基于软件定义网络的5G网络边缘辅助拥塞控制机制

M. Nasimi, Mohammad Asif Habibi, B. Han, H. Schotten
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引用次数: 23

摘要

为了应对与大量新兴应用程序和服务相关的数据流量的爆炸性增长,这些应用程序和服务预计将被普通用户和垂直行业使用,拥塞控制机制被认为是至关重要的。在本文中,我们提出了一种可以在多访问边缘计算(MEC)框架内运行的拥塞控制机制。该机制在考虑网络状况和服务质量(QoS)的前提下,能够对流量的选择性缓冲做出实时决策。为了支持MEC辅助方案,MEC服务器应该在本地存储可容忍延迟的数据流量,直到延迟条件到期。这使网络能够更好地控制高优先级数据的无线电资源供应。为了实现这一目标,我们引入了一个名为拥塞控制引擎(CCE)的专用功能,它可以通过无线网络信息服务(RNIS)功能捕获无线接入网(RAN)状况,并利用这些信息做出实时决策,选择性地卸载流量,使其能够更智能地执行。分析评估结果表明,该机制能够更有效地缓解网络拥塞。
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Edge-Assisted Congestion Control Mechanism for 5G Network Using Software-Defined Networking
In order to cope with explosive growth of data traffic which is associated with a wide plethora of emerging application and services that are expected to be used by both ordinary users and vertical industries, congestion control mechanism is considered to be vital. In this paper, we proposed a congestion control mechanism that could function within the framework of Multi-Access Edge Computing (MEC). The proposed mechanism is aiming to make real time decision for selectively buffering traffic, while taking network condition and Quality of Service (QoS) into consideration. In order to support a MEC-assisted scheme, the MEC server is expected to locally store delay-tolerant data traffics until the delay conditions expire. This enables network to have better control over the radio resource provisioning of higher priority data. To achieve this, we introduced a dedicated function known as Congestion Control Engine (CCE), which can capture Radio Access Network (RAN) condition through Radio Network Information Service (RNIS) function, and use this knowledge to make real time decision for selectively offloading traffic so that it can perform more intelligently. Analytical evaluation results of our proposed mechanism confirms that it can alleviate network congestion more efficiently.
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