Energy Efficient Networking
Jennifer Rexford
Fall 2010 (TTh 1:30-2:50 in COS 302)
COS 561: Advanced Computer Networks
http://www.cs.princeton.edu/courses/archive/fall10/cos561/
IT Energy Consumption
• IT consumes a lot of energy
– Approximately 2.5% of worldwide energy use
– As much as the airline industry, and growing
– Expected to grow by 30% by 2014
• Data centers
– Electricity costs of $4.5B in the U.S. in 2006
– More $ on power and cooling than on hardware
• Networking
– One third of the total IT energy use
– Around 10-20% of data-center energy use
– Largest energy consumer is the access equipment
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Ways to Save Energy
• Energy proportionality
– Energy use should be proportional with load
– Yet, most equipment operates at least efficient regime
– http://research.google.com/pubs/pub33387.html
• Maximizing utilization
– Best energy savings is the equipment you never buy
– Use the available resources as effectively as possible
– … rather than buying and deploying more
• Selectively powering down
– Shut down equipment during periods of lower demand
– But, reliability concerns … and slow powering up
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Main Sources of Energy Use
data centers
consumer
devices
networking
equipment
What’s a networking researcher to do?
4
Network’s Role in Energy Efficiency
• Reduce energy in other sectors
– E.g., video-conferencing as alternative to travel
• Maximize efficiency of smart grid
– Real-time measurement and coordination
– Protect the smart grid from cyber attacks
• Reduce energy on end hosts
• Reduce energy of the network itself
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Networks
• High energy consumption
– Packet-level operations
– High-speed data-plane memory
• Not energy proportional
• Often over-provisioned
– Avoid queuing delay on the links
– Handle time-of-day traffic changes
– Handle a diverse mix of workloads
– Have enough capacity left after failures
• Bad at handling churn
200-400 W
Line cards draw
~ 100W
– Routing convergence on powering up/down equipment
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Research on Network Energy
• Measurement of router energy consumption
– Quantifying the energy of line card, switches, …
– Understanding relationship to features, load, etc.
• Selectively powering down capacity
– Turning off links, or tuning to lower capacity
 E.g., variable speed Ethernet, or bundled links
– Optimization problem to identify links to shut down
• Reducing disruptions when powering down
– Reducing capacity of a link rather than shutting down
– Techniques for reducing convergence delay
– Router grafting and virtual router migration
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Research on Reducing Host Energy
• In-network proxies
– End hosts cannot easily go into “low power” mode
– Due to “chatty” services that require periodic traffic
– Could have a proxy handle these functions for the host
• Virtual machine migration
– Migrate a virtual machine from one server to another
– Support fast transfer of virtual machine state
– Allow the VM to retain its address when it moves
• Better server load balancing
– Distribute client requests to data centers and servers
– Based on server capacity and electricity prices
– Using DNS, HTTP redirection, front-end load balancer… 8