# Trade-offs between Risk and Operational Cost in SDN Failure Recovery Plan
### Related Work  
An overview of network disaster survival techniques is shown in Figure 1. Disaster-related failures may cover several network domains and include different levels. Disaster modeling is used to assess the risks involved and their related physical and financial impacts [12]. We will focus here on studies that specifically address probabilistic failure scenarios. The purpose of these studies, in general, is to design a survivable network using pre-planned backup paths with minimum mutual failure probability [13]. Network design in failure scenarios also depends heavily on probabilistic models for network failures. An early example of such models was used for improved network survivability in overlay networks in [14], where a method was presented to find a backup route with minimum joint path failure probability with the working path. This study assumed that overlay link failure probabilities were small and employed exponential failure models for physical links. Then, overlay link failure probability was calculated based on independent physical link failure probabilities, and the backup path routing problem was formulated as an Integer Quadratic Programming (IQP). Figure 1: Overview of Disaster-based Failure Survivability Mechanisms [12]. Identifying vulnerable network locations in the event of probabilistic failure scenarios can be used to redesign connectivity or add extra capacity to improve network resiliency. For instance, failure probability was calculated using a grid partitioned-based model in [15] to assess vulnerable locations in the network. In a related study in network vulnerability [16], regional failure events such as earthquakes or floods were modeled as random line-segment cuts. The authors applied geometrical probability theory to develop a grid-partitioned-based estimation model to locate vulnerable network parts and developed a model to determine single and pairwise link failure probabilities. A probabilistic approach to model correlated link failures was presented in [17], where a model was developed to study stochastic failures resulting from disasters that could be spatially correlated. Failure correlation was used to assign higher failure probability in specific areas to implement more failure events. The main contribution of this model was to identify vulnerable network locations. Probabilistic geographical failure has also been discussed in [18], where the authors studied probabilistic approaches and developed algorithms for pre-computed protection plans. The proposed model makes it possible to identify vulnerable locations in the network. However, the pre-planned protection scheme is infeasible in cases of large-scale failure. In [19], they aim to restore connection reliability following a disaster in order to achieve the minimum requirements in accordance with the relevant service level. They proposed a Reliability Sustainable Survivability (RSS) scheme to recover the affected connections with some degree of reliability in disaster scenarios, such as earthquakes. They used the reliability threshold as the point-of-rerouting decision. The model initially (re)routes this connection along the main path, after which RSS generates a secondary path for this connection to increase reliability if the connection reliability falls below the specified reliability threshold. In [20], the authors introduced a taxonomy of network failure challenges and developed a framework to evaluate the effect of different failure scenarios such as probabilistic uncorrelated random failures in non-malicious problems and deterministic failure in large-scale scenarios. There have also been many proposals for proactive handling of probabilistic failures in communication networks. In [21], path diversification was employed to design and evaluate survivable networks. The proposed algorithm was able to select a set of alternative paths with different diversities while meeting performance constraints.