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Network Function Virtualization-Aware Orchestrator for Service Function Chaining Placement in the Cloud

机译:网络功能虚拟化感知协调器,用于将服务功能链放置在云中

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Network function virtualization (NFV) has been introduced by network service providers to overcome various challenges that hinder them from satisfying the growing demand for networking services with higher return-on-investment. The association of NFV with the leading technologies of information technology virtualization and software defined networking is paving the way for flexible and dynamic orchestration of the VNFs, but still, various challenges need to be addressed. The VNFs instantiation and placement problems on data center's (DC) servers are key enablers to achieve the desired flexible and dynamic NFV applications. In this paper, we have addressed the VNF placement problem by providing a novel mixed integer linear programming (MILP) optimization model and a novel heuristic solution, Betweenness centrality Algorithm for Component Orchestration of NFV platform (BACON), for small- and large-scale DC networks. The proposed solution addresses the VNF placement while taking into consideration the carrier-grade nature of the NFV applications and at the same time, minimizing the intra-and end-to-end delays of the service function chain (SFC). Also, the proposed approach enhances the reliability and the quality of service (QoS) of the SFC by maximizing the count of the functional group members. To evaluate the performance of the proposed solution, this paper conducts a comparative analysis with an NFV-agnostic algorithm and a greedy-k-NFV approach, which is proposed in the literature work. Also, this paper defines the complexity and the order of magnitude of the MILP model and BACON. BACON outperforms the greedy algorithms especially the greedy-k-NFV solution and has a lower complexity, which is calculated as O((n(8)-n(2))/2). The simulation results show that finding an optimized VNF placement can achieve minimal SFCs delays and enhance the QoS accordingly.
机译:网络服务提供商已引入网络功能虚拟化(NFV),以克服各种阻碍他们以更高的投资回报率满足网络服务不断增长的需求的挑战。 NFV与信息技术虚拟化和软件定义网络的领先技术的结合为VNF的灵活动态编排铺平了道路,但仍然需要解决各种挑战。数据中心(DC)服务器上的VNF实例化和放置问题是实现所需的灵活,动态NFV应用程序的关键因素。在本文中,我们通过提供新颖的混合整数线性规划(MILP)优化模型和新颖的启发式解决方案,即针对小规模和大规模的NFV平台组件协调的中间性中心性算法(BACON),解决了VNF放置问题。直流网络。提出的解决方案解决了VNF放置问题,同时考虑了NFV应用程序的运营商级性质,同时将服务功能链(SFC)的端到端内延迟最小化。同样,通过最大化功能组成员的数量,所提出的方法增强了SFC的可靠性和服务质量(QoS)。为了评估所提出解决方案的性能,本文使用与文献无关的NFV不可知算法和贪婪k-NFV方法进行了比较分析。此外,本文还定义了MILP模型和BACON的复杂性和数量级。 BACON优于贪心算法,尤其是贪婪k-NFV解决方案,并且具有较低的复杂度,其计算为O((n(8)-n(2))/ 2)。仿真结果表明,找到优化的VNF布局可以实现最小的SFC延迟并相应地提高QoS。

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