JoWUA

Abstract

The paper researches the aspects of e-learning systems optimization through cross-layer design methods to enhance performance in mobile and ubiquitous computing environments. Unstable network conditions, such as high latency, low bandwidth, and network congestion, are a big challenge to e-learning systems. The overall goal of the present research is to improve the smooth transmission of the content through the optimization of the communication between various levels of the network stack. To measure the efficiency of cross-layer optimization, a series of experiments was done with the main performance metrics like latency, throughput, packet loss, video buffering, and interactive delay being evaluated. The findings indicate that there is a 40% decrease in latency, 30% throughput increase, 62.5% packet loss decrease, and a 50% video buffering decrease. Moreover, the analysis indicates that user interactions have been improved in real time, whereby the interactive delay has been reduced by half. These results show that cross-layer design may be a powerful tool that further improves the work of an e-learning system, making it more robust and effective in different network conditions. The research has implicated the practicality of the study that educators and designers can use to provide a quality learning experience, even in cases where there are limited resources. Future research will involve the development of machine learning models to adapt the network in real-time and research the capability of the system to scale to large-scale, multi-user e-learning settings.