Course: Communication Networks Optimization (UPC)

1. Green Optical Networks
with Signal Quality
Guarantee
João Rosa
Maria Stylianou
Zafar Gilani
CANO - Communication Networks Optimization
2012

2. Outline
● Introduction
● Problem description
● ILP model
● Heuristic
● Solution comparison
● Conclusions
● Possible future work

3. 1
Introduction
● Optimization is directly related to efficiency.
● Problem with power consumed by
communication networks.
○ Optical networks partially resolve the problem by
being better at consumption.
○ But need to consider improvements from other
related issues (such as efficient routing).

4. 2
Problem description
● Concern about rising energy consumption
and therefore costs of communication
networks.
● Energy efficient strategies are required for
network design provisioning that supports
both static and dynamic routing.

5. 3
Problem description
● In this project we try to minimize:
○ Number of links on a path.
○ Energy consumption of a path.
● We accomplish this by making improvements in
dynamic routing by consideration of:
○ Most economical links
○ Shortest path
○ Lowest power consumption
○ Reusing links or partial paths

6. 4
Environment Example
X1 OA OA OA X2
...
Tx Tx
X1,X2: Nodes
Tx: Transponder
OA OA
w1...wn OA: Optical Amplifier
w1...wn: Wavelengths

7. 5
Our Contribution
● ILP Model - CPLEX
● Heuristic Algorithm (Fasty)
● Comparison

8. 6
ILP model
Sets Variables
● N: Set of Nodes ● X[n]: 1 if node n is
● L: Set of Links used
● P: Set of Paths ● E[e]: 1 if link e is used
● W: Set of Wavelengths ● Xs[p,w]: 1 if
wavelength w for path
Constants p is used
● oe: #Optical Amplifiers (OA) ● y[e,w]: 1 if link e and
wavelength w is used
● eoa:Energy for 1 OA
● h[p]: # hops for each
● en: Energy for 1 node path p
● ew: Energy for 1 wavelength

9. 7
ILP model
● Objective function
Cumulative Cumulative Cumulative energy
energy of links energy of consumed by
used. nodes used. wavelengths used,
hops traversed and
nodes used over path
p for demand d.

10. 8
ILP model
For each demand, only one
● Constraints: wavelength can be used in
all paths

11. 9
ILP model
● Constraints:
A wavelength in a path
can be used only if the
same wavelength is
used in the link

12. 10
ILP model
● Constraints:
For each link e, ensure that
the number of wavelengths
used does not exceed the
maximum number of
wavelengths allowed

13. 11
ILP model
● Constraints:
Number of links used by a
node is less or equal to
number of links of a node

14. 12
Heuristic (Fasty)
● Own Implementation --> Works like a charm ;)
○ Code in C
○ Argument: same data file from CPLEX
● Goal: Satisfy all demands with the minimum power.
○ Minimum Power --> minimum links, nodes,
wavelengths used
● IDEA: Choose randomly a demand
○ Find all possible paths
○ Keep the path with the least power consumption
added

15. 13
Heuristic (Fasty)
Greedy Approach for choosing the "right" path
Demand #1 --> satisfied by 1-2-3-4 using λ1
Demand #2 --> satisfied by ?
λ1 λ2
1 2 1 2
λ1 λ1
λ1 λ1 λ2
λ1
4 3 4 3
λ1 λ2

16. 14
Solution comparison
● Execution time
● Optimal solution comparison
● Additional power consumption

17. 15
Execution time

18. 16
Optimal solution comparison
Limited
increase

19. 17
Additional power consumption
Heuristic with 8
demands.
No additional
power
consumption for
D5 after
satisfying D2.
Similar case for
D3, D0, D6 and
D4.

20. 18
Conclusions
● CPLEX is much slower than the Fasty
heuristic algorithm.
● Power increases as the demands increase
but only to a certain limit, as used links are
reused.
● For a given network graph, the heuristic
satisfies one demand after the other in such
a way as to reduce the cost in terms of
power consumed and path length.
○ Effective decrease in power used
○ .. with each new demand.

21. 19
Possible future work
● Test with larger tables/sets:
○ Demand-path set.
○ Path-link set.
● Test on multiple network graphs.
○ Different topologies.
○ Various routes.

22. Green Optical Networks
with Signal Quality
Guarantee
João Rosa
Maria Stylianou
Zafar Gilani
CANO - Communication Networks Optimization
2012