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Dipartimento di Elettronica, Informazione e Bioingegneria

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Presentation on theme: "Dipartimento di Elettronica, Informazione e Bioingegneria"— Presentation transcript:

1 Dipartimento di Elettronica, Informazione e Bioingegneria
Characterizing energy consumption and adaptation strategies for Cloud Applications Barbara Pernici Dipartimento di Elettronica, Informazione e Bioingegneria Politecnico di Milano

2 Analyzing batch workloads
Outline An approach towards an adaptive behaviour for improving energy efficiency and reducing CO2 emissions in federated clouds The ECO2Clouds project Analyzing batch workloads Barbara Pernici - ACROSS, September 2016

3 Improving energy efficiency in data centers and decrease CO2 emissions
Key concepts: Energy efficiency Green indicators Monitoring Adaptation actions Multilayer European projects: GAMES, ECO2Clouds Barbara Pernici - ACROSS, September 2016

4 Barbara Pernici - ACROSS, September 2016

5 Multilayer

6 Eco-metrics Barbara Pernici - ACROSS, September 2016

7 Measuring power consumption

8 Monitoring infrastructure
Barbara Pernici - ACROSS, September 2016

9 Adaptation strategies for applications
Barbara Pernici - ACROSS, September 2016

10 Application profiles Barbara Pernici - ACROSS, September 2016

11 Strategies Barbara Pernici - ACROSS, September 2016

12 Designing application profiles
Batch applications Modeling energy consumption in different configurations Meeting requirements and evaluating alternative configurations Refining application profiles Barbara Pernici - ACROSS, September 2016

13 Power and energy modeling
Barbara Pernici - ACROSS, September 2016

14 Analyzing batch applications
Power consumption of an experiment involves N VMs Energy per job (J jobs)

15 Power models Power consumption of physical host and VMs proportional to usage Power consumption of a VM

16 Testing the model

17 Configurations Number of VMs for J jobs? Which are the parameters for the alternatives? Order of execution Shared resources: storage access before computing activities What is interference between applications What if heterogeneous hosts are assigned by the cloud scheduler?

18 Analysis of alternative configurations
Asynchronous/synchronous No. of VMs (1 to J) asynchronous synchronous

19 Simulation models asynchronous synchronous

20 Validation – simulation with JMT vs experimental data Synchronous accesses – 1 host
1 VM N=J

21 Analysis of energy per job

22 Bottlenecks Barbara Pernici - ACROSS, September 2016

23 Energy consumption analysis using the model varying the number of VMs – homogeneous hosts
Note: minimum P_idle, considering max number of VMs on hosts

24 In case of heterogeneous hosts- asynchronous (2 classes – high/low; 50 jobs)
Execution time α = % of high performance hosts High performance: 20% faster, 20 vs 8 cores, idle power 40% of lower perf.

25 In case of heterogeneous machines - synchronous (2 classes – high/low; 50 jobs)
Execution time α = % of high performance hosts

26 Future work Analyze other types of applications Transactional I/O intensive Define algorithms to identify the best configurations for a mix of applications Study other eco-metrics and dependencies between metrics

27 References U. Wajid, C. Cappiello, P. Plebani, B. Pernici, N. Mehandjiev M. Vitali, M. Gienger, K. Kavoussanakis, D. Margery, D. Garcia Perez, P. Sampaio, On Achieving Energy Efficiency and Reducing CO2 Footprint in Cloud Computing, IEEE Transactions on Cloud Computing, Vol. 4(2), pp , April 2016 C. Cappiello, N. Ho, B. Pernici, P. Plebani, M. Vitali, CO2-aware Adaptation Strategies for Cloud Applications, IEEE Transactions on Cloud Computing, Vol. 4(2), pp , April 2016 M. Gribaudo, T.T.N. Ho, B. Pernici, G. Serazzi, Analysing the influence of application deployment to energy consumption, E2DC, Cambridge, LNCS, June 2014 M. Gribaudo, B. Pernici and T.T.N. Ho, Characterizing Energy per Job in Cloud Applications, submitted Barbara Pernici - ACROSS, September 2016

28 QUESTIONS? Barbara Pernici - ACROSS, September 2016

29 Dipartimento di Elettronica, Informazione e Bioingegneria
Characterizing energy consumption and adaptation strategies for Cloud Applications Barbara Pernici Dipartimento di Elettronica, Informazione e Bioingegneria Politecnico di Milano

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