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A Framework For User Feedback Based Cloud Service Monitoring

A Framework For User Feedback Based Cloud Service Monitoring. Authors : Zia ur Rehman Omar K Hussain Sazia Parvin Farookh K. Hussain Presenter : Sajala Rajendran. Abstract.

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A Framework For User Feedback Based Cloud Service Monitoring

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  1. A Framework For User Feedback Based Cloud Service Monitoring Authors: Zia urRehman Omar K Hussain SaziaParvin Farookh K. Hussain Presenter: SajalaRajendran

  2. Abstract • Goal: Assist users in choosing appropriate cloud services that offer optimal performance at lowest cost. • A multi-criteria optimization or decision-making problem • Major issues: • (1) Choice of criteria set • (2) Assessing cloud services against each criterion

  3. Contd… • Existing cloud service monitoring mechanisms depend on benchmark tests which is inaccurate. • Proposes a user-feedback-based approach by monitoring cloud performance more reliably and accurately compared to existing mechanisms.

  4. Outline • Introduction • Motivation • Related Work • Problem Formalization • Proposed Framework • Conclusion • Future Work

  5. Introduction • Cloud services have different service characteristics, levels of abstraction, quality of service and pricing policies.

  6. All these classification make it more complex for optimal service selection. • Proposed mechanism depends on QoS history collected by capturing changes in performance and quality of provided service over a time interval. • Continuous monitoring is required.

  7. Cloud providers offer tools to check cloud status • Third party cloud monitoring services available • Current cloud status data and past performance is vital for accurate cloud service selection • Else, cloud users need to deploy applications on different clouds to determine the relative performance of each – a costly, cumbersome and an inefficient process

  8. Motivation • Cloud users should have quality of service and performance related information of other cloud service offerings as well. • Understanding will ensure efficient cloud service selection • Migration from one service to another • Difficulty in migration from one service to another due to incompatibilities – hypervisors( Xen, KVM or Vmware ) • Interoperable and federated clouds achieve compatibility using open cloud software and inter-cloud protocols. (Open Nebula, Nimbus Project)

  9. QoS data collected through cloud monitoring • Currently, information regarding cloud service selection comes in the form of SLA’s and dashboard services. • A third party cloud service monitoring is essential to gather unbiased QoS information. • Third parties use benchmarks that cannot reflect performance of an actual application in the cloud • Proposed approach enables sharing of usage experience

  10. Related Work – Cloud Service Selection • Goscinski stresses the need for research on developing methodologies for service selection in cloud computing. • Li discussed the importance of having a service provider comparison framework. Presented a tool called CloudCmp that relies on several benchmark tools to compare services. • Garg provided a standard set of attributes for cloud comparison.

  11. Cloud Monitoring

  12. CloudHarmony • Provides vital information on the performance of clouds using benchmark tests • Checks performance of services • Data collected is provided to users • Based on the data, users make a decision about migration

  13. Applications differ in resource usage leading to different performance. • Differences between actual and predicted cost • Cloud profiling techniques have been developed to track resource usage of user applications. • Provides vital information to predict the performance and cost of these applications in a cloud environment. • These mechanisms use complex benchmarks.

  14. Cloudle • Aimed at determining resource usage pattern • User’s application is run in a simulated environment • Resource usage pattern recorded predicts expected cloud resource requirements of the application • Drawbacks – (1) Does not have its own cloud monitoring mechanism (2) Depends on existing cloud monitoring services

  15. Problem Formalization • Problem domain defined using three sets • C = { C1, C2, …. Cn } – available cloud services • U = { u1, u2, ….un } – Set of current users • Assumption : All the services in C are IaaS using same virtualization tool • VM migration across different services is feasible

  16. Relationship between users and cloud services is represented by the following matrix • Row – cloud user • Column – cloud service • User i using cloud service k – corresponding element is 1 else 0

  17. Example… • Five cloud services • 7 cloud users • C = { C1, C2, …. C5 } • U = { u1, u2, ….u7 }

  18. Proposed Framework • Cloud Status Checker – Check the status of the application running on the cloud generating cloud status report. Status checker functionality is installed in the VM by each participating user. • Repository – Maintains all status reports generated by previous step. • Determining resource usage pattern of cloud applications – status reports reflect performance of common application types on popular cloud services at any time.

  19. Dashboard Interface – Mechanism for users to access the information. • Testing of new cloud applications – Cloud status checker or temporary cloud environment to determine application’s resource usage patter • Assumption – Cloud services offering satisfactory service to existing applications having similar usage pattern to that of new applications are the best services.

  20. Advantages • Better approach compared to existing cloud monitoring services • User provided information is more reliable compared to third part benchmark data or dashboards provided by vendors. • Since users obtain monitoring data at no cost, they participate in the system despite paying for resources consumed in running cloud status checker. • Cost of hosting repositories can be shared between cloud vendors who can increase their number of customers and enhance customer trust in them.

  21. Conclusion and Future Work • Authors have proposed a cloud monitoring system based on reliable user data to assist in cloud service selection and migration. • Information sharing mechanism exists between cloud users, proving to be more effective • In future, the authors will be involved in development of a simulation and a working prototype. Also, investigate the security issuesthat can arise in this system.

  22. Thank You !!!

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