Open AccessOptimization of Mobile Ad Hoc Network DSDV and OLSR Using Evolutionary Algorithm for Elearning induction mode
Author(s) -
Fauzan Prasetyo,
Moh. Nazir Arifin,
Agus Irmawan
Publication year - 2020
Publication title -
journal of disruptive learning innovation
Language(s) - English
Resource type - Journals
eISSN - 2774-8715
pISSN - 2721-4486
DOI - 10.17977/um072v2i12020p1-8
Subject(s) - mobile ad hoc network , computer science , node (physics) , wireless ad hoc network , dynamism , optimized link state routing protocol , computer network , distributed computing , evolutionary algorithm , mode (computer interface) , routing (electronic design automation) , artificial intelligence , routing protocol , network packet , engineering , wireless , human–computer interaction , telecommunications , physics , structural engineering , quantum mechanics
The e-learning induction model that is well informed by the theory and practice is a sure way of being responsive to the dynamism of educational technologies. Common problem that must be taken as consideration and must be resolved in urban areas and the organization is an efficient message delivery in (MANET) Mobile Ad hoc Network. To get good and efficient communication, an algorithm must pay attention to several aspects such as the density of neighbouring node, shape and network size, channel priority level and used of message. Some previous studies attempted to propose solutions for delivering messages, but finding the optimal problem solution that will be use is very difficult. In our research, we sugested an optimization on MANET by using an EA. The algorithm will provide several solutions to the problem of sending messages to MANET. Our goal is able to determine the optimal communication strategy for each node in network. By using (EA) evolutionary algorithm in (n-2) network simulator, we found that result is promising for message delivery optimization to destination for using in system Elearning model networkKeywords: MANET, evolutionary algorithm, message delivery optimization.