Enhancing the e-learning system based on a novel tasks’ classification load-balancing algorithm
In the educational field, the system performance, as well as the stakeholders’ satisfaction, are considered a bottleneck in the e-learning system due to the high number of users who are represented in the educational system’s stakeholders including instructors and students. On the other hand, succes...
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PeerJ Inc.
2021-09-01
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| Series: | PeerJ Computer Science |
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| Online Access: | https://peerj.com/articles/cs-669.pdf |
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doaj-95a8df7036f246e9af4d81459e1423bd2021-09-11T15:05:06ZengPeerJ Inc.PeerJ Computer Science2376-59922021-09-017e66910.7717/peerj-cs.669Enhancing the e-learning system based on a novel tasks’ classification load-balancing algorithmAyman E. Khedr0Amira M. Idrees1Rashed Salem2Information Systems Department, Faculty of Computers and Information Technology, Future University in Egypt, Cairo, EgyptInformation Systems Department, Faculty of Computers and Information Technology, Future University in Egypt, Cairo, EgyptInformation Systems Department, Faculty of Computers and Information, Menoufia University, Cairo, EgyptIn the educational field, the system performance, as well as the stakeholders’ satisfaction, are considered a bottleneck in the e-learning system due to the high number of users who are represented in the educational system’s stakeholders including instructors and students. On the other hand, successful resource utilization in cloud systems is one of the key factors for increasing system performance which is strongly related to the ability for the optimal load distribution. In this study, a novel load-balancing algorithm is proposed. The proposed algorithm aims to optimize the educational system’s performance and, consequently, the users’ satisfaction in the educational field represented by the students. The proposed enhancement in the e-learning system has been evaluated by two methods, first, a simulation experiment for confirming the applicability of the proposed algorithm. Then a real-case experiment has been applied to the e-learning system at Helwan University. The results revealed the advantages of the proposed algorithm over other well-known load balancing algorithms. A questionnaire was also developed to measure the users’ satisfaction with the system’s performance. A total of 3,670 thousand out of 5,000 students have responded, and the results have revealed a satisfaction percentage of 95.4% in the e-learning field represented by the students.https://peerj.com/articles/cs-669.pdfCloud computingLoad balancingClassification data miningStudents’ satisfactionE-learning |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Ayman E. Khedr Amira M. Idrees Rashed Salem |
| spellingShingle |
Ayman E. Khedr Amira M. Idrees Rashed Salem Enhancing the e-learning system based on a novel tasks’ classification load-balancing algorithm PeerJ Computer Science Cloud computing Load balancing Classification data mining Students’ satisfaction E-learning |
| author_facet |
Ayman E. Khedr Amira M. Idrees Rashed Salem |
| author_sort |
Ayman E. Khedr |
| title |
Enhancing the e-learning system based on a novel tasks’ classification load-balancing algorithm |
| title_short |
Enhancing the e-learning system based on a novel tasks’ classification load-balancing algorithm |
| title_full |
Enhancing the e-learning system based on a novel tasks’ classification load-balancing algorithm |
| title_fullStr |
Enhancing the e-learning system based on a novel tasks’ classification load-balancing algorithm |
| title_full_unstemmed |
Enhancing the e-learning system based on a novel tasks’ classification load-balancing algorithm |
| title_sort |
enhancing the e-learning system based on a novel tasks’ classification load-balancing algorithm |
| publisher |
PeerJ Inc. |
| series |
PeerJ Computer Science |
| issn |
2376-5992 |
| publishDate |
2021-09-01 |
| description |
In the educational field, the system performance, as well as the stakeholders’ satisfaction, are considered a bottleneck in the e-learning system due to the high number of users who are represented in the educational system’s stakeholders including instructors and students. On the other hand, successful resource utilization in cloud systems is one of the key factors for increasing system performance which is strongly related to the ability for the optimal load distribution. In this study, a novel load-balancing algorithm is proposed. The proposed algorithm aims to optimize the educational system’s performance and, consequently, the users’ satisfaction in the educational field represented by the students. The proposed enhancement in the e-learning system has been evaluated by two methods, first, a simulation experiment for confirming the applicability of the proposed algorithm. Then a real-case experiment has been applied to the e-learning system at Helwan University. The results revealed the advantages of the proposed algorithm over other well-known load balancing algorithms. A questionnaire was also developed to measure the users’ satisfaction with the system’s performance. A total of 3,670 thousand out of 5,000 students have responded, and the results have revealed a satisfaction percentage of 95.4% in the e-learning field represented by the students. |
| topic |
Cloud computing Load balancing Classification data mining Students’ satisfaction E-learning |
| url |
https://peerj.com/articles/cs-669.pdf |
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AT aymanekhedr enhancingtheelearningsystembasedonanoveltasksclassificationloadbalancingalgorithm AT amiramidrees enhancingtheelearningsystembasedonanoveltasksclassificationloadbalancingalgorithm AT rashedsalem enhancingtheelearningsystembasedonanoveltasksclassificationloadbalancingalgorithm |
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