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DENS: Data Center Energy-Efficient Network-Aware Scheduling

Dec 20, 2010. DENS: Data Center Energy-Efficient Network-Aware Scheduling. Dzmitry Kliazovich University of Luxembourg Pascal Bouvry University of Luxembourg Samee Ullah Khan North Dakota State University. Why energy is important?. Increased computing demand

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DENS: Data Center Energy-Efficient Network-Aware Scheduling

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  1. Dec 20, 2010 DENS: Data Center Energy-EfficientNetwork-Aware Scheduling Dzmitry KliazovichUniversity of Luxembourg Pascal BouvryUniversity of Luxembourg Samee Ullah Khan North Dakota State University

  2. Why energy is important? • Increased computing demand • Data centers are rapidly growing • Consume 10 to 100 times more energy per square foot than a typical office building • Energy cost dynamics • Energy accounts for 10% of data center operational expenses (OPEX) and can rise to 50% in the next few years • Accompanying cooling system costs $2-$5 million per year Pascal Bouvry (pascal.bouvry@uni.lu)

  3. Distribution of data center energy consumption Pascal Bouvry (pascal.bouvry@uni.lu)

  4. Data center architectures • Three-tier data center architecture • Most Widely Used Nowadays • Access, Aggregation, and Core layers • Scales to over 10,000 servers Pascal Bouvry (pascal.bouvry@uni.lu)

  5. Data center components memory modules, disks, I/O resources CPU Idle server consumes about 66% of the peak load for all CPU frequencies • Servers’ Energy Model Pascal Bouvry (pascal.bouvry@uni.lu)

  6. Data center components • Switches • Most common Top-of-Rack (ToR) switches typically operate at Layer-2 interconnecting gigabit links in the access network • Aggregation and core networks host Layer-3 switches operating at 10 GE (or 100 GE) • Links • Transceivers’ power consumption depends on the quality of signal transmission in cables and is proportional to their cost • 1 GE links consume 0.4W for 100 meter transmissions over twisted pair • 10 GE links consume 1W for 300 meter transmission over optical fiber • Supported power management modes • DVFS, DNS, or both Pascal Bouvry (pascal.bouvry@uni.lu)

  7. Simulator components Chassis ~ 36% Linecards ~ 53% Port transceivers ~ 11% • Switches’ Energy Model Pascal Bouvry (pascal.bouvry@uni.lu)

  8. DENS methodology Data Center Architecture • DENS achieves balance between • Energy consumed by the data center • Individual job performances • Job QoS requirements • Data center traffic demands • DENS is architecture specific Pascal Bouvry (pascal.bouvry@uni.lu)

  9. DENS methodology Avoid Overloading Penalize Under-loaded Servers Favor High Server Utilization Computing server selection Pascal Bouvry (pascal.bouvry@uni.lu)

  10. DENS methodology Favor Low Congestion Levels Penalize Congested Queues Computing server selection Pascal Bouvry (pascal.bouvry@uni.lu)

  11. DENS methodology Maximize Server Load, Minimizing Network Congestion Computing server selection Pascal Bouvry (pascal.bouvry@uni.lu)

  12. Performance Evaluation • GreenCloud simulator is developed • Three-tier data center topology • 1536 nodes, 32 racks, 4 core and 8 aggregation switches Pascal Bouvry (pascal.bouvry@uni.lu)

  13. Performance Evaluation Green scheduler Redistributing Computing Load DENS scheduler Round-robin scheduler Server workload distribution Pascal Bouvry (pascal.bouvry@uni.lu)

  14. Performance Evaluation Network congestion Green scheduler Redistributing Load to Satisfy QoS DENS scheduler Round-robin scheduler Network workload distribution Pascal Bouvry (pascal.bouvry@uni.lu)

  15. Performance Evaluation Network congestion Green scheduler Green scheduler DENS scheduler DENS scheduler Top-of-Rack (ToR) switch load Pascal Bouvry (pascal.bouvry@uni.lu)

  16. Performance Evaluation QoS Energy Data center energy consumption Pascal Bouvry (pascal.bouvry@uni.lu)

  17. Conclusions GreenCloud • We acknowledge • Funding form Luxembourg FNR in the framework of GreenIT project • Research fellowship provided by the European Research Consortium for Informatics and Mathematics (ERCIM) • Related publications • "GreenCloud: A Packet-level Simulator of Energy-aware Cloud Computing Data Centers," in Journal of Supercomputing, special issue on Green Networks, 2011. • “GreenCloud: A Packet-level Simulator of Energy-aware Cloud Computing Data Centers,” IEEE Global Communications Conference (GLOBECOM), Miami, FL, USA, December 2010. Pascal Bouvry (pascal.bouvry@uni.lu)

  18. Thank you! Pascal Bouvry (pascal.bouvry@uni.lu)

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