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a Framework for Ranking of Cloud Computing Services Saurabh Kumar Garg, Steve Versteeg, Rajkumar Buyya Supervisor : Dr. Leyli Mohammadkhanli Presented By : SayedHassan Khatoonabadi Department of Computer Science
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Page 1: SMICloud

a Framework for Ranking of Cloud Computing Services

Saurabh Kumar Garg, Steve Versteeg, Rajkumar Buyya

Supervisor : Dr. Leyli MohammadkhanliPresented By : SayedHassan Khatoonabadi

Department of Computer Science

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a Framework for Ranking of Cloud Computing Services 2

Service Measurement IndexBased on ISO standards by CSIMC

Set of business-relevant KPIs AccountabilityAgilityCostPerformanceAssuranceSecurity and PrivacyUsability

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SMICloud Framework

Decision Making Tool Service Selection

Based on QoS requirements

Service Ranking

Based on previous user experiences and performance of services

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Quality Model for IaaSService Respond Time

Average Respond Time : ∑iTi/n

Maximum Response TimeResponse Time Failure : 100(n′/n)

SustainabilityDCIE and PUEDPPE

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Quality Model (Cont.)Suitability

AccuracyAccuracy Frequency : Accuracy Value :

Transparency

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Quality Model (Cont.)Interoperability

Availability

Reliability

Stability

Cost

Adaptability

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Quality Model (Cont.)Elasticity

Mean time to expand or contract capacityMaximum capacity

Usability

Throughput and efficiency

Scalability

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Quality Model AssessmentComply with IEEE Standard 1061

CorrelationPractical and computableConsistencyDiscriminative power

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Service Quality Ranking using AHP

Phase 1: hierarchy structure for cloud services based on SMI KPIs

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Service Quality Ranking using AHP (Cont.)

Phase 2: computation of relative weights of each QoS and serviceUser assigned weights using AHP’s standard method

Arbitrary user assigned weights

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Service Quality Ranking using AHP (Cont.)

Phase 3: relative value-based weights for ranking Cloud services

Boolean :

Numerical : si/sj =

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Service Quality Ranking using AHP (Cont.)

Unordered set

Essential :

Non-Essential :

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Service Quality Ranking using AHP (Cont.)

Range typeEssential :Non-Essential :

Phase 4: aggregation of relative ranking for each SMI attribute

Time complexity of AHP :

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Case Study