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![Page 1: Data Structures & Algorithms Graphs Richard Newman based on book by R. Sedgewick and slides by S. Sahni.](https://reader034.fdocuments.net/reader034/viewer/2022051301/5a4d1add7f8b9ab0599757ab/html5/thumbnails/1.jpg)
Data Structures & Algorithms
Graphs
Richard Newmanbased on book by R. Sedgewick
and slides by S. Sahni
![Page 2: Data Structures & Algorithms Graphs Richard Newman based on book by R. Sedgewick and slides by S. Sahni.](https://reader034.fdocuments.net/reader034/viewer/2022051301/5a4d1add7f8b9ab0599757ab/html5/thumbnails/2.jpg)
Definitions
• G = (V,E)• V is the vertex set• Vertices are also called nodes• E is the edge set• Each edge connects two different
vertices. • Edges are also called arcs
![Page 3: Data Structures & Algorithms Graphs Richard Newman based on book by R. Sedgewick and slides by S. Sahni.](https://reader034.fdocuments.net/reader034/viewer/2022051301/5a4d1add7f8b9ab0599757ab/html5/thumbnails/3.jpg)
Definitions
• Directed edge has an orientation (u,v)
• Undirected edge has no orientation {u,v}
• Undirected graph => no oriented edge
• Directed graph (a.k.a. digraph) => every edge has an orientation
u v
u v
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(Undirected) Graph
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Directed Graph
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Application: Communication NW
Vertex = city, edge = communication link
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Driving Distance/Time Map
Vertex = cityedge weight = driving distance/time
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Street Map2
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Some streets are one way.
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Complete Undirected Graph
Has all possible edges.
n = 1 n = 2 n = 3 n = 4
![Page 10: Data Structures & Algorithms Graphs Richard Newman based on book by R. Sedgewick and slides by S. Sahni.](https://reader034.fdocuments.net/reader034/viewer/2022051301/5a4d1add7f8b9ab0599757ab/html5/thumbnails/10.jpg)
Number Of Edges—Undirected Graph• Each edge is of the form (u,v), u != v• Number of such pairs in an n = |V|
vertex graph is n(n-1)• Since edge (u,v) is the same as edge
(v,u), the number of edges in a complete undirected graph is n(n-1)/2
• Number of edges in an undirected graph is |E| <= n(n-1)/2
![Page 11: Data Structures & Algorithms Graphs Richard Newman based on book by R. Sedgewick and slides by S. Sahni.](https://reader034.fdocuments.net/reader034/viewer/2022051301/5a4d1add7f8b9ab0599757ab/html5/thumbnails/11.jpg)
Number Of Edges—Directed Graph• Each edge is of the form (u,v), u != v• Number of such pairs in an n = |V|
vertex graph is n(n-1)• Since edge (u,v) is NOT the same as
edge (v,u), the number of edges in a complete directed graph is n(n-1)
• Number of edges in a directed graph is |E| <= n(n-1)
![Page 12: Data Structures & Algorithms Graphs Richard Newman based on book by R. Sedgewick and slides by S. Sahni.](https://reader034.fdocuments.net/reader034/viewer/2022051301/5a4d1add7f8b9ab0599757ab/html5/thumbnails/12.jpg)
Vertex Degree
Number of edges incident to vertex.degree(2) = 2, degree(5) = 3, degree(3) = 1
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Sum Of Vertex Degrees
Sum of degrees = 2e (e is number of edges)
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In-Degree Of A Vertex
in-degree is number of incoming edgesindegree(2) = 1, indegree(8) = 0
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Out-Degree Of A Vertex
out-degree is number of outbound edgesoutdegree(2) = 1, outdegree(8) = 2
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Sum Of In- And Out-Degrees• each edge contributes 1 to the in-
degree of some vertex and 1 to the out-degree of some other vertex
• sum of in-degrees = sum of out-degrees = e,
• where e = |E| is the number of edges in the digraph
![Page 17: Data Structures & Algorithms Graphs Richard Newman based on book by R. Sedgewick and slides by S. Sahni.](https://reader034.fdocuments.net/reader034/viewer/2022051301/5a4d1add7f8b9ab0599757ab/html5/thumbnails/17.jpg)
Sample Graph Problems• Path problems• Connectedness problems• Spanning tree problems• Flow problems• Coloring problems
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Path FindingPath between 1 and 8
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Path length is 20
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Path FindingAnother path between 1 and 8
Path length is 28
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Path FindingNo path between 1 and 10
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Connected Graph• Undirected graph• There is a path between every pair of
vertices
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Example of Not Connected
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Example of Connected
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Connected Component• A maximal subgraph that is
connected• Cannot add vertices and edges from
original graph and retain connectedness
• A connected graph has exactly 1 component
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Connected Components
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Communication Network
Each edge is a link that can be constructed (i.e., a feasible link)
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Communication Network Problems• Is the network connected?• Can we communicate between every
pair of cities?• Find the components• Want to construct smallest number of
feasible links so that resulting network is connected
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Cycles And Connectedness2
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Removal of an edge that is on a cycle does not affect connectedness.
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Cycles And Connectedness2
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Connected subgraph with all vertices and minimum number of edges has no cycles
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Tree
• Connected graph that has no cycles• n vertex connected graph with n-1
edges
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Spanning Tree
• Subgraph that includes all vertices of the original graph
• Subgraph is a tree• If original graph has n vertices, the
spanning tree has n vertices and n-1 edges
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Minimum Cost Spanning Tree
Tree cost is sum of edge weights/costs
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A Spanning Tree
Spanning tree cost = 51
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Minimum Cost Spanning Tree
Spanning tree cost = 41.
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A Wireless Broadcast Tree
Source = 1, weights = needed power.Cost = 4 + 8 + 5 + 6 + 7 + 8 + 3 = 41
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Graph Representation• Adjacency Matrix• Adjacency Lists
• Linked Adjacency Lists• Array Adjacency Lists
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Adjacency Matrix
• Binary (0/1) n x n matrix, • where n = # of vertices• A(i,j) = 1 iff (i,j) is an edge
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0 1 0 1 01 0 0 0 10 0 0 0 11 0 0 0 10 1 1 1 0
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Adjacency Matrix Properties
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• Diagonal entries are zero• Adjacency matrix of an undirected
graph is symmetric• A(i,j) = A(j,i) for all i and j
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Adjacency Matrix (Digraph)
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0 0 0 1 0
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0 0 0 0 0
0 0 0 0 1
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•Diagonal entries are zero
•Adjacency matrix of a digraph need not be symmetric.
![Page 40: Data Structures & Algorithms Graphs Richard Newman based on book by R. Sedgewick and slides by S. Sahni.](https://reader034.fdocuments.net/reader034/viewer/2022051301/5a4d1add7f8b9ab0599757ab/html5/thumbnails/40.jpg)
Adjacency Matrix• n2 bits of space• For an undirected graph, may store
only lower or upper triangle (exclude diagonal).
• Space? (n-1)n/2 bits• Time to find vertex degree and/or
vertices adjacent to a given vertex? O(n)
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Adjacency Lists
Adjacency list for vertex i is a linear list of vertices adjacent from vertex i
Graph is an array of n adjacency lists
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aList[1] = (2,4)
aList[2] = (1,5)
aList[3] = (5)
aList[4] = (5,1)
aList[5] = (2,4,3)
![Page 42: Data Structures & Algorithms Graphs Richard Newman based on book by R. Sedgewick and slides by S. Sahni.](https://reader034.fdocuments.net/reader034/viewer/2022051301/5a4d1add7f8b9ab0599757ab/html5/thumbnails/42.jpg)
Linked Adjacency Lists
Each adjacency list is a chain.
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aList[1]
aList[5]
[2][3][4]
2 41 555 12 4 3
Array Length = n# of chain nodes = 2e (undirected graph)# of chain nodes = e (digraph)
![Page 43: Data Structures & Algorithms Graphs Richard Newman based on book by R. Sedgewick and slides by S. Sahni.](https://reader034.fdocuments.net/reader034/viewer/2022051301/5a4d1add7f8b9ab0599757ab/html5/thumbnails/43.jpg)
Array Adjacency Lists
Each adjacency list is an array list
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aList[1]
aList[5]
[2][3][4]
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1 5
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Array Length = n# of list elements = 2e (undirected graph)# of list elements = e (digraph)
![Page 44: Data Structures & Algorithms Graphs Richard Newman based on book by R. Sedgewick and slides by S. Sahni.](https://reader034.fdocuments.net/reader034/viewer/2022051301/5a4d1add7f8b9ab0599757ab/html5/thumbnails/44.jpg)
Weighted Graphs• Cost adjacency matrix• C(i,j) = cost of edge (i,j)• Adjacency lists => each list element
is a pair (adjacent vertex, edge weight)
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Summary• Graph definitions, properties• Graph representations