Rajkumar Buyya (1,2), Chee Shin Yeo (1), and Srikumar Venugopa (l)

1. Market-Oriented Cloud Computing:Vision, Hype, and Reality for Delivering IT Services as Computing Utilities RajkumarBuyya(1,2), Chee Shin Yeo(1), and SrikumarVenugopa(l) 1.Grid Computing and Distributed Systems (GRIDS) Laboratory Department of computer Science and Software Engineering The University of Melbourne, Australia 2.Manjrasoft Pty Ltd, Melbourne, Australia HPCC '08. 10th IEEE

2. Outline • Introduction • Market-Oriented Cloud Architecture • Commercial offering of market-oriented Clouds requirement and Qos issue • Emerging cloud platform • Amazon EC2 intro&pricing • Google App Engine intro&pricing • Microsoft Anzure platform intro&pricing • Possible pricing strategy(by Ming Lung) • Conclusions&comments

3. Introduction:definition • Definition of cloud: • A Cloud is a type of parallel and distributed system; • Consisting of a collection of interconnected and virtualized computers • That are dynamically provisioned and presented as one or more unified computing resources • ,based on service-level agreements established through negotiation between the service provider and consumers.”

4. Introduction:trend • Web Search Trends: [C]. Google and Salesforce.com in Cloud computing deal, Siliconrepublic.com - Apr 14 2008

5. Market-Oriented Cloud Architecture • Cloud providers will need to consider and meet different QoS parameters of each individual consumer as negotiated in specific SLAs. • Traditional system-centric resource management architecture are no longer fit • Do not provide incentives for them to share their resources. • Regard all service requests to be of equal importance.

6. Market-Oriented Cloud Architecture

7. Market-Oriented Cloud Architecture • Service Request Examiner andAdmission Control: • Interprets thesubmitted request for QoSrequirements before determiningwhether to accept or reject therequest. • Pricing: • The Pricing mechanismdecides how service requests arecharged. • Ex.submission time(peak/off-peak) , pricing rates(fixed/changing) • Accounting: • Maintains the actual usage of resources by requests and historical information usage. • Final cost to charge users. • Improve resource allocation decisions.

8. Market-Oriented Cloud Architecture • VM monitor: • Keep track of the availability of VMs and their resource entitlements. • Dispatcher: • starts the execution of accepted service requests on allocated VMs. • Service Request Monitor: • keeps track of the execution progress of service requests.

9. Qos parameter issue • In cloud there are critical QoS parameters to consider in a service request • time, cost, reliability and trust/security. • In particular, QoS requirements cannot be static and need to be dynamically updated over time. • Due to continuing changes in business operations and operating environments. • But , there are no or limited support for dynamic negotiation of SLAs. • Recently, we have developed negotiation mechanisms based on alternate offers protocol for establishing SLAs [8]. [8]S. Venugopal, X. Chu, and R. Buyya. using the Alternate Offers Protocol (IWQoS 2008), A Negotiation Mechanism for Advance Resource Reservation

10. Commercial offering of market-oriented Clouds requirement • Customizable • Support customer-driven service management based on customer profiles and requested service requirements. • Market-based resource management • Contain computational risk management to sustain SLA-oriented resource allocation. • Incorporate autonomic resource management models: • Effectively self-manage changes in service requirements to satisfy both new service demands and existing service obligations.

11. Emerging cloud platform

12. Amazon EC2

13. Amazon EC2 • Instances Types (Memory / *ECU / Storage / Platform) • Standard Instances • Small (default): 1.7 GB / 1 / 160 GB / 32-bit • Large: 7.5 GB / 4 / 850 GB / 64-bit • Extra Large: 15 GB / 8 / 1690 GB / 64-bit • High-Memory Instances • Double Extra Large: 34.2 GB / 13 / 850 GB / 64-bit • Quadruple Extra Large: 68.4 GB / 26 / 1690 GB / 64-bit • High-CPU Instances • Medium: 1.7 GB / 5 / 350 GB / 32-bit • Extra Large: 7 GB / 20 / 1690 GB / 64-bit http://aws.amazon.com/ec2/

14. About Measuring Compute Resources (quote from Amazon) • *ECU – EC2 Compute Unit, providing the equivalent CPU capacity of a 1.0 – 1.2 GHz 2007 Opteron or 2007 Xeon processor • “Amazon EC2 uses a variety of measures to provide each instance with a consistent and predictable amount of CPU capacity.” • We use several benchmarks and tests to manage the consistency and predictability of the performance of an EC2 Compute Unit. • Over time, we may add or substitute measures that go into the definition of an EC2 Compute Unit, if we find metrics that will give you a clearer picture of compute capacity. • “To find out which instance will work best for your application, the best thing to do is to launch an instance and benchmark your own application.” • pay by the hour

15. On-Demand Instances Unit: Per Hour

16. Reserved Instances

17. Spot Instances • Spot Instances enable you to bid for unused Amazon EC2 capacity. • To use Spot Instances, you should set • (instance type, region, amount, maximum price) *fluctuates periodically depending on the supply of and demand for Spot Instance

18. Data Transfer Data transferred between two Amazon Web Services within the same zone is free of charge. Data transferred between AWS services in same regions but different zone will be charged $0.01 per GB in/out.

19. Amazon add-on services • Amazon Elastic Block Store • Amazon EBS volumes provide off-instance storage that persists independently from the life of an instance. • Charged per GB/month and I/O request • Amazon CloudWatch (bundle with Auto Scaling) • Amazon CloudWatch is a web service that provides monitoring for AWS cloud resources. • such as CPU utilization, disk reads and writes, and network traffic. • Auto Scaling allows you to automatically scale your Amazon EC2 capacity up or down according to conditions you define. • Charged per instance-hour • Elastic Load Balancing • Elastic Load Balancing automatically distributes incoming application traffic across multiple Amazon EC2 instances. • Charged per hour and GB of data processed

20. Google App Engine

21. Google App Engine • Run web applications on Google’s infrastructure • Programming language support: python, java • Pricing: • Quota • Fixed quota (for free) • Disable billing • Enable billing • Billable quota • Budget http://code.google.com/intl/en/appengine/docs/whatisgoogleappengine.html

22. Requests

23. Datastore

24. URL Fetch

25. Mail

26. Image Manipulation

27. Memcache

28. Billable Quota Unit Cost http://code.google.com/intl/en/appengine/docs/billing.html

29. Microsoft Windows Azure

30. Microsoft Windows Azure • Windows Azure platform • Provides a scalable environment with compute, storage, hosting, and management capabilities. • SQL Azure • A Relational Database for the Cloud(Windows Azure platform).

31. Microsoft Windows Azure • During Community Technology Preview (CTP), services included in Windows Azure will be available without charge • Total compute usage: 2000 VM hours/month • Cloud storage capacity: 50GB • Total storage data transfers: 20GB/day • Once launched for commercial use, Windows Azure would be priced and licensed • Jan 1, 2010 • First month without charge

32. Pricing unit • Compute Instances: • (Instance Size, CPU, Memory, Storage, I/O Performance ) Small --------1.6 GHz ,1.75 GB, 225 GB, Moderate Medium --2 x 1.6 GHz , 3.5 GB, 490 GB, High Large----- 4 x 1.6 GHz, 7 GB, 1,000 GB, High Extra large-8 x 1.6 GHz, 14 GB, 2,040 GB, High • Instance hour transformation: • Instance Size Elapsed Hour Small Instance Hours Small 1 hour 1 hour Medium 1 hour 2 hours Large 1 hour 4 hours Extra large 1 hour 8 hours

33. Pricing • Consumption: • Compute = $0.12 / small instance hour • Storage = $0.15 / GB stored / month • Storage transactions = $0.01 / 10K • Data transfers = $0.10 in / $0.15 out / GB - ($0.30 in / $0.45 out / GB in Asia) • Reserved(Development Accelerator Core): • 750 hours (small compute instance) • 10 GBs of storage • 1,000,000 storage transactions • 7 GB in / 14 GB out(2.5 GB in / 5 GB out in Asia) • For 6 month = $59.95 (42% off from consumption)

34. Pricing • Web Edition: Up to 1 GB relational database = $9.99 / month • Business Edition: Up to 10 GB relational database = $99.99 / month • Data transfers = $0.10 in / $0.15 out / GB - ($0.30 in / $0.45 out / GB in Asia)

35. Possible Strategies • Cost-based pricing • Flat pricing • Tiered-pricing • Performance-based pricing • User-based pricing • Usage-based pricing

36. Possible Strategies

37. Possible Strategies • Other effects • Similar prices (competing situation?)

38. Conclusion&Comments • In this paper, we have proposed architecture for market-oriented allocation of resources within Clouds. • We have discussed some representative platforms for Cloud computing covering the state-of-the-art. • Comments: • This paper has a simple but clear architecture that we can use. (need add something detail) • Some of the information of the cloud platform are out of date, but the comparison is good.