Power-Aware Network Design

1. Power-Aware Network Design «Power Awareness in Network Design and Routing» J. Chabarek et al. «Energy-Minimized Design for IP Over WDM Networks» G. Shen, R. S. Tucker

2. Introduction • The Internet is expanding tremendously • Growth in the number of end users and connection speeds -> exponential increase in bandwidth demand • Increase in energy consumption • Cost of transmission and switching one of the major barriers • Energy consumption may become a barrier • 1% - 2% of total electricity consumption in US • A cut of 1% in the Internet energy consumption means about US$5 billion per year • Increase in power density • Thermal issues -> limitations of air cooling • Increase in operational costs • Increase greenhouse footprint • Save the Earth!!!

3. Power Aware Design Areas (I) • Three main areas for power aware design • System Design • Development in CMOS technology -> improvements are slowing down • Multi-Chassis Systems: separate physical components clustered forming a single logical router • Aggregate power consumption increases -> heat spread over a large physical area -> existing cooling techniques used • Alternative Systems: optical switches • Terabits of bandwidth at much lower power dissipation • Protocols • Investigated in wireless networks -> Opportunities in wire-line networks • Basic notion: put components to sleep if low traffic load • Routing protocols: routes calculated with power consumption constraints

4. Power Aware Design Areas (II) • Network Design • Deploy routers such that the aggregate power demand is minimized • Satisfying robustness and performance • Two approaches • Multiple router-level topologies satisfying capacity, robustness and power consumption • Limit power-hungry systems to a subset of routers • Selection of chassis and line cards in routers is a main issue to reduce power consumption • In IP over WDM networks • IP routers use more than 90% of total power • Lightpath bypass is used to reduce the number of IP router ports -> IP ports consume major energy in IP routers

5. Router Power Consumption • Router power consumption depends on • Type of router chassis • Type and number of line cards deployed in the chassis • Configuration and operating conditions • Size of packets • 100 bytes / 576 bytes / 1500 bytes • Size of forwarding table • 1000 entries / 32000 entries • Type of traffic • UDP • TCP • Employed protocols and techniques • OSPF • Netflow • Unicast Reverse Path Forwarding (uRPF) • Access Control List (ACL) • Active Queue Management - Random Early Detection (AQM – RED)

6. Router Power Consumption • Chassis and line card combinations • Chassis: Cisco GSR 12008 / Cisco 7507

7. Router Power Consumption • Chassis and line card combinations (cont.) • Base system is the most consuming • 7507 chassis + router processor -> 210 Watts • GSR chassis + router processor + switching fabric -> 430 Watts • It is best to minimize the number of chassis and maximize the number of line cards per chassis • Calculated power consumption of different cards

8. Router Power Consumption • Configuration and operating conditions • A 4-port Gigabit Ethernet line card and a OC-48 card in a GSR chassis is used • Deployed testbed:

9. Router Power Consumption • Configuration and operating conditions (cont.) • Constant bit rate UDP traffic and different packet sizes • 1500 bytes / 576 bytes / 100 bytes • Power consumption increases as packets get smaller!!!

10. Router Power Consumption • Configuration and operating conditions (cont.) • Constant bit rate UDP traffic, medium packets and different features • Large forwarding table / ACL / uRPF / OSPF • uRPF is the most consuming • Large forwarding table is less consuming!!

11. Router Power Consumption • Configuration and operating conditions (cont.) • Self-similar TCP traffic, 75% offered load and different features • Netflow / AQM - RED • Power consumption similar to UDP with large-sized packets

12. Router Power Consumption • Configuration and operating conditions (cont.) • Maximum variation in previous slides -> 20 Watts • Extrapolating a fully loaded chassis -> 150 - 200 Watts • Less significant than chassis/line card configuration • General Model: • PC -> power consumption of router • X is a vector defining chassis type, line cards, configuration and traffic profile • CC -> power consumption of a chassis type • N -> number of line cards • TP -> scaling factor (traffic utilization) • LCC -> cost of line card

13. Power Consumption Optimization • Main focus: allocation of line cards and chassis in nodes to minimize power consumption • Mixed-Integer resource allocation problem with multicommodity flow constraints • Inputs • Network with OSPF link weights • Traffic matrix • Line card and chassis options • Outputs • How each node should be provisioned • Multipath routing • Implemented with General Algebraic Modeling System (GAMS)

14. Power Consumption Optimization • Networks are taken from the Rocketfuel project • Inferred weights and link latencies • Link weights -> calculate approximate bandwidths of each link • Traffic matrixes generated with a gravity model • Three additional random graphs with 12 nodes and varying number of directed edges (Waxman method)

15. Power Consumption Optimization • Network design problem: deploy different chassis/line card configurations such that provisioning requirements are satisfied and power consumption in minimized • Traffic is scaled for each origin-destination pair -> linear scaling factor • Varies provisioning requirements • Traffic flows might be altered to put cards/chassis to sleep in low utilization • First scenario includes only GSR chassis and OC-48 line card • Only 10 line cards allowed per chassis • Scaling factor varies from 0.1 to 40

16. Power Consumption Optimization • Other experiments relaxing line cards per chassis, chassis type and card types (not in the paper) • Minimum power consumption -> chassis accommodating large numbers of line cards and line cards capacities that closely match demand

17. Power Consumption Optimization • Power savings • Compared to a non-power-aware network design (shortest path) • Using a specific chassis (GSR) and line cards (OC-48 or 0C-12) • OC-12 line cards achieve smaller savings -> more ingress/egress node ports • Cost of additional connectivity is zero as long as the number of ports does not require additional line cards

18. IP Over WDM Network • IP layer: • Core IP router aggregates data traffic from low-end access routers • IP router ports consume major energy (forwarding process) -> number of IP ports as measure of total power consumption • Optical layer • Optical switches interconnected with physical fiber links • May contain multiple fibers • Each fiber needs a pair of multiplexer/demultiplexer • Each wavelength require a pair of transponders -> full wavelength conversion is assumed • EDFA amplifiers are deployed on fiber links

19. IP Over WDM Network • Two implementation approaches • Lightpath non-bypass • All data carried by lightpaths is processed and forwarded by IP routers • All lightpaths incident to a node must be terminated • Lightpath bypass • IP traffic whose destination is not the intermediate node -> directly bypasses the intermediate router • Saves IP router ports

20. Energy Consumption Optimization for IP over WDM • Network design problem: design an energy-minimized IP over WDM network • Serving all the traffic demands • With a limited maximal number of wavelengths in each fiber • With a limited maximal number of IP router ports at each node • Inputs • Physical topology -> N nodes and E links • Traffic demand matrix • Number of wavelength channels per fiber and capacity of each wavelength • Maximal number of IP router ports at each node • Energy consumption of router ports, transponders and EDFAs

21. Energy Consumption Optimization for IP over WDM • The optimization problem is solved using a Mixed-Integer Linear Programming (MILP) model including • Energy consumption of IP routers, EDFAs and transponders • Layout of EDFAs • Ports for aggregating data from low-end routers • MILP model minimizes also the number of network components -> could be used for cost-minimized IP over WDM network • The computational complexity is high • O(N4) variables and O(N3) constraints • Heuristics are needed for fast solution

22. Energy Consumption Optimization for IP over WDM - Heuristics • Heuristics • Direct Bypass: directly establish virtual links (lightpaths) whose capacity is sufficient to accommodate all the traffic demands between each node pair • Routing of lightpaths -> shortest path routing • Simple • Could lead to low capacity utilization • Multi-hop bypass: traffic demands between different node pairs could share capacity on common lightpaths • Elongate lengths of some IP traffic flows • Fewer lightpaths -> fewer IP router ports

23. Energy Consumption Optimization for IP over WDM - Heuristics • Multi-hop bypass heuristic:

24. Energy Consumption Optimization for IP over WDM - Setup • Five study cases • Linear relaxation of the MILP model -> lower bound • MILP optimal design • Non-bypass -> upper bound • Direct bypass • Multi-hop bypass • Inputs • Traffic demand between each pair node: • Uniform distribution within a certain range centered at an identical average

25. Energy Consumption Optimization for IP over WDM – Test Networks • Test networks n6s8 NSFNET USNET

26. Energy Consumption Optimization for IP over WDM – Total Power Consumption n6s8 NSFNET Larger topology -> higher power consumption, heuristics closer to lower bound Non bypass -> upper bound LP relax. -> lower bound Linear relationship between total power consumption and total traffic demand intensity USNET

27. Energy Consumption Optimization for IP over WDM – Power Consumption Saving n6s8 NSFNET Larger topology -> higher savings, longer lightpaths bypassing more nodes -> fewer IP ports Multi-hop bypass heuristic performs better than direct bypass -> Small traffic flows are aggregated USNET

28. Energy Consumption Optimization for IP over WDM – Component Consumption n6s8 NSFNET

29. Energy Consumption Optimization for IP over WDM – Geographical Distribution n6s8 NSFNET All bypass design have a more uniform power distribution Solve problems associated with: Supplying large amounts of energy Removing associated heat

30. Energy Consumption Optimization for IP over WDM – Cost Analysis • The model could be used for minimizing cost • Changing the optimization weights from energy to cost • May NOT be valid if components with low energy consumption are the most expensive ones N6s8 network based on the MILP optimization model

31. Conclusions • Energy consumption may become a barrier for the Internet • Operational costs • Greenhouse footprint • Cooling issues • Supplying large amounts of energy • Power aware design could solve it • Power aware system design • Power aware protocols • Power aware network design • Power aware network design could achieve important savings • In IP over WDM networks, lightpath bypass could save power consumption

32. References • [CHA08] J. Chabarek et al., «Power Awareness in Network Design and Routing», Proc. Of IEEE INFOCOM, 2008 • [SHE09] G. Shen, R. S. Tucker, «Energy-Minimized Design for IP Over WDM Networks», Journal of Optical Communication Networks, June 2009.