Update the vector of candidates where to propagate the topology discovery tree from a current node in respect with the node index (End).
[v,c,pred]=RoutingSearchEnd(i,g,v,c,pred)
current node.
network graph.
vector that gathers the chronological order how network nodes are visited.
vector of candidate nodes.
vector composed by the predecessor of each node in order to reach the source node.
RoutingSearchEnd updates the vector of candidates c where to propagate the topology discovery tree from the current node i in respect with the node index. The network nodes already visited by the algorithm are stored in v. A tree inside the graph g is constructed in respect with a source node defined as the root. This graph search algorithm begins at the root node and explores all the neighboring nodes. Then for each of those nearest nodes, unexplored neighbor nodes are explored, and so on. The search is done in respect with a discovery propagation towards the nodes with the smallest indexes. New candidates are added at the beginning of c.
n=100;//network size l=1000;//network squared area side d=100;//Locality radius [g]=NtgLocalityConnex(n,l,d);//generation of a topology nr=length(g.node_x);//real network size nl=length(g.head); i=Random(length(g.node_x));//selection of the source node pred=zeros(1,n);//initialization v=[];//visited c=[];//candidates [v,c,pred]=RoutingSearchEnd(i,g,v,c,pred);//application of RoutingSearchEnd p=[];//display the candidates, the first ones are represented with the smallest edge width for i=1:length(c) p=[p nodes_2_path([v c(i)],g)] end EC=ones(1,nl); EB=ones(1,nl); EC(p)=5; EB(p)=1:length(p); D=ones(1,nr); D([v c])=3; g.node_border=D; g.edge_color=EC; g.edge_width=EB; show_graph(g); i v c pred | ![]() | ![]() |