cp3397 network design and security lecture 4 wan design - principles and practice
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CP3397 Network Design and SecurityLecture 4 WAN design - Principles and practice
WAN design
Wide area networks constructed from private circuits (leased lines) need careful design to optimise performance minimise costs provide adequate service allow redundancy for fault tolerance
Backbone and access networks
WANs can be split into two parts Backbone network linking main
centres Access networks linking endpoints to
nearest backbone node
Both aspects of the network need designDifferent rules apply to each type
Principles1. Good designs have many well-utilized components2. In voice network utilization should be high (to
reduce costs) - in a data network utilization should be low (to reduce delay)
3. Aim for 50% utilization on all links (to balance cost/delay)
4. Aim to have as few links as possible under 50% utilization
5. Use “natural traffic centres” - found from “weight” calculation
6. Balance need for shortest path, economy of scale from high speed links and utilization
7. Most design algorithms need repeated application to give best results
Some definitionsGraphsGraphs
A,B,C etc. are vertices(nodes)A,B,C etc. are vertices(nodes) (A,X), (X,Y) etc. are edges(A,X), (X,Y) etc. are edges P,Q,Z is a cycle (loop)P,Q,Z is a cycle (loop) Degree of a node is the number of edges at the nodeDegree of a node is the number of edges at the node
– Degree Y =3, degree C=1Degree Y =3, degree C=1
X
Y
Z
P Q
A
B
D
C
Trees
A tree is a connected simple graph with no cycles e.g.
XY
Z
P Q
A
B
D
C
Star
A tree is a star if only 1 node has degree >1
X
Y
Z
PQ
A
B
D
C
Chains
A chain is a tree with no nodes of degree >2
XY
Z
P Q
A
B
D
C
Weighted graphs
Each edge has a value (e.g. link speed, cost, etc.) Weight of the edge ei = w(ei)
To optimise a connected graph find the graph with the minimum weight
The Minimal Spanning Tree (MST)
Finding the MST
Two algorithms Prim and Kruskal Prim starts by selecting a node, adding the “least expensive edge” iterates until tree is built
Kruskal achieves the MST by starting with a graph and cutting out edges
Example MST
Use of MSTs
Small design problems - few nodesHighly reliable links with low “downtime” or network can tolerate unreliability
Nodes ‘v’ reliability As the number of nodes increases reliability decreases (exponentially!)
Shortest path trees
SPTs are when the path between each pair of nodes has the lowest weight Can be found using Dijkstra’s algorithm
See Cahn p67 and Kenyon p102
MSTs and SPTs will be different Prim and Dijkstra algorithms can be combined to give
MST or SPT using parameter alpha Ref: R. S. Cahn (1998) “Wide area network design”, Morgan
Kaufmann, ISBN 1-55860-458-8 and the Delite design tool, http://www.mkp.com/wand.htm and mirrored on the CP3397 homepage
Ref: T Kenyon (2002) “High-performance data network design” Digital Press, ISBN 1-55558-207-9
Access design
Each node on a backbone may have a number of local access pointsAccess networks route all traffic to the local backbone node.With n nodes there are nn-2 spanning trees!There are algorithms that reduce the possibilities - e.g. Esau-Williams, Sharma (Cahn Chapter 5)
Backbone design
Aim is to minimise the degree of the nodes (X) (i.e. number of connections at each) andminimise the number of hops (H) between all the nodesThese need balancing to produce a credible designFully-connected n-node mesh (H=1, X=n)Star (H=2, X=1 for all except central node)
Design algorithm
Mentor algorithm (one of many) relies on radius and weight to
determine backbone radius is proximity-based weight is traffic-related (in and out)
Calculates merit of a site based on distance from centre of network weight - i.e. traffic
Algorithm steps
1. Cluster sites within radius (Rparm) around those with largest merit
2. Select backbone centre (smallest weight x distance)
3. Build backbone tree4. Find the sequence of all pairs on the tree
starting with the outside5. Choose homes (sites between each pair)
Algorithm steps
6. Consider each pair once and add links if
utilization is too high otherwise traffic is sent via home node This adds links between non-adjacent
sites
Example
Detail diagrams
South East
Midlands
Input data
Coordinates of sitesCost of linksTraffic between sites in kbytesUser population at each siteParameters Rparm, wparm, slack
Network design
Parameters Rparm 0.4 Wparm 1.0 Slack 0.0 Utilization 0.5
Cost 757991
Alternative robust design
Parameters Rparm 0.4 Wparm
1.0 Slack 0.5 Utilization
0.5
Cost 766717
Detail diagrams
Midlands area detail
512K128K3x
128k
Summary
Design will depend on traffic, costs, andOther desirable parameters such as slack and utilizationDesign methods for Access and backbone are differentMany algorithms are availableReal networks will require careful cost minimisation