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Transcript
Routing, Flow, and Capacity Design in
Communication and Computer Networks
Chapter 6:
Location and Topological Design
Slides by
Yong Liu1, Deep Medhi2, and Michał Pióro3
1Polytechnic
University, New York, USA
2University of Missouri-Kansas City, USA
3Warsaw University of Technology, Poland & Lund University, Sweden
October 2007
1
Outline
 Topological Design Modeling
 location
 connectivity
 demand/capacity allocation
 Solution
 heuristic algorithms
2
Node Location Problem
 connect N areas through M
possible locations
 one access link per
location
 maximal connection per
location
 maximum number of ports
per router
 cost of open each location
 cost of connecting each
area to each location
 always connect to the
cheapest/closest station?
3
NLD: Formulation
4
Add Heuristic
 Local Search Algorithm
 Start with a random location
 all sources connect to that location
 Iteratively add new locations, one each time
 to reduce the opening and connection cost
 choose the candidate with largest reduction
 Stop if cost reduction is not possible
5
Add Heuristic: the algorithm
6
 Complexity: O(NM2),
N--number of areas, M--number of locations
Add Heuristic: example
 6 areas, 4 locations
 connectivity cost
2
1
3
6
4
7
5
Joint Node Location and Link
Connectivity
 connectivity cost
 from access nodes to core nodes
 between core nodes
 fully connected core
 two models
 one-level
all nodes same type, each site can be
possibly a core node site (same node
for access and core): IP routers with
different capacities
 overlay-underlay design
access node locations and core node
locations are different: IP/MPLS
IP
MPLS
8
One-level Formulation
9
Two-level Formulation
10
Illustration: Distance-based/
Skewed-Distance-based
11
Non-Fully Connected Core
 Non-fully connected in practice
 Avoid disconnecting network
 Delete core link heuristic
12
Topological Design
 traffic demand has big impact on node and
link location
 jointly design location/dimesnion/flow
given access/core locations, determine link
locations, flow and capacity allocation
 given access locations only, determine core
locations, link locations, flow and capacity
allocation

 traffic demand between access nodes, to
be realized; pure access nodes cannot
transit traffic; pure core nodes don’t
generate traffic
 cost
 link/node opening
 Capacity cost
13
access node
Core/transit node
Design with Budget Constraint:
optimal network problem
 access/core
locations given
 link cost
 capital cost
(installation) must
under budget

maintenance/opera
tional (capacity
dependent) cost to
be minimized
 enforce path
diversity?
14
Optimal Network Problem:
extended objective
 what if budget too tight?
 network cost = capital cost + maintenance cost
15
Optimal Network Problem:
Heuristic Algorithm
 start with all links installed
 iteratively remove links, one
each iteration
 saving from link removal: capital +
operational
 cost from link removal:
• traffic on the removed link have to
be rerouted:
local rerouting v.s. global rerouting
• capacity cost incurred on new paths
 Net gain of remove link e
• gain(e)=saving(e)-cost(e)
 Remove the link maximizing gain(e)
16
X
Core Nodes and Links Location
 both core nodes and links locations to be
determined
 new constraints
 if a node v not installed, all links attached to v
won’t be installed
 bound on core node degree
 Link-path formulation or node-link
formulation
17
Link-Path Formulation
 how to pre-set
paths without
knowing the
locations of
core nodes and
links?
 bad set of
candidate paths
might lead to
expensive or
infeasible
solutions
18
Link-Path Formulation (cont.d)
19
Node-Link Formulation
 distinguish access and transit links
 directed access links: between access and transit
nodes
 directed transit links: between transit nodes
 use source-based link-flow variable
20
REF: Node-Link Formulation II
21
Node-Link Formulation
22
Node-Link Formulation
23
Node-Link Formulation
24