# Resilience Quantification of Smart Distribution Networks--A Bird's Eye View Perspective
## 5 Literature Review
### Grid ICT Network
#### 5.3.1 Performance Calculation, Resilience Metrics, and Extreme Event  
Figures of performance (FoP) defined for ICT system in distribution grid are different from the ones presented before for electric service. Both [142; 144] adopt simulation-based modeling to set the ground for resilience quantification. The former builds upon the ad-hoc nature of wireless sensor networks (WSNs) technology that can be used to support metering infrastructure for redundancy and replication, therefore the use of a WSN simulator to evaluate various routing protocols (assumed 300 nodes) based on five performance measures: average delivery ratio, energy efficiency, delivery fairness, average throughput, and delay efficiency. Then, all these are normalized and provided as an equiangular polygon where each performance metric is presented by an axis. Resilience metric is taken as the area of that polygon, so the wider it is, the more resilient is the routing protocol against selective forwarding attacks. Authors in [144] consider a simpler configuration with one software defined networking (SDN) controller, and three substations each having a connected field device; with the goal to show that SDN is a viable technology with negligible switching delay to backup wireless communication and a minimum number of packet loss, which are taken as resilience metrics. A graph-based analytical model is adopted in [140] to determine the needed transmission power and required number of gateways for wireless-enabled mesh architectures in the context of smart metering. A proposed methodology involves clustering to assign each smart meter to a gateway, then the average number of hops and the number of independent paths to reach the gateway are calculated as intra-cluster resilience metrics, while node capability to connect to other gateways in case of a primary gateway failure is addressed by inter-cluster resilience. A different graph approach is used by [141] to consider dependencies between ICT and measurement layers which, seen from a higher perspective, are no more than the entire communication infrastructure used in a smart grid. The degree of centrality is used to find the importance of each communication link and measurement unit,  
\begin{table}
\begin{tabular}{p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt}} \hline \hline \multirow{2}{*}{**Paper**} & \multicolumn{3}{c}{**Extreme Event**} & \multicolumn{3}{c}{**Performance Calculation**} \\ \cline{3-8}  & \multirow{2}{*}{**Single Event**} & \multirow{2}{*}{**Wide-Range of Events**} & \multicolumn{3}{c}{**Systems Model**} \\ \cline{3-8}  & & & **Contingency Model** & **Fragility Model** & **Restoration Model** & **Functional Model** \\ \hline \multirow{3}{*}{[140]} & \multicolumn{3}{c}{Scenarios with different network conditions} & \multicolumn{3}{c}{Graph theory + Clustering} \\ \cline{2-8}  & \multicolumn{3}{c}{Generic HILP event} & \multicolumn{3}{c}{WAMS dependency analysis} \\ \cline{2-8}  & \multicolumn{3}{c}{} & \multicolumn{3}{c}{} & \multicolumn{3}{c}{} & \multicolumn{3}{c}{} \\ \cline{2-8}  & \multicolumn{3}{c}{} & \multicolumn{3}{c}{} & \multicolumn{3}{c}{} & \multicolumn{3}{c}{} \\ \cline{2-8}  & \multicolumn{3}{c}{} & \multicolumn{3}{c}{} & \multicolumn{3}{c}{} & \multicolumn{3}{c}{} \\ \hline \multirow{3}{*}{[142]} & \multicolumn{3}{c}{\ \begin{tabular}{c} Selective \\ Forwarding \\ attacks \\ \end{tabular}  } & \multicolumn{3}{c}{
\begin{tabular}{c} \& \& \& \& \& \\ \multicolumn{3}{c}{} \\ \multicol  
then resilience metric is defined as the deviation from ideal importance values, knowing that the main goal is to reduce the importance of critical nodes that increases the robustness of the network. At this point, one can notice the absence of resilience phases notion from the presented works so far, which is a major drawback. This can be seen also from the relatively low importance given to disruption modeling and characterization, considered very important in resilience studies.