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Universidade Federal do Ceará FOLE: A Framework for Elasticity Performance Evaluation in Cloud Computing Systems Emanuel F. Coutinho Group of Computer.

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Presentation on theme: "Universidade Federal do Ceará FOLE: A Framework for Elasticity Performance Evaluation in Cloud Computing Systems Emanuel F. Coutinho Group of Computer."— Presentation transcript:

1 Universidade Federal do Ceará FOLE: A Framework for Elasticity Performance Evaluation in Cloud Computing Systems Emanuel F. Coutinho Group of Computer Networks, Software Engineering, and Systems (GREat) Federal University of Ceara (UFC) Advisor: José Neuman de Souza Co-advisor: Danielo Gonçalves Gomes 1

2 Universidade Federal do Ceará Main Research Cloud Computing –Elasticity –Metrics –Workloads Performance Analysis –Methodologies 2

3 Universidade Federal do Ceará Elasticity 3 Tools - benchmarks - workloads

4 Universidade Federal do Ceará Metrics Allocation time of operations Resources involved in allocation operations Analogies Measuring elasticity 4

5 Universidade Federal do Ceará Methodology Performance analysis Design of experiments 5

6 Universidade Federal do Ceará Mobile Cloud Computing Infraestructure, Performance, and Resource Allocation Paulo A. Rego Group of Computer Networks, Software Engineering, and Systems (GREat) Federal University of Ceara (UFC) Advisor: José Neuman de Souza Co-advisor: Fernando Trinta

7 Universidade Federal do Ceará Cloud Infraestructure and Resource Allocation -Evaluation of software to set up a private/hybrid cloud -OpenNebula, OpenStack, Eucalyptus, CloudStack -Creation of virtual appliances for easier the deployment of cloud applications -Development of solutions to handle the heterogeneity of the data center’s physical machines to achieve an homogeneous performance (FairCPU architecture) FairCPU Architecture

8 Universidade Federal do Ceará Cloud Infraestructure and Resource Allocation -Development of techniques to handle elasticity among different cloud solutions and cloud datacenters (hybrid cloud) -Execution of parallel applications on cloud -MPI (EHRA solution) -Performance evaluation of parallel applications to Big Data -Hadoop, YARN Execution and Resources Homogenization Architecture (ERHA)

9 Universidade Federal do Ceará Mobile Cloud Computing -Development of solutions to improve the performance of mobile applications and reduce battery consumption -Exploit cloud capabilities (storage and compute) through the use of offloading techniques -MPOS offloading system (Philipp’s master's thesis) -Orchestration of cloud services in private/local resources (cloudlet concept) and public/remote resources -Frameworks for Android and Windows Phone MPOS Architecture

10 Universidade Federal do Ceará Mobile Cloud Computing -Evaluate the impact of the 4G network in offloading performance -Study to improve the performance of private cloud infrastructure for different workload behavior of mobile applications -Handle mobility issues of mobile applications -Handoff, loss of connectivity, … -Handle QoS and SLA -Evaluate and extend offloading models -Develop components for decision making (when, where and what to offload)

11 Universidade Federal do Ceará Fernando Trinta Research topics: –Context-Aware Mobile Applications Content Adaptation –Digital Games Support for Pervasive Games (Middleware) –Cloud Computing Billing/Pricing Services in Cloud Computing Mobile Cloud Computing Software Engineering for Cloud

12 Universidade Federal do Ceará Fernando Trinta Personal Interest in SL4Cloud: –Theme 4: Pricing Strategies for Cloud Computing Load Balance and Profit Some research has already been done (aCCountS – a Cloud aCCOUNting System for IaaS, MsC Dissertation 2013) –Theme 5: Applications in Mobile Cloud Computing Demonstrator One student already engaged Mobile Cloud Computing + Context Aware – This resource may be useful

13 Universidade Federal do Ceará Web Workload Modeling for Simulation and Analysis in Cloud Computing Deborah M. V. Magalhães Group of Computer Networks, Software Engineering, and Systems (GREat) Federal University of Ceara (UFC) Advisor: Danielo Gonçalves Gomes Cloud Computing and Distributed Systems (CLOUDS) Laboratory The University of Melbourne (Unimelb) Co-advisors: Rajkumar Buyya and Rodrigo Calheiros

14 Universidade Federal do Ceará Motivation Cloud environments have different types of applications –resulting in complex workloads according to users behaviour and task resource consumption patterns Not much real datacenters traces are available (MORENO et al., 2013) –Lack of methodologies to capture the diversity of cloud workload patterns Provisioning and scheduling techniques for interactive applications is an important issue (GROZEV;BUYYA, 2013) Workload modeling in cloud computing gives rise to performance analysis and simulation (FEITELSON, 2003)

15 Universidade Federal do Ceará Main Goals The creation of a web application model based on data collected from a real Cloud for analysis and simulation, so that there is a good approximation to the real system –A model easily manageable to generate different synthetic loads relating to other relevant applications in Cloud Computing What is the relation between the model creation and energy efficiency (theme 2)?

16 Universidade Federal do Ceará Workload RUBiS: Rice University Bidding System http://rubis.ow2.org/ http://rubis.ow2.org/ –An auction site based on eBay.com, implementing basic functionality, such as: selling, browsing and bidding –It is widely used to evaluate scalability of application servers –It is a free and open source benchmark

17 Universidade Federal do Ceará Short and midterm actions 1.Incorporate the mathematical models extrated from the observed data to the R software 2.Extract the simulation results from CloudSim and evaluate the fit of model to the observed data 3.Investigate the most suitable algorithm for predicting the metric of interest: response time

18 Universidade Federal do Ceará References FEITELSON, Dror G. Workload Modeling for Computer Systems Performance Evaluation, 2003. Disponível em:. GROZEV, Nikolay; BUYYA, Rajkumar. Performance modelling and simulation of three-tier applications in cloud and multi-cloud environments. The Computer Journal, 2013. Disponível em:. MORENO, I.S.; GARRAGHAN, P.; TOWNEND, P.; XU, Jie. An approach for characterizing workloads in google cloud to derive realistic resource utilization models. In: Service Oriented System Engineering (SOSE), 2013. p. 49-60.

19 Universidade Federal do Ceará 19

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