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Comparative performance analysis of WiMAX networks with CBR traffic in various mobility and energy models

机译:在各种移动性和能源模型中具有CBR流量的WiMAX网络的比较性能分析

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Social needs and demand changes fuel the technology to rise and meet those needs. Nowadays, users of wireless network communications tend to use their small size, limited powered mobile devices to access multimedia services with good quality of service anytime, anywhere. This implies more power consumption and raises the need for energy efficiency in doing more work with less power consumption. WiMAX (World Wide Interoperability for Microwave Access) supports battery-operated terminals and allow them to operate longer. It defines power-saving features and signaling methods, helpingmobile terminal to shift to idle or sleep mode when it is not transmitting or receiving. In this paper, WiMAX Network performance for CBR traffic in three different Mobility models and four different Energy Models have been analyzed. The simulations are carried out using Qualnet simulator. Results are in the form of throughput, Delay, Jitter, energy consumption in transmitting, receiving, sleep and idle mode. Further, to observe the best network performance in terms of Mobility models as well as the efficient energy model for each mobility models, the comparative analysis of different performance metrics has been evaluated. Depending on the results we get from this study we can say that energy model does not affect the performance of the network in case of flag and random mobility models, while it shows a little effect on network performance in case of using group mobility. For group mobility Mica Motes gives the best performance.
机译:社会需求和需求变化推动了技术的兴起并满足这些需求。如今,无线网络通信的用户倾向于使用其体积小,受限制的移动设备来随时随地访问具有良好服务质量的多媒体服务。这意味着更多的功耗,并且在以更少的功耗进行更多工作的过程中提高了对能源效率的需求。 WiMAX(微波访问全球互通性)支持电池供电的终端,并允许它们工作更长的时间。它定义了省电功能和信令方法,可帮助移动终端在不发送或接收信号时转变为空闲或睡眠模式。本文分析了在三种不同的移动性模型和四种不同的能量模型中用于CBR流量的WiMAX网络性能。使用Qualnet仿真器进行仿真。结果的形式为吞吐量,延迟,抖动,发送,接收,睡眠和空闲模式下的能耗。此外,为了在移动性模型以及每个移动性模型的有效能量模型方面观察到最佳的网络性能,已对不同性能指标的比较分析进行了评估。根据我们从这项研究中获得的结果,我们可以说,在使用标记和随机移动性模型的情况下,能量模型不会影响网络的性能,而在使用组移动性的情况下,它对网络性能的影响很小。对于团体流动性,Mica Motes具有最佳性能。

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