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An OpenMP-Based Algorithmic Optimization for Congestion Control of Network Traffic

机译:基于OpenMP的网络流量控制算法优化

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The last decade being a web revolution in the field of electronic media, data and information exchange in various forms has significantly increased. With the advancement in the technological aspects of the communication mechanism, the textual form of data has taken the shape of audiovisual format, and more and more content over internet is being shared in this form. Data sharing in this form calls for the need of high bandwidth consumption which may slow down the network resulting in performance degradation of content delivery networks due to congestion. Several attempts have been made by the researchers to propose various techniques and algorithms to achieve optimal performance of the network resources under high-usage circumstances. But due to high-dense network architectures, the performance implementations of suggested algorithms for congestion may not be able to produce the desired results in real time. In this paper, we have presented an optimized multi-core architecture-based parallel version of two congestion control algorithms-leaky bucket and choke packet. The experimental results over a dense network show that optimized parallel implementation using OpenMP programming specification gets the network rebalancing in a very short span of time as compared to its serial counterpart. The proposed approach runs 60% faster than the serial implementation. The graphical map for the speed up continues to increase with the size of the network and routers. The paper throws the light on the implementation aspects as well as result analysis in detail along with some existing algorithms for the problem.
机译:最后十年是电子媒体领域的Web革命,各种形式的数据和信息交换的革命显着增加。随着沟通机制的技术方面的进步,仔细形式的数据形成了视听格式的形状,越来越多的互联网内容正在以这种形式共享。数据共享在此表单中呼吁需要高带宽消耗,这可能会降低网络,导致由于拥塞引起的内容传递网络的性能降低。研究人员已经提出了几次尝试,提出了各种技术和算法,以在高使用情况下实现网络资源的最佳性能。但由于高密度的网络架构,建议算法的性能实现可能无法实时产生所需的结果。在本文中,我们介绍了一种优化的基于多核架构的并行版本的两个拥塞控制算法泄漏桶和扼流包。在密集网络上的实验结果表明,与其串行对应物相比,使用OpenMP编程规范的优化并行实现使网络重新平衡在非常短的时间内。所提出的方法比串行实施速度快60%。随着网络和路由器的大小,加速的图形图继续增加。纸张对实施方面的光抛光以及详细的结果分析以及一些现有算法的问题。

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