Simulation-based performance evaluation of queuing for e-learning real time system

S. Badr, F. Bayoumi, G. Darwesh
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引用次数: 4

Abstract

Electronic learning has produced a comfortable, sophisticated, interactive and adaptable teaching model. Moreover, the consistent technical progress in this field allows the development of increasingly interesting applications [1]. We chose to select those elements to create an e-learning environment. This paper presents a model of the multi-tiered e-learning system based on Web Services. It shows architecture for implementing e-learning environment by taking into account quality of service (QoS) requirements namely traffic dropped, traffic received and packet end to end delay. However, there exists no known simulation approach on how to deploy a popular real-time network service such as e-learning system. This paper offers remarkable details on how to model and configure OPNET for such a purpose. The study has been carried out using OPNET IT Guru on 3 scenarios are suggested first before enabling any QoS mechanism at the routers, second apply class based weighted fair queuing using low latency queue (CBWFQ-LLQ) for video traffic and last scenario apply CBWFQ-LLQ for voice. The simulation results show that CBWFQ with LLQ for Voice Traffic has a superior quality than the other techniques. This model was tested with different number of learners. Results indicate that improvements caused by traffic differentiation, become more significant as the number of users increases.
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基于仿真的在线学习实时系统排队性能评价
电子学习产生了一种舒适、复杂、互动和适应性强的教学模式。此外,该领域的持续技术进步允许开发越来越有趣的应用[1]。我们选择了这些元素来创建一个电子学习环境。提出了一种基于Web Services的多层电子学习系统模型。通过考虑服务质量(QoS)要求,即流量丢弃、流量接收和数据包端到端延迟,展示了实现电子学习环境的体系结构。然而,如何部署流行的实时网络服务,如电子学习系统,目前还没有已知的仿真方法。本文提供了关于如何为此目的建模和配置OPNET的重要细节。该研究使用OPNET IT Guru在三种场景下进行,首先在路由器上启用任何QoS机制之前,第二种场景采用基于类的加权公平队列,使用低延迟队列(CBWFQ-LLQ)用于视频流量,最后一种场景采用CBWFQ-LLQ用于语音流量。仿真结果表明,带LLQ的CBWFQ对话音流量的处理质量优于其他技术。用不同数量的学习者对该模型进行了测试。结果表明,随着用户数量的增加,流量分化带来的改善变得更加显著。
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