Source code for fnss.topologies.simplemodels
"""
Generate canonical deterministic topologies
"""
import networkx as nx
from fnss.topologies.topology import Topology
__all__ = ['ring_topology',
'line_topology',
'star_topology',
'full_mesh_topology',
'k_ary_tree_topology',
'dumbbell_topology',
]
[docs]def ring_topology(n):
"""
Return a ring topology of n nodes
Parameters
----------
n : int
The number of nodes
Returns
-------
topology : A Topology object
"""
if type(n) is not int:
raise TypeError('n argument must be of int type')
if n < 1:
raise ValueError('n argument must be a positive integer')
G = Topology(nx.path_graph(n))
G.add_edge(n-1, 0)
G.name = "ring_topology(%d)" % (n)
G.graph['type'] = 'ring'
return G
[docs]def line_topology(n):
"""
Return a line topology of n nodes
Parameters
----------
n : int
The number of nodes
Returns
-------
topology : A Topology object
"""
if type(n) is not int:
raise TypeError('n argument must be of int type')
if n < 1:
raise ValueError('n argument must be a positive integer')
G = Topology(nx.path_graph(n))
G.name = "line_topology(%d)" % (n)
G.graph['type'] = 'line'
return G
[docs]def star_topology(n):
"""
Return a line topology of n+1 nodes
The root node has id 0 while all leaf nodes have id (1, n + 1).
Each node has the attribute type which can either be "root" (for node 0) or
"leaf" for all other nodes
Parameters
----------
n : int
The number of leaf nodes
Returns
-------
topology : A Topology object
"""
if type(n) is not int:
raise TypeError('n argument must be of int type')
if n < 1:
raise ValueError('n argument must be a positive integer')
G = Topology(nx.star_graph(n))
G.name = "star_topology(%d)" % (n)
G.graph['type'] = 'star'
G.node[0]['type'] = 'root'
for v in range(1, n + 1):
G.node[v]['type'] = 'leaf'
return G
[docs]def full_mesh_topology(n):
"""
Return a fully connected mesh topology of n nodes
Parameters
----------
n : int
The number of nodes
Returns
-------
topology : A Topology object
"""
if type(n) is not int:
raise TypeError('n argument must be of int type')
if n < 1:
raise ValueError('n argument must be a positive integer')
G = Topology(nx.complete_graph(n))
G.name = "full_mesh_topology(%d)" % (n)
G.graph['type'] = 'full_mesh'
return G
[docs]def k_ary_tree_topology(k, h):
"""
Return a balanced k-ary tree topology of with depth h
Each node has two attributes:
- type: which can either be 'root', 'intermediate' or 'leaf'
- depth (0, h) the height of the node in the tree, where 0 is the root
and h are leaves.
Parameters
----------
k : int
The branching factor of the tree
h : int
The height or depth of the tree
Returns
-------
topology : A Topology object
"""
if type(k) is not int or type(h) is not int:
raise TypeError('k and h arguments must be of int type')
if k <= 1:
raise ValueError("Invalid k parameter. It should be > 1")
if h < 1:
raise ValueError("Invalid h parameter. It should be >=1")
G = Topology(nx.balanced_tree(k, h))
G.name = "k_ary_tree_topology(%d,%d)" % (k, h)
G.graph['type'] = 'tree'
G.graph['k'] = k
G.graph['h'] = h
G.node[0]['type'] = 'root'
G.node[0]['depth'] = 0
# Iterate through the tree to assign labels to nodes
v = 1
for depth in range(1, h + 1):
for _ in range(k**depth):
G.node[v]['depth'] = depth
if depth == h:
G.node[v]['type'] = 'leaf'
else:
G.node[v]['type'] = 'intermediate'
v += 1
return G
[docs]def dumbbell_topology(m1, m2):
"""
Return a dumbbell topology consisting of two star topologies
connected by a path.
More precisely, two star graphs K_{m1} form the left and right bells, and
are connected by a path P_{m2}.
The 2*m1+m2 nodes are numbered
- 0,...,m1-1 for the left barbell,
- m1,...,m1+m2-1 for the path,
- and m1+m2,...,2*m1+m2-1 for the right barbell.
The 3 subgraphs are joined via the edges (m1-1,m1) and (m1+m2-1,m1+m2).
If m2=0, this is merely two star topologies joined together.
Please notice that this dumbbell topology is different from the barbell
graph generated by networkx's barbell_graph function. That barbell graph
consists of two complete graphs connected by a path. This consists of two
stars whose roots are connected by a path. This dumbbell topology is
particularly useful for transport layer simulations.
All nodes and edges of this topology have an attribute *type* which can be
either *right bell*, *core* or *left_bell*
Parameters
----------
m1 : int
The number of nodes in each bell
m2 : int
The number of nodes in the path
Returns
-------
topology : A Topology object
"""
if type(m1) is not int or type(m2) is not int:
raise TypeError('m1 and m2 arguments must be of int type')
if m1 < 2:
raise ValueError("Invalid graph description, m1 should be >= 2")
if m2 < 1:
raise ValueError("Invalid graph description, m2 should be >= 1")
G = Topology(type='dumbbell')
G.name = "dumbbell_topology(%d,%d)" % (m1, m2)
# left bell
G.add_node(m1)
for v in range(m1):
G.add_node(v, type='left_bell')
G.add_edge(v, m1, type='left_bell')
# right bell
for v in range(m1):
G.add_node(v + m1 + m2, type='right_bell')
G.add_edge(v + m1 + m2, m1 + m2 - 1, type='right_bell')
# connecting path
for v in range(m1, m1 + m2 - 1):
G.node[v]['type'] = 'core'
G.add_edge(v, v + 1, type='core')
G.node[m1 + m2 - 1]['type'] = 'core'
return G