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Efficient flow processing-aware controller placement in future wireless networks

机译:在未来的无线网络中高效感知流量处理的控制器

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Future wireless access networks include a broad variety of applications. Examples for these range from network applications meant to optimize the usage of resources, e.g. Coordinated Multi-Point (CoMP) transmission, over coordinating network mechanisms for Inter-Cell Interference Coordination (ICIC) to virtualized applications to gain flexibility and save hardware costs such as Virtual Network Functions (VNFs). Still, there is one common thread for all these functions: the necessity for data flow processing. Data flow processing imposes many requirements on network resources and a good allocation of the locations for data processing in a network is a challenging task and crucial for network performance. Hence, data flow processing is a significant point to be considered when searching for efficient control architectures for future wireless networks. We propose a flow processing-aware controller placement framework, which introduces data flow processing to the research domain of future wireless network control and enhances the classic Software-Defined Networking (SDN) view of reducing network control to just packet forwarding. We have developed an optimization problem and a heuristic algorithm that verify the practical feasibility of flow processing-aware controller placement. Our evaluations reveal that the heuristic algorithm performs close to optimal, while reducing the runtime by about four orders of magnitude compared to the optimization problem and thus providing acceptable runtime for real-world application.
机译:未来的无线接入网络将包括各种各样的应用。这些示例包括旨在优化资源使用的网络应用,例如通过小区间干扰协调(ICIC)到虚拟化应用程序的协调网络机制上的协调多点(CoMP)传输,可以获得灵活性并节省了诸如虚拟网络功能(VNF)之类的硬件成本。尽管如此,所有这些功能都有一个共同的线程:数据流处理的必要性。数据流处理对网络资源提出了许多要求,并且网络中数据处理的位置的良好分配是一项艰巨的任务,对网络性能至关重要。因此,在为未来的无线网络搜索有效的控制架构时,数据流处理是要考虑的重要点。我们提出了一种可感知流处理的控制器放置框架,该框架将数据流处理引入了未来的无线网络控制的研究领域,并增强了经典的软件定义网络(SDN)观点,即将网络控制减少到仅数据包转发。我们已经开发出一个优化问题和一种启发式算法,可以验证流处理感知控制器放置的实际可行性。我们的评估表明,启发式算法的性能接近最佳,同时与优化问题相比,将运行时间减少了大约四个数量级,从而为实际应用程序提供了可接受的运行时间。

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