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Congestion Prediction Modeling for Quality of Service Improvement in Wireless Sensor Networks

机译:无线传感器网络中改善服务质量的拥塞预测模型

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摘要

Information technology (IT) is pushing ahead with drastic reforms of modern life for improvement of human welfare. Objects constitute “Information Networks” through smart, self-regulated information gathering that also recognizes and controls current information states in Wireless Sensor Networks (WSNs). Information observed from sensor networks in real-time is used to increase quality of life (QoL) in various industries and daily life. One of the key challenges of the WSNs is how to achieve lossless data transmission. Although nowadays sensor nodes have enhanced capacities, it is hard to assure lossless and reliable end-to-end data transmission in WSNs due to the unstable wireless links and low hard ware resources to satisfy high quality of service (QoS) requirements. We propose a node and path traffic prediction model to predict and minimize the congestion. This solution includes prediction of packet generation due to network congestion from both periodic and event data generation. Simulation using NS-2 and Matlab is used to demonstrate the effectiveness of the proposed solution.
机译:信息技术(IT)正在进行大刀阔斧的现代生活改革,以改善人类福祉。对象通过智能的,自我调节的信息收集构成“信息网络”,该信息收集还可以识别和控制无线传感器网络(WSN)中的当前信息状态。从传感器网络实时观察到的信息可用于提高各种行业和日常生活中的生活质量(QoL)。 WSN的主要挑战之一是如何实现无损数据传输。尽管如今的传感器节点具有增强的容量,但是由于不稳定的无线链路和较少的硬件资源无法满足高服务质量(QoS)的要求,因此难以确保WSN中无损且可靠的端到端数据传输。我们提出了一种节点和路径流量预测模型,以预测并最小化拥塞。该解决方案包括根据周期性和事件数据生成来预测由于网络拥塞而导致的数据包生成。使用NS-2和Matlab进行的仿真证明了所提出解决方案的有效性。

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