# Trade-offs between Risk and Operational Cost in SDN Failure Recovery Plan
### Related Work
The authors also proposed a measure of diversity that considers physical distance as opposed to a measure that solely relies on node or link disjointness. For this purpose, several networks were studied with different ranges of Effective Path Diversity (EPD) thresholds. Flow robustness was used as a metric in this study to indicate the level of topological survivability and was measured with increasing link and node failure probability. The results demonstrated improved network resiliency by applying a path diversification scheme. For a selected set of paths between the source and destination, path diversities can be aggregated to calculate an effective path diversity factor [22]. The average effective path diversity of all node pairs within the graph was considered as a metric for total graph diversity and was employed to estimate network survivability in the case of simultaneous failure of nodes and links in probabilistic failure scenarios. Using the proposed metric, connected nodes in each failure scenario were computed. Risk-based routing models have also been studied as effective approaches to handling large-scale probabilistic failures. In [23], the authors developed a model to design survivable networks based on managing risk. The main goal of this study was to spend a fixed budget on the best part of the network to enhance network resiliency. Considering prior knowledge regarding link failure probability, end-to-end path failure probability can be computed. With this knowledge, it is possible to select working and backup paths with the minimum joint path failure probability. Using risk minimization and employing traffic engineering, path pair protection can be developed in multi-failure scenarios [24]. In [25], they attempt to identify a pair of paths between two specified nodes that is the cheapestand has the fewest risks in general. They provide an algorithm that, in the event of failure along the primary path, calculates both a primary and a backup path to reduce the chance of connection failure between source and destination nodes while minimizing bandwidth routing costs. A probabilistic model for failures resulting from natural disasters (e.g., Earthquakes) was proposed in [26]. Based on that model, the authors developed a predictive restoration plan that aimed to strike a balance between capacity optimization and the probability of service disruption. They further enhanced this method by taking network topological characteristics into account when calculating the risk and proposed adaptive and proactive risk management to protect network traffic in high-risk areas [11]. This approach is particularly suitable for SDN networks as it can be implemented at the SDN controller where information about the current failure rates and status of network elements can be stored and analyzed. The issue of failure correlation between nodes in an SDN network and its impact on availability have also been studied in [27]. While most of the above studies primarily look at the data plane, the issue of reconstruction of control paths between SDN nodes and SDN controllers has been recently examined in [28]. While the above works discuss and propose various solutions for network restoration in case of probabilistic failures, their performance analysis does not consider the unique operations of software-defined networks that may deploy virtualized switches. A previous study by the authors [10] showed that the operational performance in software-controlled flow tables in SDN switches, particularly the number of operations required to update the flows, could affect the choice of optimal backup paths and rerouting operations. Our work here builds on top of the work in [10] and extends it to probabilistic failure scenarios, providing further insights into the performance of Software Defined Wide Area Networks (SD-WAN).