Enhancing the e-learning system based on a novel tasks' classification load-balancing algorithm.

Ayman E. Khedr,Amira M. Idrees,Rashed Salem

doi:10.7717/peerj-cs.669

Ayman E. Khedr, Amira M. Idrees + Show 1 more

Open Access

https://doi.org/10.7717/peerj-cs.669

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Abstract

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.

Highlights

E-learning is a term that refers to adapting the information technology tools as well as communication methods in the education sector
The proposed approach is discussed in detail in “E-Learning Based on Task Classification Load Balancing Algorithm” while the evaluation measures are discussed in “Evaluation Measures Applied in the Case Studies”
As discussed in “Background”, different parameters can be considered for evaluating the proposed algorithm. These parameters are presented in different research such as in Milani & Navimipour (2016) and Khedr, Idrees & Elseddawy (2016b) which include the following: “Algorithm nature, performance, flexibility, implementation, resource utilization, communication overhead, stability, adaptability, response time, reliability, complexity, and cost”

Summary

Introduction

E-learning is a term that refers to adapting the information technology tools as well as communication methods in the education sector. The local level provides the learning activities for a single course or group of courses Investing in both levels is essential for ensuring the continuous development in the educational sector which provides continuous development in the whole economy as discussed in. The algorithms that follow the static approach apply the round-robin algorithm, which is a simple technique with low resource utilization This algorithm does not guarantee equity in the load distribution as the current status of the servers is not considered (Chen, Chen & Kuo, 2016). One of the considerations of dynamic algorithms is complexity This was not highlighted by many researchers due to other benefits such as the high performance and accuracy in the load distribution for the system’s nodes (Kanakala, Reddy & Karthik, 2015). The high cost and eliminated considerations of different vital factors were noticed

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