A Performance Evaluation of a Multi-Agent Mobile Learning System

Abstract

Mobile devices have emerged as our daily companion whose applicability evolves as the day unfolds. One of such applications is in the area of learning, called mobile learning (M-learning). However, as with all new technologies, M-learning is faced with the issues of standard, content packing, and deployment. And like other distributed applications on ubiquitous networks, M-learning is challenged with performance issues. This work shows the implementation and evaluation of a model for intelligent mobile learning system (IMLS) using a multi-agent system (MAS), such as the Java Agent Development Environment (JADE) framework. Two M-learning applications (agent-based and non-agent) were developed, deployed and tested. The agent-based application is deployed using an HTTP-based Message Transfer Protocol (MTP). The results suggest that agents can increase the performance of an M-learning application up to eight times.