ENERGY AWARE ROUTINGRuss Whiterussw@riw.us

Motivation• Optimal network performance

• Optimal resource use• Drive the load adaptive principles of EnergyWise into the network

Load Adaptive

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EDGE NETWORK

Motivation• The initial round of energy savings is taking place at the edge

• But what about the core?

•Network elements and links are expensive to run (power wise)•The problems here are more complex to resolve•But the savings could still be significant

Highest Cost

Intermediate Cost

Lowest Cost

Motivation• What are the power savings possible by reducing usage in the core?

• These numbers from a Cisco 12000 give us an idea of the scope and level

Power Management for Networks to Reduce Energy Consumption, David Wetherall

Motivation• Energy cost is a factor of capacity, not use

• Matching capacity closely to demand saves energy• In other words, adapting

the network capacity to the network load E

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Maximum Throughput (Mb/sec)

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Motivation• The techniques presented here can reduce energy usage by about 20% in a typical campus

• $350 per year per network device• Conservative estimate• But our competitors

agree with us…1

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Network is designed for this level of traffic

Load Adaptation could save these resources

Existing Approaches MANET• Minimize per packet costs• Generally used in

MANET networks• Use nodes based on

battery power• Why isn’t this useful for wired networks? Avoid this node

Prefer these nodes

Existing Approaches MANET• Different network conditions....

• MANET devices are battery powered• Wired devices are “plugged in”

• Lead to different goals• MANET

• Extend battery life• Per node power usage is important• Spread usage among many nodes as much as possible

• Wired• Reduce overall network usage

Load Adaptive Control Plane• When does a router stop

switching traffic?• In a modern network design –never!• Load sharing means most links are

used all the time• When could a router be placed

into sleep mode?• In a modern network design –never!

• The goal of the load adaptive control plane is to minimize the network topology• Dynamically• Based on business requirements

specified by the user• Based on dynamic load information

Load Sharing

Load Adaptive Control Plane• Reduce the topology to the minimal

required for the offered/expected load• Expected load based on user built

profiles• Time of day, resiliency requirements,

etc.• Offered load could be based on real

time traffic measurements• The control plane can determine the

minimal topology required• Routing, such as EIGRP, OSPF, etc.• Switching, such as TRILL, Spanning

Tree, etc.• The control plane does not “put

devices to sleep”• Simply builds the opportunities for

devices to use built in energy efficient modes

Minimal Topology

Load Adaptive Control PlaneMinimum Topology Secondary

TopologyFull Topology Notes

Fully Enabled Fully Enabled Fully Enabled • No recovery time• No reduction in bandwidth• Survives two failures

Fully Enabled Fully Enabled Low Energy Use • Minimal recovery time (<1 sec)• Small reduction in bandwidth• Survives single failure

Fully Enabled Low Energy Use Minimum Energy Use (“Off”)

• Moderate recovery time (1-3 sec)• Moderate reduction in bandwidth• Failure requires recovery

Low Energy Use Minimum Energy Use (“Off”)

Minimum Energy Use (“Off))

• Long recovery time (minutes)• Minimum bandwidth available• Failure requires recovery

Weekend network posture

“After Hours” network posture

Normal Network Posture

Energy Managed Networks• Challenges

• How do we build these “energy states?”• How do we build these “network topologies?”• How do we make all of this work together?

Building Energy States• Power levels defined through standards process• H is High• R is Reduced• F is Frugal• These are just examples

• Power states correspond to ideal network states

Edge Devices

Aggregation

Core

Normal Posture F R H

Recovery Time 0 seconds

Off Hours Posture F F R

Recovery Time < 1 second

Weekend Posture F F R

Recovery Time < 2 minutes

Building Energy States• The network manager sets various “state triggers”

• Done through network management• For instance, time of day, etc.

• When a trigger engages• The network management station sets the devices within each

“zone” to the appropriate “ideal state”• The control plane then works to move the network into the

ideal state• Examines actual network usage, etc.

Building Energy Topologies• The process of moving a network into a desired state

relies on being able to find reduced energy network topologies• To move the network into a given state, the devices in a given

topology are moved into the appropriate state• Three mechanisms

• Traffic Engineering• Routing Modifications• Disjoint Topologies

Building Energy Topologies TE• Use traffic engineering to push traffic onto a subset of links in the network• Openflow or MPLS/TE

• Links and devices not used can be placed into sleep mode

Building Energy Topologies RP• Modify the existing routing protocols to find a “minimal set”

of the topology• The amount of redundancy, bandwidth, and other factors

can be controlled dynamically

Building Energy Topologies Disjoint• This is a relatively new idea in the network world

• Use an algorithm to find two topologies with non-overlapping links within the network

• Mark each topology so the routers treat each one as a logical network in some way

• Route over each topology independently• Still very “researchy”

• Some algorithms in this space wouldn’t work well for our purposes• Something to keep an eye on and think about, rather than take

action on “right now”

Bringing Devices Back• Once a device is asleep, how do we bring it back up?• Two general mechanisms

• Out of band signaling• SNMP, Openflow with an “alive” RP, etc

• In band signaling• Wake on LAN capability built into the box

• Either way, this piece needs hardware modifications• Real functionality in this space won’t exist until vendors are

convinced there enough cost/benefit ratio to justify the hardware changes

Summary• There are significant savings possible

• Savings at the edge swamps the network savings, however• It’s going to take lots of work to get to the savings in the core

• Network management controls the ideal state• Signals the control plane it’s okay to drop to a lower power state• Signals the control plane when it should move to a higher power

state• The control plane controls the actual state

• Within the parameters given by the ideal state• A “range of states” may be possible, as well