<< NARVAL_M_DijkstraMP NARVAL NARVAL_M_DistanceNPoi >>

NARVAL >> NARVAL > NARVAL_M_DijkstraWeight

NARVAL_M_DijkstraWeight

Perform the Dijkstra's algorithm on a network topology from a source node in respect with given links weights (shortest path to all remaining nodes).

Calling Sequence

[d,p] = NARVAL_M_DijkstraWeight(n,h,t,w,nd)

Parameters

n :

network size.

h :

links head vector.

t :

links tail vector.

w :

links weight vector.

nd :

source node.

d :

distance vector from the source node towards remaining network nodes.

p :

predecessors vector to reach the source node from remaining network nodes.

Description

NARVAL_M_DijkstraWeight performs the Dijkstra's algorithm from the source node nd on the network topology represented by the 3 following vectors: h, t and w. Links weights are provided by the user. d and p enable to reconstruct the shortest path between any network node towards the source node ni (WIKIPEDIA).

Pseudo-Code (Wikipedia)

1  function Dijkstra(Graph, source):
2      for each vertex v in Graph:           // Initializations
3          dist[v] := infinity               // Unknown distance function from source to v
4          previous[v] := undefined          // Previous node in optimal path from source
5      dist[source] := 0                     // Distance from source to source
6      Q := the set of all nodes in Graph
       // All nodes in the graph are unoptimized - thus are in Q
7      while Q is not empty:                 // The main loop
8          u := vertex in Q with smallest dist[]
9          if dist[u] = infinity:
10              break                         // all remaining vertices are inaccessible from source
11          remove u from Q
12          for each neighbor v of u:         // where v has not yet been removed from Q.
13              alt := dist[u] + dist_between(u, v) 
14              if alt is inferior to dist[v]:             // Relax (u,v,a)
15                  dist[v] := alt
16                  previous[v] := u
17      return dist[]

Examples

n=80;//network size
L=1000;//network square area side
dmax=100;//locality radius
[g]=NARVAL_T_LocalityConnex(n,L,dmax);//generation of a random topology in respect with the Locality method. 
i=NARVAL_F_Random(length(g.node_x));//selection of the source node
ind=1;//window index
f=NARVAL_G_ShowNodesIndex(g,ind);
[dist,pred]=NARVAL_M_DijkstraWeight(g.node_number,g.head,g.tail,g.edge_length,i);//Application of NARVAL_M_DijkstraWeight
i
dist
pred

Dependency

NARVAL_F_Remov, NARVAL_M_NeighborhoodN

Authors

Foued Melakessou

Contact

Dr. Foued Melakessou

Research Associate

Interdisciplinary Centre for Security, Reliability and Trust

Room F106

University of Luxembourg

6, rue Coudenhove Kalergi

L-1359 Luxembourg-Kirchberg

E-mail: foued.melakessou@uni.lu

Tel: (+352) 46 66 44 5346

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