Book contents
- Frontmatter
- Contents
- Preface
- Acknowledgments
- 1 Optical networking technology
- 2 Design issues
- 3 Restoration approaches
- 4 p-cycle protection
- 5 Network operation
- 6 Managing large networks
- 7 Subgraph-based protection strategy
- 8 Managing multiple link failures
- 9 Traffic grooming in WDM networks
- 10 Gains of traffic grooming
- 11 Capacity fairness in grooming
- 12 Survivable traffic grooming
- 13 Static survivable grooming network design
- 14 Trunk-switched networks
- 15 Blocking in TSN
- 16 Validation of the TSN model
- 17 Performance of dynamic routing in WDM grooming networks
- 18 IP over WDM traffic grooming
- 19 Light trail architecture for grooming
- Appendix 1 Optical network components
- Appendix 2 Network design
- Appendix 3 Graph model for network
- Appendix 4 Graph algorithms
- Appendix 5 Routing algorithm
- Appendix 6 Network topology design
- References
- Index
Appendix 3 - Graph model for network
Published online by Cambridge University Press: 18 December 2009
- Frontmatter
- Contents
- Preface
- Acknowledgments
- 1 Optical networking technology
- 2 Design issues
- 3 Restoration approaches
- 4 p-cycle protection
- 5 Network operation
- 6 Managing large networks
- 7 Subgraph-based protection strategy
- 8 Managing multiple link failures
- 9 Traffic grooming in WDM networks
- 10 Gains of traffic grooming
- 11 Capacity fairness in grooming
- 12 Survivable traffic grooming
- 13 Static survivable grooming network design
- 14 Trunk-switched networks
- 15 Blocking in TSN
- 16 Validation of the TSN model
- 17 Performance of dynamic routing in WDM grooming networks
- 18 IP over WDM traffic grooming
- 19 Light trail architecture for grooming
- Appendix 1 Optical network components
- Appendix 2 Network design
- Appendix 3 Graph model for network
- Appendix 4 Graph algorithms
- Appendix 5 Routing algorithm
- Appendix 6 Network topology design
- References
- Index
Summary
A network is represented by a graph G = (V, E), where V is a finite set of elements called nodes or vertices, and E is a set of unordered pairs of nodes called edges or arcs. This is an undirected graph. A directed graph is also defined similarly except that the arcs or edges are ordered pairs. For both directed and undirected graphs, an arc or an edge from a node i to a node j is represented using the notation (i, j). Examples of five-node directed and undirected graphs are shown in Fig. A3.1. In an undirected graph, an edge (i, j) can carry data traffic in both directions (i.e. from node i to node j and from node j to node i), whereas in a directed graph, the traffic is only carried from node i to node j.
Graph representations. A graph is stored either as an adjacency matrix or an incidence matrix, as shown in Fig. A3.2. For a graph with N nodes, an N × N 0−1 matrix stores the link information in the adjacency matrix. The element (i, j) is a 1 if node i has a link to node j. An incidence matrix, on the other hand, is an N × M matrix where M is the number of links numbered from 0 to M - 1. The element (i, j) stores the information on whether link j is incident on node i or not. Thus, the incidence matrix carries information about exactly what links are incident on a node.
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- Survivability and Traffic Grooming in WDM Optical Networks , pp. 390 - 392Publisher: Cambridge University PressPrint publication year: 2006