基于进化算法的移动自组网DSDV和OLSR在线学习诱导模式优化

Fauzan Prasetyo, M. N. Arifin, A. Irmawan
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引用次数: 1

摘要

基于理论和实践的e-learning归纳模型是响应教育技术动态发展的有效途径。在城市地区和组织中必须考虑和解决的共同问题是移动自组网(MANET)中的高效消息传递。为了获得良好、高效的通信,算法必须考虑到邻近节点的密度、网络的形状和大小、信道的优先级和消息的使用等几个方面。以前的一些研究试图提出传递消息的解决方案,但找到将被使用的最佳问题解决方案非常困难。在我们的研究中,我们建议使用EA对MANET进行优化。该算法将为向MANET发送消息的问题提供几种解决方案。我们的目标是能够确定网络中每个节点的最佳通信策略。通过在(n-2)网络模拟器中使用(EA)进化算法,我们发现结果有望用于系统电子学习模型网络的消息传递优化。关键词:MANET,进化算法,消息传递优化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization of Mobile Ad Hoc Network DSDV and OLSR Using Evolutionary Algorithm for Elearning induction mode
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.
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