CloudBus
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The document presents the CloudBus Toolkit for market-oriented cloud computing, which aims to transform IT services into accessible utilities. It outlines the architecture and technologies involved, including cloud marketplaces, brokers, and various applications like Aneka and CloudSim. Additionally, it discusses challenges and future trends in cloud computing, emphasizing its potential impact on the computing industry.
![Cloud Computing
• Armbrust et al. [3] observe that “Cloud computing
refers to both the applications delivered as services
over the Internet and the hardware and system
software in the data centers that provide those
services”
• Buyya et al. [2] define Cloud as “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”
9](https://image.slidesharecdn.com/cloudbuspresentationamitashish-141123083408-conversion-gate01/85/CloudBus-9-320.jpg)
![[1] Kleinrock, L.: A Vision for the Internet. ST Journal of Research, vol. 2, Issue 1, pp. 4--5, November 2005.
[2] Buyya, R., Yeo, C.S., and Venugopal, S.: Market-Oriented Cloud Computing: Vision, Hype, and Reality for
Delivering IT Services as Computing Utilities, Keynote Paper, Proceedings of the 10th IEEE International
Conference on High Performance Computing and Communications, Dalian, China, Sept. 25-27, 2008.
[3] Armbrust, M., Fox, A. et. al.: Above the Clouds: A Berkeley View of Cloud Computing. Technical Report No.
UCB/EECS-2009-28, University of California at Berkley, USA, Feb. 10, 2009.
[4] Buyya, R., Yeo, C.S., Venugopal, S., Broberg, J., and Brandic, I.: Cloud Computing and Emerging IT
Platforms: Vision, Hype, and Reality for Delivering Computing as the 5th Utility. Future Generation Computer
Systems, 25(6): 599-616, Elsevier Science, Amsterdam, The Netherlands, June 2009.
[5] London, S.: Inside Track: The high-tech rebels. Financial Times, Sept. 6, 2002.
[6] VMware: Migrate Virtual Machines with Zero Downtime. http://www.vmware.com/.
[7] Barham, P., Dragovic, B., Fraser, K., Hand, S., Harris, T., Ho, A., Neugebauer, R., Pratt, I., and Warfield, A.:
Xen and the Art of Virtualization. Proceedings of the 19th ACM
Symposium on Operating Systems Principles, ACM Press, New York, 2003.
[8] Broberg, J., Buyya, R., and Tari, Z.: MetaCDN: Harnessing 'Storage Clouds' for High Performance Content
Delivery, Journal of Network and Computer Applications, 32(5): 1012-1022, Elsevier, Amsterdam, The
Netherlands, Sept. 2009.
[9] Venugopal, S., Nadiminti, K., Gibbins, H., and Buyya, R.: Designing a Resource Broker for Heterogeneous
Grids, Software: Practice and Experience, 38(8):793-825, ISSN: 0038- 0644, Wiley Press, New York, USA, 2008.
35
References](https://image.slidesharecdn.com/cloudbuspresentationamitashish-141123083408-conversion-gate01/85/CloudBus-35-320.jpg)
![[10] Pandey, S., Voorsluys, W., Rahman, M., Buyya, R., Dobson, J., and Chiu, K.: A Grid Workflow Environment
for Brain Imaging Analysis on Distributed Systems, Concurrency and Computation: Practice and Experience,
Wiley Press, New York, USA, 2009.
[11] Pandey, S., Dobson, J.E., Voorsluys, W., Vecchiola, C., Karunamoorthy, D., Chu, X., and Buyya, R.:
Workflow Engine: fMRI Brain Image Analysis on Amazon EC2 and S3 Clouds, The Second IEEE International
Scalable Computing Challenge (SCALE 2009) in conjunction with CCGrid 2009, Shanghai, China, 2009.
[12] Pandey, S., Gupta, K.K., Barker, A., and Buyya, R.: Minimizing Cost when Using Globally Distributed Cloud
Services: A Case Study in Analysis of Intrusion Detection Workflow Application, Technical Report, CLOUDS-TR-
2009-6, Cloud Computing and Distributed Systems Laboratory, The University of Melbourne, Australia, Aug. 7,
2009.
[13] Garg, S.K., Venugopal, S., and Buyya, R.: A Meta-scheduler with Auction Based Resource Allocation for
Global Grids, Proceedings of the 14th IEEE International Conference on Parallel and Distributed Systems, IEEE
CS Press, Los Alamitos, USA, 2008.
[14] Garg, S.K., Buyya, R., Siegel, H.J.: Time and Cost Trade-off Management for Scheduling Parallel
Applications on Utility Grids, Future Generation Computer Systems, In Press, Available online 25 July 2009, DOI:
10.1016/j.future.2009.07.003.
[15] Assunção, Dias de, M., Buyya, and Venugopal, S.: InterGrid: A Case for Internetworking Islands of Grids,
Concurrency and Computation: Practice and Experience, vol 20, No. 8, pp. 997--1024, ISSN: 1532-0626, Wiley
Press, New York, USA, June 10, 2008.
[16] Kim, K.H., Buyya, R., and Kim, J.: Power Aware Scheduling of Bag-of-Tasks Applications with Deadline
Constraints on DVS-enabled Clusters, Proceedings of the 7th IEEE International Symposium on Cluster
Computing and the Grid (CCGrid), IEEE CS Press, Los Alamitos, CA, USA, 2007.
36
References](https://image.slidesharecdn.com/cloudbuspresentationamitashish-141123083408-conversion-gate01/85/CloudBus-36-320.jpg)
CloudBus
- 1. CSE – 530 CLOUD COMPUTING Paper Presentation
- 2. Cloudbus Toolkit for Market-Oriented Cloud Computing Authors: Rajkumar Buyya, Suraj Pandey and Christian Vecchiola Cloud Computing and Distributed Systems (CLOUDS) Laboratory Department of Computer Science and Software Engineering The University of Melbourne, Australia Published in: Proceedings of First International Conference, CloudCom 2009, Beijing, China, December 1-4, 2009. Presented by: Amit Kumar Nath (Ja-342) Ashish Kumar Chanda (Ja-343)
- 3. • Introduction • Cloud Computing • Cloudbus Vision & Architecture • Cloudbus Technologies • Related Technologies & Deployment • Future Trends • References 3 Overview
- 4. Introduction - Leonard Kleinrock (One of the chief scientists of the original ARPANET project which seeded the Internet) 4 “As of now, computer networks are still in their infancy, but as they grow up and become sophisticated, we will probably see the spread of ‘computer utilities’ which, like present electric and telephone utilities, will service individual homes and offices across the country” (1969)
- 5. Introduction (Cont’d.) • The vision of computing utilities, based on a service provisioning model, anticipated the massive transformation of the entire computing industry in the 21st century whereby computing services will be readily available on demand • Computing service users (consumers) need to pay providers only when they access computing services, without the need to invest heavily or encounter difficulties in building and maintaining complex IT infrastructure by themselves • Users access the services based on their requirements without regard to where the services are hosted • This model has been referred to as utility computing, or recently as Cloud computing 5
- 6. Introduction (Cont’d.) • “Cloud computing, the long-held dream of computing as a utility, has the potential to transform a large part of the IT industry, making software even more attractive as a service” - Berkeley Report (February 2009) • Clouds aim to power the next generation data centers by architecting them as a network of virtual services • Users are able to access and deploy applications from anywhere in the world on demand at competitive costs depending on their Quality of Service (QoS) requirements 6
- 7. Introduction (Cont’d.) • Cloud computing has high potential to provide infrastructure, services and capabilities required for harnessing business potential • It has been identified as one of the emerging technologies in IT as noted in ‘Gartner’s IT Hype Cycle’ • A ‘Hype Cycle’ is a way to represent the emergence, adoption, maturity and impact on applications of specific technologies 7
- 9. Cloud Computing • Armbrust et al. [3] observe that “Cloud computing refers to both the applications delivered as services over the Internet and the hardware and system software in the data centers that provide those services” • Buyya et al. [2] define Cloud as “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” 9
- 10. A Cloudy Story! 10 Before starting the formal presentation, I would like to share a small story. It’s a story with clouds in it, but no, it’s not like ‘Cloudy with a chance of Meatballs’! You can call it ‘A Cloudy Story’!
- 11. A Cloudy Story! (Cont’d.) • This is the story of Drew, who was a student of MIT • Drew repeatedly forgot his USB flash drive in MIT • Being irritated, Drew decided to solve this problem • Any guess what Drew did…….? 11
- 12. A Cloudy Story! (Cont’d.) 12
- 13. A Cloudy Story! (Cont’d.) • Our story does have a happy ending! • Drew became an Internet entrepreneur • He is best known for being the founder and CEO of Dropbox, an online backup and storage service • Drew rejected an offer from Steve Jobs to work keep working independently! • According to Forbes magazine, his net worth is $1.2 billion !!! 13
- 14. Cloud Computing (Cont’d.) 14
- 16. Cloud Computing Reference Model 16
- 17. Cloudbus Vision • A Cloud marketplace is composed of different types of Clouds such as computing, storage, and content delivery Clouds • The cloud marketplace will be available to end-users and enterprises • Users can interact with the Cloud market either transparently, by using applications that leverage the Cloud, or explicitly, by making resource requests according to application needs 17
- 18. Cloudbus Vision (Cont’d.) 18
- 19. Cloudbus Vision and Architecture • Cloud broker client will interact with the market maker by specifying the desired QoS parameters through an SLA • Meta-broker will select the best option available among all the cloud providers belonging to the cloud marketplace • Different Cloud providers could establish peering arrangements among themselves in order to offload to (or serve from) other providers’ service requests 19
- 20. Cloudbus Vision and Architecture (Cont’d.) • Peering arrangements will define a Cloud federation and foster the introduction of standard interface and policies for the interconnection of heterogeneous Clouds • Integration of different technologies and solutions into a single value offering will be the key to the success of the Cloud marketplace 20
- 22. 22 CloudBus Applications • Aneka • Broker • Workflow Management System • Market Marker/Meta Broker • InterGrid • MetaCDN • CloudSim
- 23. 23 Aneka • Aneka is a platform and a framework for developing distributed applications on the Cloud • Flexible design and high level of Customization • Web Services make Aneka completely integrate with client applications
- 24. 24 Aneka • A configurable software container constituting the building blocks of the Cloud • An open ended set of programming models available • A collection of tools for rapidly prototyping and porting applications to the cloud • A set of advanced services that put the horse power of Aneka in a market oriented perspective
- 25. 25 Architecture of Aneka
- 26. 26 • A cloud broker is a third-party individual or business that acts as an intermediary between the purchaser of a cloud computing service and the sellers of that service • Discovering suitable data sources for a given analysis scenario • Selecting suitable computational resources • Optimally mapping analysis jobs to compute resources • Deploying and monitoring job execution on selected resource Broker
- 27. 27 Workflow Management System • WMS aids user by enabling their applications to be represented as a workflow and then execute on the Cloud • It provides an XML-based workflow language • Example: fMRI brain image analysis, evolutionary multi-objective optimizations, intrusion detection systems
- 28. Market Maker/Meta broker • It works on behalf of both Cloud users and Cloud 28 service providers • It mediates access to distributed resources by discovering suitable Cloud providers • Services: resource discovery, meta-scheduler, reservation service, queuing service, accounting
- 29. Intergrid • Promote interlinking of islands of Clouds through 29 peering arrangements to enable inter Cloud resource sharing • Provide a scalable structure for Clouds that allow them to interconnect • Create a global Cyber infrastructure to support e-Science and e-Business applications
- 30. 30 MetaCDN • The system exploits “Storage Cloud” resources offered by multiple IaaS vendors • It removes the complexity of dealing with multiple storage providers • By using a single unified namespace, it helps users to harness the performance and coverage of numerous “Storage Clouds”
- 31. 31 Energy Efficient Computing • They develop a scheduling algorithm that select appropriate supply voltages of processing elements to minimize energy consumption • As energy consumption is optimized, operational cost decreases and the reliability of the system increases
- 32. 32 CloudSim • It enables users to model and simulate extensible Clouds as well as execute applications on top of Clouds • A completely customizable tool • Support for modeling and simulation of large scale Cloud computing infrastructure • A self-contained platform for modeling data centers, service brokers, scheduling, and allocations policies
- 33. 33 Related Tech. & Deployment • Amazon EC2, Eucalyptus, and OpenNebula • OpenPEX • GoFront, (fMRI), gene expression data classification
- 34. 34 Future Trends • Software licensing will be a major hurdle for vendors of Cloud services • Balancing usage cost and services delivered • Using renewable sources of energy to power up their centers • Keeping Cloud services alive and running for as long as it takes
- 35. [1] Kleinrock, L.: A Vision for the Internet. ST Journal of Research, vol. 2, Issue 1, pp. 4--5, November 2005. [2] Buyya, R., Yeo, C.S., and Venugopal, S.: Market-Oriented Cloud Computing: Vision, Hype, and Reality for Delivering IT Services as Computing Utilities, Keynote Paper, Proceedings of the 10th IEEE International Conference on High Performance Computing and Communications, Dalian, China, Sept. 25-27, 2008. [3] Armbrust, M., Fox, A. et. al.: Above the Clouds: A Berkeley View of Cloud Computing. Technical Report No. UCB/EECS-2009-28, University of California at Berkley, USA, Feb. 10, 2009. [4] Buyya, R., Yeo, C.S., Venugopal, S., Broberg, J., and Brandic, I.: Cloud Computing and Emerging IT Platforms: Vision, Hype, and Reality for Delivering Computing as the 5th Utility. Future Generation Computer Systems, 25(6): 599-616, Elsevier Science, Amsterdam, The Netherlands, June 2009. [5] London, S.: Inside Track: The high-tech rebels. Financial Times, Sept. 6, 2002. [6] VMware: Migrate Virtual Machines with Zero Downtime. http://www.vmware.com/. [7] Barham, P., Dragovic, B., Fraser, K., Hand, S., Harris, T., Ho, A., Neugebauer, R., Pratt, I., and Warfield, A.: Xen and the Art of Virtualization. Proceedings of the 19th ACM Symposium on Operating Systems Principles, ACM Press, New York, 2003. [8] Broberg, J., Buyya, R., and Tari, Z.: MetaCDN: Harnessing 'Storage Clouds' for High Performance Content Delivery, Journal of Network and Computer Applications, 32(5): 1012-1022, Elsevier, Amsterdam, The Netherlands, Sept. 2009. [9] Venugopal, S., Nadiminti, K., Gibbins, H., and Buyya, R.: Designing a Resource Broker for Heterogeneous Grids, Software: Practice and Experience, 38(8):793-825, ISSN: 0038- 0644, Wiley Press, New York, USA, 2008. 35 References
- 36. [10] Pandey, S., Voorsluys, W., Rahman, M., Buyya, R., Dobson, J., and Chiu, K.: A Grid Workflow Environment for Brain Imaging Analysis on Distributed Systems, Concurrency and Computation: Practice and Experience, Wiley Press, New York, USA, 2009. [11] Pandey, S., Dobson, J.E., Voorsluys, W., Vecchiola, C., Karunamoorthy, D., Chu, X., and Buyya, R.: Workflow Engine: fMRI Brain Image Analysis on Amazon EC2 and S3 Clouds, The Second IEEE International Scalable Computing Challenge (SCALE 2009) in conjunction with CCGrid 2009, Shanghai, China, 2009. [12] Pandey, S., Gupta, K.K., Barker, A., and Buyya, R.: Minimizing Cost when Using Globally Distributed Cloud Services: A Case Study in Analysis of Intrusion Detection Workflow Application, Technical Report, CLOUDS-TR- 2009-6, Cloud Computing and Distributed Systems Laboratory, The University of Melbourne, Australia, Aug. 7, 2009. [13] Garg, S.K., Venugopal, S., and Buyya, R.: A Meta-scheduler with Auction Based Resource Allocation for Global Grids, Proceedings of the 14th IEEE International Conference on Parallel and Distributed Systems, IEEE CS Press, Los Alamitos, USA, 2008. [14] Garg, S.K., Buyya, R., Siegel, H.J.: Time and Cost Trade-off Management for Scheduling Parallel Applications on Utility Grids, Future Generation Computer Systems, In Press, Available online 25 July 2009, DOI: 10.1016/j.future.2009.07.003. [15] Assunção, Dias de, M., Buyya, and Venugopal, S.: InterGrid: A Case for Internetworking Islands of Grids, Concurrency and Computation: Practice and Experience, vol 20, No. 8, pp. 997--1024, ISSN: 1532-0626, Wiley Press, New York, USA, June 10, 2008. [16] Kim, K.H., Buyya, R., and Kim, J.: Power Aware Scheduling of Bag-of-Tasks Applications with Deadline Constraints on DVS-enabled Clusters, Proceedings of the 7th IEEE International Symposium on Cluster Computing and the Grid (CCGrid), IEEE CS Press, Los Alamitos, CA, USA, 2007. 36 References
- 37. 37