Evaluation of an IoT-based e-learning testbed: Performance of OLSR protocol in a NLoS environment and mean-shift clustering approach considering electroencephalogram data

Abstract

Purpose

This paper aims to present the design and implementation of an Internet of Things (IoT)-based e-learning testbed using Raspberry Pi mounted on Raspbian operating system (OS).

Design/methodology/approach

The testbed is composed of five Raspberry Pi B+ computers. The experiments are carried out in the department floor considering an non line of sight (NLoS) environment. Single constant bit rate (CBR) flows were transmitted over user datagram protocol (UDP), and data were collected for five metrics: throughput, packet delivery ratio (PDR), hop count, delay and jitter using the Iperf.

Findings

The implemented testbed was evaluated using experiments. The experimental results showed that the nodes in the testbed were communicating smoothly, and by using attention value, the learner concentration is increased.

Research limitations/implications

The performance of the Optimized Link State Routing (OLSR) protocol was analyzed in a floor environment considering the NLoS scenario. However, this testbed can be implemented to other protocols also.

Originality/value

Because of the opportunities provided by the internet, people are taking advantage of e-learning courses, and enormous research efforts have been dedicated to the development of e-learning systems. To date, many e-learning systems are proposed and used practically. However, in these systems, the e-learning completion rate is low. To deal with this problem, an IoT-based e-learning system was implemented to increase the e-learning completion ratio by increasing the learner concentration.

Citation

Yamada, M., Cuka, M., Liu, Y., Oda, T., Matsuo, K. and Barolli, L. (2017), "Evaluation of an IoT-based e-learning testbed: Performance of OLSR protocol in a NLoS environment and mean-shift clustering approach considering electroencephalogram data", International Journal of Web Information Systems, Vol. 13 No. 1, pp. 2-13. https://doi.org/10.1108/IJWIS-12-2016-0072