Article

Optimal State Replication in Stateful Data Planes

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Abstract

In SDN stateful data planes, switches can execute algorithms to process traffic based on local states. This approach permits to offload decisions from the controller to the switches, thus reducing the latency when reacting to network events. We consider distributed network applications that process traffic at each switch based on local replicas of network-wide states. Replicating a state across multiple switches poses many challenges, because the number of state replicas and their placement affects both the data traffic distribution and the amount of synchronization traffic among the replicas. In this paper, we formulate the optimal placement problem for replicated states, taking into account the data traffic routing, to ensure that traffic flows are properly managed by network applications, and the synchronization traffic between replicas, to ensure state coherence. Due to the high complexity required to find the optimal solution, we also propose an approximated algorithm to scale to large network instances. We numerically show that this algorithm, despite its simplicity, well approximates the optimal solution. We also show the beneficial effects of state replication with respect to the singlereplica scenario, so far considered in the literature. Finally, we provide an asymptotic analysis to find the optimal number of replicas.

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... The optimal replication problem for multiple replicas has been defined and investigated in [16]. Given a network application and the corresponding states, the problem considers all the traffic flows that are affected by/affect such states and, based on a generic cost function, computes (i) the optimal number of replicas, (ii) their placement within the network and (iii) the corresponding optimal traffic routing. ...
... Given a network application and the corresponding states, the problem considers all the traffic flows that are affected by/affect such states and, based on a generic cost function, computes (i) the optimal number of replicas, (ii) their placement within the network and (iii) the corresponding optimal traffic routing. The work in [16] can be used as a building block for LOADER (i.e., the optimization engine), which provides the programming framework and the implementation for replicated states. ...
... The complexity is further increased when considering that a given state of an application may be accessed by different network applications such as in the case of two network applications reading a common counter. This inter and intra application dependency imposes a constraint on how the traffic must be routed across individual elements of the split application to ensure the correctness on the execution of the application [6,16]. ...
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... Additionally, data replication helps overcome long data transmission delays by keeping information close to the places where queries are generated [20,21]. Moreover, replications of many of the same datasets are dispersed during replication in the data network [22]. Different sites may have various functional features and capabilities [23], and coping of the same files on these sites is generally called a replica replacement problem [24]. ...
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... Network monitoring Collect statistics (e.g., number of packets per flow entry) [12,13] 2021 Flow size counter Report to the controller after the completion of collecting the size of flow in data plane [14] 2020 ...
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