energy aware
TRANSCRIPT
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Energy-aware Networks:
Reducing Power Consumption
by Switching Off
Network Elements
Luca Chiaraviglio
Marco Mellia
Fabio Neri
May 2008
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Motivations
Goals Solutions
Results
Technical issues Conclusions
Outline
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Introduction
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Introduction
Italian Debt for Kyoto delay: 440.000.000 euro .Italy must pay a daily fine of 4.111.000 (47,6 per second) for the failure to
achieve the objectives of Kyoto Protocol from 2008.
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Introduction
ICT alone is responsible of a percentage which vary widely
from 2% to 10% of the world power consumption.
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Reduce the energy consumption of a network
Can be achieved by Reducing power consumption of devices
Routers: reduce cpu/memory/asics power consumption
Links: design more efficient modulation, low power tx
Reduce power consumption of the whole network
Efficient DESIGN of the network
Our Goal
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a physical network topology built by routers and links, inwhich links have a known capacity
the knowledge of the average amount of traffic
exchanged by any source/destination node pair
the power consumption of each link and node,
Problem Formulation
Given
the set of routers and links that must be powered on so that
the total power consumption is minimized
flow conservation and maximum link utilization constraints.
Find
Subject to
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Problem Formulation
yiis a router
xi jis a link with capacityci j
tsdis the traffic fromstod
fsdi jis the traffic fromstodon
link fromi toj
is the overprovisioning
constraint
P is the power
The problem isNP-complete!
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Algorithms
Node Heuristics
Link Heuristics
Least Flow
Random
Least Flow
Least Link
Random
Simpleheuristics!!
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,
Algorithms - II
1 2
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Topology
,
Core
Aggregation
Edge
10
30
120
5
3
2
Num
Nodes
Links
degree
Sources - Destinations
Tsd=U[0.5,1.5] Cij=min(floor(fij/),cijmin)
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Simulation Results
,
0,00%
5,00%
10,00%
15,00%
20,00%
25,00%
30,00%
LEAST_FLOW -
LEAST_FLOW
LEAST_LINK -
LEAST_FLOW
RANDOM -
LEAST_FLOW
RANDOM -
RANDOM
LEAST_FLOW -
RANDOM
LEAST_LINK -
RANDOM
L
Node Heuristic - Link Heuristic
Heuristics Comparison
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Simulation Results - II
,
0,00%
2,00%
4,00%
6,00%
8,00%
10,00%
12,00%
14,00%
LEAST_FLOW -
LEAST_FLOW
LEAST_LINK -
LEAST_FLOW
RANDOM -
LEAST_FLOW
RANDOM -
RANDOM
LEAST_FLOW -
RANDOM
LEAST_LINK -
RANDOM
N
Node Heuristic - Link Heuristic
Heuristics Comparison (2)
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Simulation Results - III
,
5,00%
10,00%
15,00%
20,00%
25,00%
30,00%
50 55 60 65 70 75 80 85 90 95 100
L
Percentage of links switched off versus
LEAST_FLOW - LEAST_FLOW
LEAST_LINK - LEAST_FLOW
RANDOM - LEAST_FLOW
LEAST_FLOW - RANDOM
LEAST_LINK - RANDOMRANDOM - RANDOM
0 100
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Simulation Results - IV
,
0,00%
2,00%
4,00%
6,00%
8,00%
10,00%
12,00%
14,00%
50 55 60 65 70 75 80 85 90 95 100
N
Percentage of nodes switched off versus
LEAST_FLOW - LEAST_FLOW
LEAST_LINK - LEAST_FLOW
RANDOM - LEAST_FLOW
LEAST_FLOW - RANDOM
LEAST_LINK - RANDOMRANDOM - RANDOM
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Parameter Impact - I
,
0,00%
5,00%
10,00%
15,00%
20,00%
25,00%
30,00%
35,00%
40,00%
45,00%
50,00%
6 10 15 20 25 30
L
x
Percentage variation of links switched offversus different values of x
x core
3x edge
12x aggregation
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Parameter Impact - II
,
0,00%
2,00%
4,00%
6,00%
8,00%
10,00%
12,00%
6 10 15 20 25 30
N
x
Percentage variation of nodes switched offversus different values of x
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Impact of traffic variation
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Traffic Variation
,
0
0,2
0,4
0,6
0,8
1
1,2
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
E[traffic]
Time
Traffic Variation
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,
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
N
Time
Percentage Variation of Nodes Off
Traffic Variation
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,
0%
5%
10%
15%
20%
25%
30%
35%
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
L
Time
Percentage Variation of Links off
Traffic Variation
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Turning off network portions save energy
BUT
How to do this?
Device support
Standby mode? Idle mode?
Control plane impact
Centralized solution? Or distributed solution?
How to signal the device the power state?
How to control/reroute the traffic?
How to decide WHEN to enter idle mode?
Technical Issues
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Conclusions
- Minimization of the total power consumed by a network
- Connectivity and maximum link utilization contraints
- Simple Heuristics proposed for WAN scenario
- Possibility to turn off links and full nodes
Energy-aware
network design
-More efficient heuristics for nodes, e.g. minimize the number of
multiple paths
- Performance analysis on a real network
-Case study on operative networks
Next Steps