Review on multi-agent system collaboration in learning management system domain by deploying wireless sensor networks for student location detection

Student location detection in Learning Management System (LMS) by utilizing Multi-Agent System (MAS) which contains sensor nodes is a new area of research. This study reviews several studies to ascertain the potential of integrating these two technologies to automate students’ class attendance in Higher Learning Institutions (HLIs). Currently, the HLIs are using paper-based process to record students’ attendance in the class, that is time consuming and is not possible to monitor students all the time, that they suppose to be in learning environment. Introducing the sensor networks and MAS in LMS system is to enable the instructors or lecturers to be aware of the presence of their students once they reach the system’s domain. The collaboration using MAS facilitates the retrieval and recording of students’ details from the sensors and then sends them to LMS servers through Cluster Head Sensor. The information that is collected and recorded by the agents include the signal strength of the students’ device and their profiles which can facilitate to know the exactly locations of the students, by comparing such information with the information already stored in LMS database. Therefore, a system architecture that comprises MAS with sensor networks in LMS is presented in this study for monitoring students’ attendance in the classes and labs. This type of system architecture with improved LMS features is more focused and intended for HLIs that follow the blended learning system. This proposed system has potential of boosting learning process in HLIs by providing new feature in LMS that monitor students’ activities in blended systems, that support classroom and online teachings

Adaptive design model on heterogeneous Learning Management System (LMS) by utilizing Multi-Agent System (MAS)

Content synchronization in LMS(Learning Management System) is a new area of research which involves the transfer of data from one machine to another. Many researchers have conducted their researches concerning synchronization in different applications on data transfer. Therefore, in this paper we introduce a new idea of synchronization in heterogeneous LMSs and to share learning contents among different learning institutions. The major contribution in this paper, is based on the integration of rsync with MAS (Multi-Agent System) in heterogeneous learning management systems (LMSs) environment using SCORM (Sharable Content Object Reference Model), so as different learning in stitutions in higher education (HE)can seamlessly share learning contents in the different LMSs. Hence, a new model of heterogeneous LMS(HLMS)has been presented for easily sharing of learning contents in Higher Learning Institutions (HLI)

Improved rsync algorithm to minimize communication cost using multi-agent systems for synchronization in multi-learning management systems

Remote file synchronization (RFS) is based on updating the outdated version of a file that resides on one machine to be similar to the new version of the updated file in another machine at a minimum computation time (cost). The problem of rsync algorithm synchronization process is that rsync tries to check folders and files one by one, which takes long time to synchronize them. Therefore, the aim of this study is to minimize the computation time during RFS by improving the standard rsync algorithm. Previously, several algorithms and techniques have been proposed for partial file synchronization but many of them were based on controlling the block size, checksums, and delta compression of the matched blocks, to solve the searching problem of the rsync algorithm. This study proposed several techniques to improve rsync (irsync) algorithm in order to reduce computation time during RFS, by encompasses a Multi-Agent system (MAS) framework. This algorithm involves several agents, such as: initiator, sense_agent (SA), log_agent (LA), and search_agent (SeA). These types of agents have different capabilities, actions, and efficiency to the irsync algorithm in file synchronization. The study proposed MAS framework in the Learning Management System (LMS) that involves the transfer of data from one machine to another. To meet this requirement, a new Multi LMS (MLMS) model using Sharable Content Object Reference Model (SCORM) specifications to share learning materials among different higher learning institutions (HLIs) has been presented. This model enhances the interoperability and collaboration of HLIs in terms of synchronization and sharing of learning contents. To evaluate the computation time of the new techniques, standard datasets, which include two versions of source codes emacs-19.28 with emacs-19.29, and gcc-4.8.1 with gcc-4.8.2, were used. The experimental results show that the improved rsync (irsync) algorithm yields a better performance against two previous algorithms, rsync algorithm and hierarchical folder synchronization algorithm (HFSA) in terms of reducing computation time and improve synchronization response time. Therefore, the MAS framework was performed and the reduction of computation time was obtained by 19.86% compared to 42.25% of standard rsync. The results also indicated that reducing the searching time could enhance the irsync algorithm responsiveness time by 32.07% compared to 67.93% of the standard rsync. The integration of the proposed MLMS model with irsync algorithm was further tested through a prototype with MAS and show significant improvement over the cloud synchronization system which based on CDMI technology. These two systems were evaluated in terms of synchronization rate. The results revealed that the MLMS system with irsync (MAS) outperformed the cloud system

Review on ubiquitous education system with multi-agent synchronization on mobile learning application environment

The motivation of this study is based on the use of web based learning system from different institutions to embrace the concept of e-learning and m-learning. Due to the mobility nature of these devices and frequency changing of information in the LMS make the process of updating and adding contents together with managing users become very difficult problem. Sync agent is a improved algorithm which solve the problem faced rsync which is a famous open source software tool which is connected to this problem of updating file between two computers or mobile devices. The sync agent (Multi-agent system) proposed algorithm is based on the use of mobile agents which runs from the host (sender) computer and then migrates to the receiving (receiver) mobile computer to continue the process of updating learning contents before coming back to the sender for completing the process. Sync agent which is Multi-agent system is a promising technique which, we believe that, this approach has a potential of increasing the performance of the network and easy learning process by speed up the update process of the mobile learning contents

Interoperability of multi-agent system in heterogeneous learning management system (HLMS) by deploying wireless sensor networks (WSNS)

User detection in Heterogeneous Learning Management System (HLMS) using sensors which are attached with the Multi-Agent System (MAS) is a new area of research. The integration of sensors with the Multi-Agent system improved the efficiency of LMS by reducing the work load on the LMS servers to the dedicated sensors which are deployed in the domains. In order to explore the potential of sensors and agents, the authors of these papers have integrated these two components so that the efficiency and security of learning management system are realized. In this paper we have introduced the sensors in the web learning system so that the administrators can be aware of the presence of each and every user once connected to the system. The interoperability of Multi-Agent Systems in this learning system is facilitating the retrieval of information from the sensors and sends them to the HLMS servers (Sinks). Furthermore, the information which are gathered and manipulated by the MAS is including measured signal strength of the learning devices and user profile. This information will enable the administrators to know the location of the user in the learning domain and also to notify students on their learning status, based on their profiles which are stored in the database. Hence, a new system model of Multi-Agent System (MAS) with sensor network, in Heterogeneous Learning Management System is presented for improving overall system performance