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

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!!!

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

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

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)

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

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

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:

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!!!

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!!

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

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

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)

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)

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

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

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

IP Over WDM Network IP layer: Optical 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

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

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

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

Energy Consumption Optimization for IP over WDM - 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

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

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

Energy Consumption Optimization for IP over WDM – Test Networks NSFNET USNET

Energy Consumption Optimization for IP over WDM – Total Power Consumption 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

Energy Consumption Optimization for IP over WDM – Power Consumption Saving 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

Energy Consumption Optimization for IP over WDM – Component Consumption NSFNET

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

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

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

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.