2.3. Graph RepresentationThe adjacency matrix is a useful graph representation for many analyt-ical calculations. However, when we need to store a network in a computer,we can save computer memory by offering the list of links in a Lx2 matrix,whose rows contain the starting and end point i and j of each link.Construct for the networks (a) and (b) in Figure 2.20: Figure 2.20Graph Representation(a) Undirected graph of 6 nodes and 7 links.(b) Directed graph of 6 nodes and 8 directed66links.(a) The corresponding adjacency matrices.(b) The corresponding link lists.(c) Determine the average clustering coefficient of the networkshown in Figure 2.20a.(d) If you switch the labels of nodes 5 and 6 in Figure 2.20a, how doesthat move change the adjacency matrix? And the link list?(e) What kind of information can you not infer from the link listrepresentation of the network that you can infer from the adja-cency matrix?(f) In the (a) network, how many paths (with possible repetition ofnodes and links) of length 3 exist starting from node 1 and end-ing at node 3? And in (b)?(g) With the help of a computer, count the number of cycles oflength 4 in both networks.

A graph can be represented in two ways: 1)adjacency matrix 2)adjacency list Adjacency Matrix is a 2D…

The adjacency matrix is a useful graph representation for many analyt- ical calculations. However, when we need to store a network in a computer, we can save computer memory by offering the list of links in a Lx2 matrix, whose rows contain the starting and end point i and j of each link. Construct for the networks (a) and (b) in Figure 2.20:

The adjacency matrix is a useful graph representation for many analyt- ical calculations. However, when we need to store a network in a computer, we can save computer memory by offering the list of links in a Lx2 matrix, whose rows contain the starting and end point i and j of each link. Construct for the networks (a) and (b) in Figure 2.20:

Computer Networking: A Top-Down Approach (7th Edition)

7th Edition

ISBN:9780133594140

Author:James Kurose, Keith Ross

Publisher:James Kurose, Keith Ross

Chapter1: Computer Networks And The Internet

Section: Chapter Questions

Problem R1RQ: What is the difference between a host and an end system? List several different types of end...

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Question

2.3. Graph Representation
The adjacency matrix is a useful graph representation for many analyt-
ical calculations. However, when we need to store a network in a computer,
we can save computer memory by offering the list of links in a Lx2 matrix,
whose rows contain the starting and end point i and j of each link.
Construct for the networks (a) and (b) in Figure 2.20:

Figure 2.20
Graph Representation
(a) Undirected graph of 6 nodes and 7 links.
(b) Directed graph of 6 nodes and 8 directed
6
6
links.
(a) The corresponding adjacency matrices.
(b) The corresponding link lists.
(c) Determine the average clustering coefficient of the network
shown in Figure 2.20a.
(d) If you switch the labels of nodes 5 and 6 in Figure 2.20a, how does
that move change the adjacency matrix? And the link list?
(e) What kind of information can you not infer from the link list
representation of the network that you can infer from the adja-
cency matrix?
(f) In the (a) network, how many paths (with possible repetition of
nodes and links) of length 3 exist starting from node 1 and end-
ing at node 3? And in (b)?
(g) With the help of a computer, count the number of cycles of
length 4 in both networks.

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