1. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 1 Cloud Computing A Trend Taking Shape Yangfan Zhou Dept. Computer Science and Engineering The Chinese University of Hong Kong

2. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 2 Contents Drive of cloud computing Nature of cloud computing Cloud computing industry Conclusions Trustworthy cloud computing

3. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 3 Contents Drive of cloud computing Nature of cloud computing Cloud computing industry Conclusions Trustworthy cloud computing

4. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 4 What the buzzword is about You may ask: Is cloud computing created by marketing people?? A new name of an old and awful technology?? a new technology focusing on higher-speed computing?? a new technology that can let you use more storage capacity?? a new concept that can help programmers? maintainers? Let’s see what it is via its economic drive

5. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 5 Hosting computing systems CSE co. ltd. Server

6. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 6 Hosting computing systems CSE co. ltd.

7. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 7 Hosting computing systems CSE co. ltd.

8. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 8 Hosting computing systems CSE co. ltd. Peak hourMost of the time Waste of resource = waste of $

9. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 9 Hosting computing systems You pay for the servers no matter whether you are using them or not –The money you spend to buy the hardware –The salary for the maintainers –The electricity (including that for air conditioning) –Other maintenance costs, e.g., repairing, upgrading, renting a room for the servers. Waste of resource = waste of $ CSE co. ltd.

10. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 10 Hosting computing systems CSE co. ltd. Server How I wish this cloud can really host the computing systems for me So that I can provide a scalable, on-demand service.

11. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 11 When there is a dream, there is a market A lot of companies said: Sure!!! We can produce such a cloud for you –Microsoft, IBM, Google, Amazon, HP, Yahoo!, Intel.. A lot of people do have done a lot of hard work –Many more IT companies join and make the same promise before they really know what the promise means technologically –Try to define “cloud computing” –Try to register “cloud computing” as a trademark –Found many startups I don’t have to care what it is. I can just host my services here. marketing

12. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 12 When there is a dream, there is a market A recent reaction in the capital market PE=Price per Share/Earning per Share

13. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 13 When there is a dream, there is a market

14. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 14 Contents Drive of cloud computing Nature of cloud computing Cloud computing industry Conclusions Trustworthy cloud computing

15. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 15 Cloud computing preliminaries Computing System Application Platform Infrastructure hardware OS, middleware User software, API

16. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 16 Cloud computing preliminaries Application Platform Infrastructure SaaS: Software as a service PaaS: Platform as a service Provided by the cloud computing provider IaaS: Infrastructure as a service A cloud user’s own application and OS A cloud user’s own application Three cloud computing stacks

17. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 17 Out-sourcing is a great idea!!! Pay as you go The core of cloud computing is computing/storage outsourcing vs Pay for exactly what you’ve used Pay as you go!! Cost Down!!!

18. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 18 Outsourcing Electronics industry Brand vendor Manufacturer Manufacturing outsourcing Different manufacturing requirements in low season and high season # of product lines # of workers OEM: original equipment manufacturer ODM: original design manufacturer Cost down!!! Service vendor Cloud computing provider Computing and storage outsourcing Different service requirements in different times # of servers # of maintainers OSP: original service provider Cost down!!! Services for end users

19. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 19 Cloud computing v.s. Grid computing Cloud computing is not just a new term for an old idea Grid computing –Focus on let more than one computer coordinate to solve a problem together –Often include heterogeneous environments, i.e., computers of different capacity, configuration, and even different OS. –Business Model: project-oriented Cloud computing –An application doesn't access resources directly. It accesses them through a service. Usually the service has access to a large amount of physical resources, and can dynamically allocate them on demand. –Business Model: pay on a consumption basis A cloud can use grid computing technique. But a grid is not necessarily a cloud or part of a cloud.

20. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 20 Contents Drive of cloud computing Nature of cloud computing Cloud computing industry Conclusions Trustworthy cloud computing

21. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 21 Cloud computing industry Amazon Elastic Compute Cloud (EC2) Google App Engine Microsoft's Windows Azure Platform Other small startups: Heroku & Engine Yard Representative Providers

22. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 22 Amazon Elastic Compute Cloud (EC2) Xen-based virtual computing environment where a user can run Linux-based applications A user can boot an Amazon Machine Image to create a virtual machine instance containing any software desired IaaS: A user can control nearly the entire software stack, from the kernel upwards. It provides low level of virtualization –raw CPU cycles, block-device storage, IP-level connectivity Provided together with Simple Storage Services (S3) –data storage service A user can increase or decrease capacity within minutes Amazon charges $0.084/hour ($61/month) for the smallest virtual machine and around $0.10 per gigabyte of data transfer

23. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 23 Google App Engine Application domain-specific platforms. Not suitable for general-purpose computing Allow a user to run Web applications in Python or Java. Host applications in Google-managed data centers Enforcing an application structure of clean separation between a stateless computation tier and a stateful storage tier Support APIs for the Google Datastore, Google Accounts, URL fetch, image manipulation, and email services Automatically scale in response to load increases and decreases, and users are charged by the cycles used Free up to a certain level of used resources –500MB of storage and about 5 million page views

24. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 24 Microsoft's Windows Azure Platform Use Windows Azure Hypervisor as the infrastructure Use the.NET framework as the application container and applications are compiled to the Common Language Runtime, a language-independent managed environment PaaS: Can be considered as something intermediate between application frameworks like Google App Engine and hardware virtual environments like Amazon EC2 Support general-purpose computing, rather than a single category of application Users can choose language, but cannot control the underlying operating system or runtime The libraries provide a degree of automatic network configuration and failover/scalability, but require the developer to declare some application properties

25. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 25 Other small startups: Heroku & Engine Yard Heroku –Based on Ruby on Rails –Dyno: a dyno is a single process running ruby code on a server in Heroku grid –Application codes run inside the dyno grid, occupying as many slots as needed. New dynos for an application can be started in under 2 seconds for most applications. –Dynos are launched in an environment containing your app's database and cache information –Charge on a capacity basis. Free for the entry level Engine Yard –Also based on Ruby on Rails –Similar

26. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 26 Contents Drive of cloud computing Nature of cloud computing Trustworthy cloud computing Conclusions Cloud computing industry

27. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 27 Cloud computing challenges and opportunities Challenges and opportunities of our interests How to provide a scalable service, adaptive to the diversity of end-users (# of end users, locations of end users) –QoS provisioning How to provide a secure service –Privacy preserving –Secure access guaranteeing –Resilient to attacks How to provide a reliable service –Fault tolerance –New test methodologies Why people will trust their data/computing to the cloud and accept the idea of computing/storage outsourcing?? Towards Trustworthy Cloud Computing

28. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 28 Cloud computing challenges and opportunities Topic 1: QoS Provisioning How to provide a scalable service, adaptive to the diversity of end-users

29. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 29 Preliminaries of service composition –A service can be composed by many components –Components may locate world-wide –There are many components with the same functionalities Cloud computing challenges and opportunities ` A cloud service components

30. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 30 Potential research problems QoS driven recommendation for cloud service composition Observations –The QoS properties of the same cloud service component are different in the users’ perspective Users are located world wide The network connections of different users are different –Software quality metrics no longer depends only on the software per se Cloud computing challenges and opportunities

31. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 31 Cloud computing challenges and opportunities Potential research problems Problem 1: QoS driven recommendation for cloud service composition: How to recommend a set of components to form a service based on a cloud user’s networking feature –Heuristic: recommend based on IP address –Recommend based on the similarity –Mapping our Web services research to this domain Component 1Component 2Component 3Component 4 User 1Value 11Value 12Value 13Value 14 User 2Value 21Value 22Value 23Value 24 User 3Value 31Value 32Value 33Value 34 New UserValue 43Value 44 Prediction

32. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 32 Potential research problems Problem 2: How many resources/components that should be proactively reserved to guarantee QoS –Based on a prediction of the service usage –We should look into how resources are virtualized Cloud computing challenges and opportunities

33. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 33 Potential research problems Problem 3: Real-world measurement on the existing clouds –Amazon EC2, Google APP Engine –Elastic? –QoS all over the world? Cloud computing challenges and opportunities Commercial Cloud PlanetLab Node

34. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 34 Cloud computing challenges and opportunities Topic 2: Fault tolerance and reliability How to provide a reliable service given the fact no components are perfectly created, and the Internet is unpredictable

35. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 35 Cloud computing challenges and opportunities Potential research problem Problem 1: Reliability prediction of cloud service composition, i.e., how to predict the reliability quality of a service that is composed by a set of components –Previous method: measurement Cannot know before deployment Cannot know if we cannot do tremendous tests Hard to know if we don’t know how components are coded –Predict also based on the similarity –Reliability can be predicted in the service design phase based on its composition specific Component 1Component 2Component 3Component 4 User 1Value 11Value 12Value 13Value 14 User 2Value 21Value 22Value 23Value 24 User 3Value 31Value 32Value 33Value 34 New UserValue 43Value 44 Prediction

36. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 36 Cloud computing challenges and opportunities Potential research problem Problem 2: How to tolerate faults in stateful cloud applications. –Long term business process –Cloud computing: Redundancy in nature –Solutions Recovery –Check pointing and rollback Standby redundancy –State transfer Parallel redundancy –State synchronization.

37. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 37 Cloud computing challenges and opportunities Other potential research problems How to exploit the redundancy in cloud computing Cloud failure detection Component dependency analysis Error propagation analysis

38. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 38 Cloud computing challenges and opportunities Topic 3: Security How to provide a secure service

39. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 39 Potential research problems Problem 1: Identify critical cloud nodes –Dynamic service composition  Complex component invoking relations –Reliability and attack-resilience features of different components may have different impacts on the whole cloud –Identify critical components Purpose: To reduce the vulnerability Approach: based on the service composition relations (Ranking) Cloud computing challenges and opportunities

40. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 40 Potential research problems Problem 2: Attack resilient –Subproblem 1: DoS masking Utilize the redundant nature of components Intelligent watchdog technique Load balance technique –Subproblem 2: Anti-Masquerade attacks A malicious node will fake a large number of pseudonymous components, which can be used to gain a biased trust in service composition Design a reputation mechanism Use similar techniques as those for anti-spam in searching engines Cloud computing challenges and opportunities

41. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 41 Potential research problems Problem 3: New access control paradigm –Purpose: Anti-freeriding Guarantee data security –Challenge: How to share the user credentials among different cloud nodes/components efficiently A user may login at a node And invoke a component at another node Access control paradigm for stateful services Cloud computing challenges and opportunities

42. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 42 Cloud computing challenges and opportunities Email servers You put your emails there without worrying about leaking your privacy? We have laws and commercial moral. - Can still be a good area to publish academic papers - Several top conference papers Potential research problem? Privacy preserving –There are already papers in this area. –May not be a big deal, because … –We may have to provide private data to the cloud because we need it to compute them Why we trust the IT guys in our department more than a cloud computing company far far away

43. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 43 Cloud computing challenges and opportunities Topic 4: Testing How to test cloud computing system

44. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 44 Potential research problems Problem 1: Embracing user-supplied software testing –Test-as-you-use paradigm is possible –Tremendous runtime data can greatly facilitate testing Cloud computing challenges and opportunities Software is running at servers, runtime data can be collected easily Software is running at PCs, runtime data can only be collected by user report

45. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 45 Potential research problems Problem 2: Anomaly detection (for locating potential faults) –Test-as-you-use paradigm is possible –There are tremendous runtime data –Can these data be utilized for locating potential faults How to locate anomaly How to locate the root cause of the anomaly Cloud computing challenges and opportunities

46. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 46 Cloud computing challenges and opportunities Topic 5: System How to build a cloud computing system

47. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 47 Potential research problems Problem 1: Building a cloud An organization provides its PCs as nodes in the cloud Users can use the cloud Challenges –Many engineering efforts Which language(s) it supports The framework: IaaS or PaaS More including coding –Accounting system –Reliability system –QoS provisioning –Attack-resilient –And many others Cloud computing challenges and opportunities

48. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 48 Potential research problems Problem 2: Building an open cloud Everyone can provide his/her PC as a node in the cloud And everybody can use the cloud Challenges –Many engineering efforts Which language(s) it supports The framework: IaaS or PaaS More including coding –A reputation mechanism to stimulate contributions –A reputation mechanism for anti-freeriding –Attack-resilient Cloud computing challenges and opportunities

49. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 49 Task 1: Achieving trustworthy cloud computing in architectural design –Ranking-based identification of critical cloud nodes –QoS driven recommendation for cloud service composition –Development of an open cloud computing architecture Task 2: Enhancing the security and reliability for cloud computing paradigm –A new access control paradigm –Tolerating faults in cloud computing –Designing a reputation mechanism for an open cloud Task 3: Formulating a new testing methodology for trustworthy cloud computing –Embracing user-supplied software testing in cloud computing paradigm –Unveiling faults via symptom mining Task 4: Implementing an open-source cloud computing framework –Test-bed construction –Large scale experiments Current proposal outline

50. Dept. of Computer Sci. & Eng., The Chinese University of Hong Kong 50 Conclusions 1.Cloud computing include IaaS, PaaS, SaaS 2.We identify several research areas QoS provisioning Fault tolerance and reliability Security Testing Cloud system implementations 3.Cloud service composition is a critical feature, enriching QoS provisioning, fault tolerance, and reliability issues 4. Redundancy is an important nature of cloud computing systems, enabling fault tolerance, attack resilience 5. Application runtime data are available in the cloud, facilitating reliability prediction, QoS provisioning, and testing