Civil Engineering Reference
In-Depth Information
17.3.2 Hierarchical model of infrastructure networks
Building a hierarchy that represents network communities at different
levels is the core idea behind the proposed approach. This is carried out by
a process of successive clustering of the network. Therefore, a recursive
implementation of clustering is necessary to construct a hierarchy. More-
over, variations in parameters may be necessary from level to level in order
to achieve different levels of detail and cluster sizes.
A clustering C
{ C 1 , . . . , C k } of a graph G is a partition of the node-set
V into non-empty (disjoint) subsets C i such that V is given by the union of
them. The set E ( C i , C j ) represents the set of edges with origin in cluster C i
and destination in cluster C j ; E ( C i ) is the short notation for E ( C i , C i ). Then,
E ( C ) is the set of intra-cluster edges E ( C ), thus E / E ( C ) (node-set without),
is the set of inter-cluster edges (Brandes and Erlebach, 2005). A clustering
is a refi nement of other if it is a partitioning of higher resolution, or a
coarsening in the opposite case. Cases where the number of clusters k is
equal to 1 or the number of nodes n are referred to as a trivial clusterings.
A chain of clusterings is called a hierarchy. Multi-level network clustering
provides structured organization of a system, which enhances knowledge
of network properties.
Aiming to provide a model for a highly complex system, it is proposed
that networks are partitioned recursively based on pertinent criteria (Gómez
et al. , 2011a). Each level of recursion (i.e., each different partitioning of the
network) denotes a level of abstraction. The hierarchical clustering leads to
a system representation in the form of a tree, also called a dendrogram
(from Greek dendron 'tree' and gramma 'drawing'). The concept of hierar-
chical representation of a system has been widely discussed for hard (e.g.,
infrastructure) and soft (e.g., sociological) systems (Blockley and Godfrey,
2000; Scott 2000).
=
￿
Fictitious nodes: Clusters at all levels defi ne fi ctitious nodes. Let V ( lv ) be
the i th node at the hierarchical level lv . Then, at the top of the hierarchy
(i.e., lv
1), the network is interpreted as a single unit (i.e., one fi ctitious
node), which consists of all actual nodes v i and all links between them:
V (1)
=
{ v 1 , v 2 , . . . , v n , E }, where E is the set of links of the graph G ( V , E ).
In the second level ( lv
=
2), the network is described by d fi ctitious
nodes: V (2) , V (2) , . . . , V (2) , with V (2) , V (2) , . . . , V (2) being a subset of V 1 (1) .
Notice that the n actual nodes, contained in the fi ctitious node V (1) at
the fi rst level, are distributed among the d fi ctitious nodes at the second
level.
=
￿
Fictitious links: A fi ctitious link E i ( lv ) , which connects V ( lv ) and V ( lv ) ,
describes how clusters at a hierarchical level lv are connected to each
other, and is constructed as the parallel arrangement of all actual links
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