For software-defined networking (SDN) systems, to enhance the scalability and reliability of control plane, existing solutions adopt either multi-controller design with static switch-controller association, or static control devolution by delegating certain request processing back to switches. Such solutions can fall short in face of temporal variations of request traffics, incurring considerable local computation costs on switches and their communication costs to controllers. So far, it still remains an open problem to develop a joint online scheme that conducts dynamic switch-controller association and dynamic control devolution. In addition, the fundamental benefits of predictive scheduling to SDN systems still remain unexplored. In this paper, we identify the non-trivial trade-off in such a joint design and formulate a stochastic network optimization problem which aims to minimize time-averaged total system costs and ensure long-term queue stability. By exploiting the unique problem structure, we devise a predictive online switch-controller association and control devolution (POSCAD) scheme, which solves the problem through a series of online distributed decision making. Theoretical analysis shows that without prediction, POSCAD can achieve near-optimal total system costs a tunable trade-off for queue stability. With prediction, POSCAD can achieve even better performance with shorter latencies. We conduct extensive simulations to evaluate POSCAD. Notably, with mild-value of future information, POSCAD incurs a significant reduction in request latencies, even when faced with prediction errors.

中文翻译：

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SDN系统的预测开关控制器关联和控制下放

对于软件定义的网络（SDN）系统，为了增强控制平面的可伸缩性和可靠性，现有的解决方案要么采用具有静态开关控制器关联的多控制器设计，要么通过将某些请求处理委托给交换机来进行静态控制转移。面对请求业务量的时间变化，这样的解决方案可能不足，从而在交换机上引起相当大的本地计算成本以及它们与控制器的通信成本。到目前为止，开发进行动态开关控制器关联和动态控制下放的联合在线方案仍然是一个悬而未决的问题。此外，对SDN系统进行预测性调度的基本好处仍未开发。在本文中，我们在这种联合设计中确定了不小的折衷方案，并提出了一种随机网络优化问题，旨在最大程度地减少时间平均的总系统成本并确保长期队列稳定性。通过利用独特的问题结构，我们设计了一种预测性在线开关控制器关联和控制转移（POSCAD）方案，该方案通过一系列在线分布式决策解决了该问题。理论分析表明，无需预测，POSCAD即可实现接近最佳的总系统成本，因此可以在队列稳定性方面进行可调的权衡。通过预测，POSCAD可以以更短的延迟获得更好的性能。我们进行了广泛的仿真来评估POSCAD。值得注意的是，由于未来信息的价值不高，POSCAD大大减少了请求等待时间，