# Survivable Deployments of Optical Sensor Networks against Multiple Failures and Disasters: A Survey
## 3 Sensing Connectivity and K-Node (Edge) Sensing Connectivity
### Content Connectivity and K-Node (Edge) Content Connectivity  
The content connectivity is proposed with respect to network connectivity. Network connectivity is one of the basic concepts of graph theory. It is an important measure of the robustness of a network. Network connectivity indicates the minimum number of elements (nodes or edges) that need to be removed to disconnect the remaining nodes from each other. Based on this, content connectivity is defined as the reachability of the content from any point of a data center network [36]. Figure 6 presents the survivability capability comparison between network connectivity and content connectivity. In Figure 7a, a user obtains the required video through one end-to-end light path. However, the video is interrupted when a failure occurs on any link along this light path. In Figure 7b, a user obtains the required video through end-to-content light paths. Even if a failure occurs on any link in physical layer, the video is still available. The content connectivity has been used to improve the survivability \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Disasters** & **Affect Region** & **Probability** & **Severity** & **Impact** \\ \hline Earthquake & Wide & Low & High & Fiber Line/Sensors \\ Landslide & Narrow & High & Low & Fiber Line/Sensors \\ Collapse & Narrow & High & Low & Fiber Line \\ Mud–Rock Flow & Narrow & High & Low & Fiber Line \\ Flood & Wide & Low & Low & Fiber Line/Sensors \\ Volcano & Narrow & Low & Low & Fiber Line/Sensors \\ Rainstorm & Wide & High & Low & Fiber Line/Sensors \\ Land Freezing and & Narrow & High & Low & Fiber Line \\ Thawing & & Low & Low & Fiber Line \\ Snowstorm & Wide & Low & Low & Fiber Line \\ High Temperature & Wide & High & Low & Sensors \\ \hline \hline \end{tabular}
\end{table} 
Table 5: The characteristics of different kinds of natural disasters. of optical data center networks against natural disasters. In [127], the authors proposed a protection scheme for a disaster recovery center based on content connectivity against disasters in disaster recovery center networks. In [128], the authors proposed survivable multipath routing and spectrum allocation with a content connectivity scheme in OFDM-based elastic data center networks. In [129], the authors focused on double-link failures and considered different combinations of content connectivity and network connectivity. They presented an ILP formulation for survivable virtual network mapping to guarantee the network connectivity after single-link failures to maintain the content connectivity after double-link failures. In [130], the authors proposed a dynamic content replacement scheme to minimize spectrum consumption, blocking probability, and network latency. In [131], the authors proposed an efficient dynamic content replacement scheme to minimize blocking probability and resource utilization. In [132], the authors proposed a disaster-aware dynamic content-management algorithm that can adjust the existing placement based on dynamic settings. Besides reducing the overall risk and making the network disaster aware, reducing network resource usage and satisfying quality-of-service requirements can also be achieved via this approach. In graph theory, \(k\)-node (edge) network connectivity is defined where there does not exist a set of \(k-1\) nodes (edges) whose removal disconnects the connectivity from any remaining node to the needed content, which is replicated and maintained in multiple data centers. In contrast to \(k\)-node (edge) network connectivity, \(k\)-node (edge) content connectivity is defined where there does not exist a set of \(k-1\) nodes (edges) whose removal disconnects the connectivity from any remaining node to the needed content, which is replicated and maintained in multiple data centers [37]. The \(k\)-node (edge) content connectivity can be used to design disaster-resilient optical data center networks.