Table 4: Results of the shortest path detection (in Figure 12) using the NAOP-simulator and Benchmarking between the NAOP paradigm and the DVHNN concept. A scenario corresponds to a specific choice of source-destination pair.

Shortest path results using NAOP-simulatorNAOP versus DVHNN
From source
to destination
Sim. time (sim)Convergence
Edges in the shortest pathTotal cost of the pathNAOP (ms)VDHNN (ms)NAOPDVHNN

Small weights values: the cost of an edge with index “” is “
0.10.4548.4YesYes
, 0.41.73114YesYes
, , and 0.842.2YesNo
0.3177.3YesYes
0.737.9YesNo
, 0.57.689.2YesYes
0.20.9468.9YesYes

High weights values: the cost of an edge with index “” is “
10000.54YesNo
, 40000.77YesNo
, , and 800070.3YesNo
30000.22YesNo
700085.4YesNo
, 50000.19YesNo
20000.16YesNo

In this paper, the concepts have been all implemented in Matlab on a standard PC.