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ElasticTree : Saving Energy in Data Center Networks

ElasticTree : Saving Energy in Data Center Networks. Very offended by KALYAN MANDA LEI XIA. Facts about Network Elements. Network Elements only consume 5% of Total Power and not 10-20% as stated in your paper.(hmmm……..)

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ElasticTree : Saving Energy in Data Center Networks

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  1. ElasticTree: Saving Energy in Data Center Networks Very offended by KALYAN MANDA LEI XIA

  2. Facts about Network Elements • Network Elements only consume 5% of Total Power and not 10-20% as stated in your paper.(hmmm……..) • ElasticTree can save upto 40% of network energy, i.e. we have saved 1billion kWh.(best case scenario) • This is achieved by deciding on trade-off between Performance and Energy Consumption.

  3. Some Maths to calculate the Profit Ok, so we have just saved: = 1 *10^9 *.088(price/kWh) = $88000000. Number of servers in Datacenters in 2007: = 11.8Million.(http://royal.pingdom.com/2008/07/25/us-data-centers-consuming-as-much-power-as-5-million-houses/) Approx. number of Datacenters: = 11.8*10^6/10000(a very generous assumption) = 1180

  4. Profit/Datacenter • Profit/Datacenter = 88000000 / 1180 = $74576.27/year HURRAY!!!

  5. Wait a Second…. • I will have to hire a Network Admin to configure ElasticTree to satisfy the needs for performance and Fault tolerance. (source - paper) • And since my datacenter will be running 24/7 will have to hire 3 network admins- one per shift.(ideally 6- other 3 as backup) • And since I am a miser I will be paying them only $60000 pa. • So my total investment = 3 * 60000 = $180000/ year • So my Total Profit = 74576.27 – 180000 = $-105423.73

  6. My Achievements • I have degraded the performance of my datacenter by selecting on a trade-off between energy and performance to save 40% network energy…assuming the best case scenario. • I have made a profit of $-105423.73 • And, I got myself fired…..

  7. Applications of ElasticTree • Only to datacenters with Fat tree topology at present. • Cannot be applied to a 2N Tree topology. • Future interest, to explore the applicabilty to other topologies such as HyperCubes and Butterfly topology.

  8. Common guys…… • You based all of your conclusions by performing tests on a k = 4,6 Fat Tree and with a maximum of 54 hosts. • How hard it could be to simulate other topologies, considering the fact that you have not simulated on a real datacenter. • This also clearly indicates the lack of interest of Stanford university, Duetsche Telekom and HP labs – your employers, in your work.

  9. ElasticTree v/s Third Party Computing • Will Elastic Tree approach be more profitable than Third Party Computing? • Wouldn’t it make more sense to outsource my datacenter’s additional capacity to third party rather than shutting them so as to save power costs? • Considering the fact that VM’s are instantiated on demand, will the optimizer algorithm be any good since it needs a lot of previous information?

  10. ElasticTree v/s DDOS • Wouldn’t a datacenter running on a ElasticTree be an ideal target for a DDOS attack. Since there is no way to predict a DDOS attack even from previous statistics???

  11. Robustness Analysis • A datacenter will use a MST-k configuration to absorb k simultaneous faults. • With a MST-k configuration our total energy savings = 5% * 40% * Total Power k

  12. Testbed: Far from the real • Switches: Virtual Switch? • Power consumption, on/off • Latency • Configuration operability • Topology: simplified fat tree (k=4) • Real DCs: k>12~ • Other topologies, not only fat tree

  13. Testbed: Far from the real – cont’d • Workload Traffic: • collected from DC with only 290 servers • different fat tree configurations with simulation. • Traffic collected in very coarse granularity. • 10 minutes interval • Anything could happen during this interval in real DC (burst, raise/down)

  14. System response time • The algorithms itself • 3.5th order for formal model • 2th order for greedy • How many time will these take in real system? • What the response time? • None of these are given in the paper.

  15. Real Switch Latency • Time to boot a real switch • Up to 3 mins? • How to handle this network traffic burst • The latency time is unbearable in most of DCs • Authors propose us to use the possible fantasy feathers from these future switches, like sleeping mode

  16. How Control Module works in real DC? • How the control signals sent out • In simulation, easy, all software • In real DC, how? • By extra wires from control machine to each switch? • You justify that in real DC one can use mechanisms such as command line interface, SNMP etc to on/off switches, why not use them rather than state them…… • OpenFlow & NOX • Does widely used switches and DC has these? • How many efforts to port these?

  17. Centralized Control Module? – not good idea • Control modules – single point of failure • What is the potential harmfulness of control failure? • If down, the whole DC could be malfunctioned, or stopped • What is the recovery process from failure • Cost/time

  18. Results – Not convinced • What the overall power saving for the real DC traffics? • In figures 15 and 16. What is the typical latency and lost percentage for DCs without ElasticTree applied? • Authors claim the results from figures 15 and 16 are helpful for DC operators to choose needed tradeoff, • Actually not!! • The statistics differ a lot for DCs with different configurations and scales

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