Recently, the programmable data plane (PDP) switches have been considered as the key enablers for in-network computing. However, the limited memory resources in them for flow tables might restrict their performance. This work addresses this challenge by studying how to optimize the placements of flow tables in the external memory on multiple servers, and to access them with remote direct memory access (RDMA) for ensuring low latency. Specifically, we consider a data-center network (DCN) that uses PDP switches as top-of-rack (ToR) switches, and propose and optimize the hybrid flow table installation (hFT-INST) on each ToR switch. With hFT-INST, the switch can either store flow tables in its local memory or use RDMA to install and access them remotely in its rack servers. We first design the protocol and operation procedure of hFT-INST. Then, regarding the key problem of hFT-INST, i.e., how to place the flow tables on the external memory on different servers, we take a few practical parameters into account, and formulate a mixed integer linear programming (MILP) model to tackle it. Next, the optimization in the MILP is transformed into a capacitated facility location problem (CFLP) with additional constraints. We further transform it into a ${k}$ -median problem through pre-processing, and design a polynomial-time approximation algorithm to solve the problem. Extensive simulations confirm the performance of our proposed algorithm. We also prototype our design of the hFT-INST, and conduct experiments to demonstrate its feasibility.

中文翻译：

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混合流表安装：优化服务器上​​流表的远程位置，以增强用于网络内计算的PDP交换机

最近，可编程数据平面（PDP）交换机已被视为网络内计算的关键推动力。但是，流表中有限的内存资源可能会限制其性能。这项工作通过研究如何优化流表在多台服务器上的外部存储器中的放置以及如何使用远程直接存储器访问（RDMA）来访问它们以确保低延迟来解决这一挑战。具体来说，我们考虑使用PDP交换机作为机架顶部（ToR）交换机的数据中心网络（DCN），并在每个ToR交换机上提出并优化混合流表安装（hFT-INST）。使用hFT-INST，交换机可以将流表存储在其本地内存中，也可以使用RDMA在其机架服务器中远程安装和访问它们。我们首先设计了hFT-INST的协议和操作过程。然后，关于hFT-INST的关键问题，即如何将流表放置在不同服务器上的外部存储器上，我们考虑了一些实际参数，并制定了混合整数线性规划（MILP）模型来解决该问题。接下来，将MILP中的优化转换为带有附加约束的能力有限的设施位置问题（CFLP）。我们进一步将其转化为 $ {k} $ 通过预处理对中值问题进行处理，并设计了多项式时间近似算法来解决该问题。大量的仿真证实了我们提出的算法的性能。我们还设计了hFT-INST的设计原型，并进行了实验以证明其可行性。