Minuteman Launch Cotrol Center
The US Strategic Command has got a plenty of airplanes to sustain reliable and redundante control of the nuclear triad (ICBM, SSBN and Bombers) in case of bolt out of blue attack in order to retaliate adversary.
For more about ANCCS and Minuteman surviveability see:
1. https://rpubs.com/alex-lev/483336,
2. https://rpubs.com/alex-lev/260829,
3. https://rstudio-pubs-static.s3.amazonaws.com/200551_499f1be280024d50b83916cf6b62e37e.html#probability-for-retaliation-strike
4. https://rpubs.com/alex-lev/439123
PACCS concept
library(igraph)
nodes <- cbind("id"=c("necap","paccsr", "aabncpe","saclg",
"lcc","aabncpw","ercs","alcc","icbm"))
links <- cbind("from"=c("necap"),"to"=c("lcc","paccsr","aabncpe","saclg","aabncpw"))
links2 <- cbind("from"=c("paccsr"),"to"=c("aabncpe"))
links3 <- cbind("from"=c("aabncpe"),"to"=c("saclg"))
links4 <- cbind("from"=c("saclg"),"to"=c("aabncpw","ercs","lcc"))
links5 <- cbind("from"=c("aabncpw"),"to"=c("alcc"))
links6 <- cbind("from"=c("ercs"),"to"=c("alcc"))
links7 <- cbind("from"=c("alcc"),"to"=c("icbm"))
links8 <- cbind("from"=c("lcc"),"to"=c("icbm"))
links_all <- rbind(links,links2,links3,links4,links5,links6,links7,links8)
net = graph_from_data_frame(links_all,vertices = nodes,directed = T)
plot(net,layout=layout_nicely)
get.adjacency(net)
## 9 x 9 sparse Matrix of class "dgCMatrix"
## necap paccsr aabncpe saclg lcc aabncpw ercs alcc icbm
## necap . 1 1 1 1 1 . . .
## paccsr . . 1 . . . . . .
## aabncpe . . . 1 . . . . .
## saclg . . . . 1 1 1 . .
## lcc . . . . . . . . 1
## aabncpw . . . . . . . 1 .
## ercs . . . . . . . 1 .
## alcc . . . . . . . . 1
## icbm . . . . . . . . .
degree(net)
## necap paccsr aabncpe saclg lcc aabncpw ercs alcc icbm
## 5 2 3 5 3 3 2 3 2
eigen_centrality(net)$value
## [1] 3.498593
eigen_centrality(net)$vector
## necap paccsr aabncpe saclg lcc aabncpw ercs alcc
## 1.0000000 0.4872944 0.7048446 0.9786699 0.6506162 0.6771679 0.3913387 0.3904650
## icbm
## 0.2975714
barplot(sort(eigen_centrality(net)$vector))
ceb <- cluster_edge_betweenness(net)
dendPlot(ceb, mode="hclust")
plot(ceb, net)
cfg <- cluster_fast_greedy(as.undirected(net))
plot(cfg, as.undirected(net))
GBSD concept
net21 <- graph(c("necap","lcc","necap","icbm","necap",
"germes","germes","lcc","germes","icbm","lcc","icbm"))
plot(net21)
get.adjacency(net21)
## 4 x 4 sparse Matrix of class "dgCMatrix"
## necap lcc icbm germes
## necap . 1 1 1
## lcc . . 1 .
## icbm . . . .
## germes . 1 1 .
degree(net21)
## necap lcc icbm germes
## 3 3 3 3
eigen_centrality(net21)$value
## [1] 3
eigen_centrality(net21)$vector
## necap lcc icbm germes
## 1 1 1 1
cfg21 <- cluster_fast_greedy(as.undirected(net21))
plot(cfg21, as.undirected(net21))
hs <- hub_score(net, weights=NA)$vector
hs21 <- hub_score(net21, weights=NA)$vector
par(mfrow=c(1,2))
plot(net, vertex.size=hs*50, main="1980")
plot(net21, vertex.size=hs21*50, main="2020")