Analyzing the Applicatbility of Airline Booking Systems for Cloud Computing Offerings
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1 ISGC 2010 Analyzing the Applicatbility of Airline Booking Systems for Cloud Computing Offerings Johannes Watzl, Nils gentschen Felde, Dieter Kranzlmüller Aufgabensteller: Prof. Dr. H.-G. Hegering Grid Computing and Cloud Computing II Betreuer: <Name des 1. Betreuers, Name 12 March des , Betreuers, Taipei...> Datum: <Datum des Vortrags> Johannes Ludwig-Maximilians-Universität Watzl ISGC München, 2010 MNM-Team
2 Contents Cloud Computing - Classification - Pricing Overview - Example: Amazon Web Services Airline Booking Systems Application on Cloud Computing - Example Cloud Booking System Use Cases - Requirements Motivation for Further Work Conclusions 22
3 Cloud Computing Classification Examples: salesforce.com, Google Apps, Infrastructure as a Service Platform (IaaS) as a Service (PaaS) Software as a Service (SaaS) Examples: Amazon Web Examples: Hosting Services, of Google virtual Rackspace, machines AppEngine, Application Platform demand Heroku, for service executing providing (web)ap 33
4 Cloud Computing Classification Company Extending No Make need use for of internal a overprovisioning private benefits Cloud cloud of Cloud with infrastructures resources from public Clouds - peak load outs Public Cloud Private Cloud Hybrid Cloud Services offered over the Avoid Security internet security concerns risks of public Clouds 44
5 Cloud Pricing Overview Focus on: - Infrastructure as a Service - Virtual machine hosting Current pricing models - Mostly static concepts - Hourly charging Examples: - Amazon EC2 - Flexiscale - Rackspace
6 Cloud Pricing Amazon Web Services Amazon Web Services (Elastic Compute Cloud - EC2) Three different offered pricing concepts: - On-Demand Instances ($0.085-$2.40/hour) Standard, High-Memory, High-CPU Static pricing Pay-per-use, hourly charged - Reserved Instances (base fee + $0.03-$0.84/hour) Offered Product as in On-Demand Instances Reservation fee (one year or three years contract) Cheaper price per instance and hour - Spot Instances bidding on spare EC2 instances Price based on current offer and demand Enable bids on instances 66
7 Cloud Pricing Amazon Web Services Comparing on-demand and reserved instances 77
8 Airline Booking Systems Revenue management, capacity planning Maximize the revenue per flight Maximize the utilization Basic Concept - Service Classes - Different products Economy Business First - Booking Classes (Defining fences) Restrictions Cancellation Booking Change - (Dynamically) define capacities for each booking class 88
9 Application on Cloud Computing? 99
10 Example Cloud Booking System Basic model with three service classes and three booking classes per service class Corresponding static model: Expected Marginal Seat Revenue (EMSR) Method 1010
11 Example Cloud Booking System Comparison of expected revenue of static and dynamic model 1111
12 Use Cases - Requirements A user wants to buy Cloud resources for the lowest price A user wants to use allocated Cloud resources for a longer period of time A provider wants to sell Cloud resources on a certain platform Requirments: - Cloud resource description language - Definition of semantics of units (e.g. for CPU power/ usage) - Comparability of resources described within a given resource description language - Quantization of usage over time (e.g. minutes or hours) - Pricing of Cloud offerings per time unit 1212
13 Motivation for Further Work Cloud resources seem to be infinite - Higher Demand => resources will rapidly become finite Offer and demand driven pricing strategies will become indispensable in the future Cloud ecosystems - Interoperability - Standards - Comparability - Transparent Pricing - Transparent SLAs Trading platform for Cloud resources 1313
14 Conclusions Introduction in Cloud Computing Pricing Overview - Amazon Airline Booking Systems Cloud computing offerrings mapped on Airline Booking - Different products (service classes) - Different booking classes Cloud Booking System Example Requirements derived from use cases Further work 1414
15 Thank you! Johannes Watzl
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