a framework for user feedback based cloud service monitoring authors: zia ur rehman omar k hussain...

A Framework For User Feedback Based Cloud Service Monitoring

Authors: Zia ur Rehman Omar K Hussain

Sazia Parvin Farookh K. Hussain

Presenter: Sajala Rajendran

AbstractGoal: 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

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.

OutlineIntroductionMotivationRelated WorkProblem FormalizationProposed FrameworkConclusionFuture Work

IntroductionCloud services have different service

characteristics, levels of abstraction, quality of service and pricing policies.

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.

Cloud providers offer tools to check cloud status

Third party cloud monitoring services availableCurrent 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

MotivationCloud 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 anotherDifficulty 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)

QoS data collected through cloud monitoringCurrently, 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

Related Work – Cloud Service SelectionGoscinski 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.

Cloud Monitoring

CloudHarmonyProvides vital information on the

performance of clouds using benchmark testsChecks performance of servicesData collected is provided to usersBased on the data, users make a decision

about migration

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.

CloudleAimed at determining resource usage patternUser’s application is run in a simulated

environmentResource 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

Problem FormalizationProblem domain defined using three setsC = { C1, C2, …. Cn } – available cloud

servicesU = { 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

Relationship between users and cloud services is represented by the following matrix

Row – cloud userColumn – cloud serviceUser i using cloud service k – corresponding

element is 1 else 0

Example…Five cloud services7 cloud usersC = { C1, C2, …. C5 }

U = { u1, u2, ….u7 }

Proposed FrameworkCloud 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.

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.

AdvantagesBetter approach compared to existing cloud

monitoring servicesUser 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.

Conclusion and Future WorkAuthors 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 issues that can arise in this system.

Thank You !!!