil, Badfar, Nazif,

& Ehsani, 2019).

Low cost computing can be integrated with web

services to optimum the cost (Yuvaraj, 2015). Private

cloud design still need (Makori, 2016), (E. A. Ahmed

& Ahmed, 2019). Configuration and availability can

be build by combination deep neural network (Chiba,

Abghour, Moussaid, omri], & Rida, 2019). There are

potential benefits of adopting cloud computing

technology in higher education institutions

(Tashkandi & Al-Jabri, 2015), (F. F. Ahmed, 2015),

such as Google Docs (Amron, Ibrahim, & Chuprat,

2017), (Farzai, Shirvani, & Rabbani, 2020) and

consultation services in addition to the cloud

solutions offered to higher education institutions

(Shorfuzzaman, Alelaiwi, Masud, Hassan, &

Hossain, 2015). Collaboration solutions,

infrastructure computing or virtual desktops solutions

(Couto et al., 2018) offers a shift from computing as

a product that is owned to as a service that is delivered

from large-scale data centers or clouds (Kumar,

Goomer, & Singh, 2018).

Cloud computing technology has revolutionized

to make the cost become effective and resource

efficient (Kertesz, Dombi, & Benyi, 2016), (Njenga

et al., 2019). The deployment of a data-intensive

application to a cloud poses a number of serious

challenges, mainly concerning the provider and

resources selection process, based on the Quality of

Service expected, as well as the management of the

Virtual Machines in the provider premises (Psychas

et al., 2020) and Control system can use by

mechatronics (Chao et al., 2015), (Cerroni et al.,

2015). Component failures within the cloud

infrastructure are common, but large cloud data

centres should be designed to guarantee a certain

level of availability to the business system (Cheng,

Cao, Yu, & Ma, 2017).

Cloud systems have a high failure rate because

they have many servers, which are geographically

dispersed and have a large workload (Patel, Patel, &

Patel, 2016). In order to ensure that cloud users can

use the service, the cloud infrastructure should be

designed so that their system downtime is minimal or

irrelevant. The latest advances in machine learning

and cloud storage provide an excellent opportunity to

take advantage of the large amounts of data generated

from cloud infrastructure, which provides room for

predicting when components may fail or fail (Peng &

Ho, 2018). Currently, mathematical and statistical

modelling are the prominent approaches used for

failure predictions, these are based on equipment

degradation, physical models and machine learning

techniques respectively (Mollajafari & Shahhoseini,

2016), (Mohammed et al., 2018), (Xu, Chen, &

Alcaraz Calero, 2017), (Chawki, Ahmed, & Zakariae,

2018).

To ensure the security of business-sensitive data

and information, organizations must understand the

type of cloud used (Vogel, Griebler, Maron, Schepke,

& Fernandes, 2016). In terms of data storage and

access security (Jain, Tyagi, & Kalra, 2016), (Rahouti

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354

& Xiong, 2019) or cloudStack (Abdulhamid, Abd

Latiff, Abdul-Salaam, & Madni, 2016). Regarding

optimization and cost minimization, we can also build

smartphones to release SDKs for Apple iOS or

Android (Ilyas, Khan, Saleem, & Alowibdi, 2019).

On a comprehensive basis, current technological

advancements play a key role in the development of

formal education by providing a variety of learning

delivery and communication modes that can meet the

needs of continuing education at low cost. Ultimately,

the issue of interest to decision makers is how to use

modern technology to attract distance learners to

participate in collaborative learning courses. In

addition, given the continuing need for universities to

build capacity to take advantage of technological and

teaching advances in the formal education sector.

Information security in the cloud is based on the

fact that no one can access client information from the

cloud, so they will not be able to understand the

essence of the information. These lines ensure

information security, which is the most important

prerequisite for cloud clients, and can actually avoid

hardware costs, and there is little understanding of

configuration software. When using cloud computing

in the education sector, transparency and audit control

are still not working optimally, so we need a system

that can use innovative technologies to read business

performance requirements.

5 CONCLUSION

The aim of this work was to present a comprehensive

overview of cloud computing implementation

research in the education field. A systemmatic review

has been conducted which included planning,

implementation, and reporting phases. Various

technique of cloud computing infrastructure as a

service implementation in education field have been

identified from 53 selected literatures. In this study

also identified the challenges, such as security, data

server complexity, and financial problems in

educational sector.

To take on these challenges, there are several

solutions are proposed, such as the selection of the

best technology approach for effective and efficient

use, regular and routine checks and backups, and

infrastructure management to manage as effectively

and efficiently as possible as needed. So that, the

costs incurred will be optimal.

However, the author only about technical aspects

such as security, complexity, or financial.

Meanwhile, non-technical aspects also need to be

considered (eg human factors). Development can

continue when people can have a lot of professional

experience for cloud computing adoption maximal.

So, the next study deeply discusses user interest and

user research on cloud computing issues.

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