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CIS6000 Paper Presentation: Mohammad Naeem School of Computer Science (SOSC) University of Guelph

Above the Clouds: A B erkley View of Cloud Computing Ambrust et al. RAD Lab (supported: google , amazon, microsoft , etc.). CIS6000 Paper Presentation: Mohammad Naeem School of Computer Science (SOSC) University of Guelph. g ist of the paper.

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CIS6000 Paper Presentation: Mohammad Naeem School of Computer Science (SOSC) University of Guelph

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  1. Above the Clouds: A Berkley View of Cloud ComputingAmbrust et al.RAD Lab (supported: google, amazon, microsoft, etc.) CIS6000 Paper Presentation: Mohammad Naeem School of Computer Science (SOSC) University of Guelph

  2. gist of the paper NO---Cloud Computing (CC) makes technical and economic sense there May be some issues though

  3. focal points • background • advantages • reasons for later/potential success • becoming cloud computing provider: guideline • moving to clouds: conditions for • utility computing: classes • cloud computing: economic of • moving to cloud : economics of • critical obstacles and opportunities • recommendations

  4. outline • utility computing (selling date center resources) • SaaS--- software as a service • The data center’s hardware and software as a cloud application software (simple software installation & m, control over versioning) data center = hardware+ system software

  5. [2]

  6. advantages • adding to the attractiveness of software service • availability of an abundant amount of hardware • under and over provisioning avoided • quick results (1000 computers working • on the same task simultaneously)

  7. conditions for moving to clouds • demand varies with time • (over-provisioning leads to under-utilization • of resources) • demand unknown in advance • (a web start-up needing to support a sudden spike • followed by a reduction in load) • cost-associativity in case of batch-analytic • (organizations that perform batch • analytics can use the cost associativity • of CC to finish the computation faster)

  8. types of utility computing

  9. types of utility computing Clean separation between storage And computation tier, automatic scalability and handling of failover highest-level lowest-level EC2-looks like physical hardware, users can control the entire software stack up the kernel • possibility of multilayered architecture with the • above stacked upon each other…

  10. reasons for later/potential success • hardware • illusion of infinite computing resources • elimination of upfront commitment by users • payment for resources on short-term basis • “past attempts failed because one or two • of these features were missing” • Intel Computing Services: • - contract, • - long-term use than per hour • EC2 --- sells • -1.0-GHs x 86 ISA slices for 10 cents per hour

  11. reasons for later/potential success • physical infrastructure • “large-scale commodity computer data • centers at low-cost location • 5 to 7 decrease in cost of” • Electricity • Network bandwidth • Operations • Software • Hardware • Coupled with statistical multiplexing

  12. reasons for later/potential success • large-scale commodity-computer data center • technology trends & new applications • mobile interactive applications • (real time services) • parallel batch processing • (batch-processing, analytic jobs) • business analytic • (growth of decision support processing) • computing-extensive desktop applications • (MATLAB, Mathematica) • earth-bound services • (analytic for long-term financial decisions)

  13. cloud computing: economic logic • CC has fine-grained economic model--- • so trade-off decisions flexible • CC can track changes in hardware cost and pass them • through to the customer

  14. cloud computing: economic logic • “converting capital cost to economic cost” • (cleverly) rephrased as • “you pay as you go” • economic sense of CC captured in two • fancy terms/concepts • elasticity • Transference of risk

  15. cloud computing: economic logic • elasticity • (in acquisition and de-acquisition of resources) • resource addition/removal at fine-grained level • so better matching of resources to workload--- • users do resource-provisioning for peek-utilization • with CC waste of idle resources avoidable--- • more effective tackling of over/under provisioning-

  16. Visitors receiving poor performance during the peak load • permanently lost

  17. cloud computing: economic logic • transference of risk • (risk of misestimating workload shifted from service • operator to cloud vendor) • the cloud vendor may charge a premium • (higher use cost per server-hour compared • to 3-years purchase cost)

  18. moving services to clouds: feasibility • pay separately per resource • (e.g., CPU-bounded jobs can benefit for paying for CPU separately) • power cooling & physical plant cost • (cost double when amortised over building life-time) • operations cost • (operations handled by the cloud, lower for managed environments)

  19. top 10 obstacles to cloud computing

  20. top 10 obstacles to cloud computing • Availability of service • multiple clouds --- wouldn’t this add to cost? • the complex calculations say • DDoS would cost the attacker more than • Until the attack last for 32 hours but then • it would be detected--- (kind of speculative)

  21. top 10 obstacles to cloud computing • data lock-in • APIs for CCs proprietary (i.e., not standardized yet)---so difficulty extracting data and programs from one site to run on another--- • solution: standardise APIs for clouds • “race-to-the-bottom” of cloud pricing flattening profit for CC providers- • authors arguments: quality of service, standardization of APIs enabling the use of same software for private as well as public clouds---

  22. top 10 obstacles to cloud computing • data confidentiality and auditability • CCs essentially use public networks so more exposed to attacks • lack of auditability and Accountability Act regulation in CCs • “my sensitive corporation data will never be in the cloud” • authors arguments: same measures e.g., encrypted storage, virtual local area network, and network middleboxes(firewalls, packet filters) as used in in-house IT environment can be employed---

  23. recommendations • scalability • VMs (horizontal scalability of VMs) • Application software (needs to rapidly scale-up as well scale- down, pay for use licensing model) • infrastructure software (needs to aware of running on VMs, billing built in from the beginning) • hardware systems • To be designed at the scale of container • Processors should work with VMs • Flash memory added • LAN/WAN switches/routers to be improved in bandwidth and cost

  24. critical review • overly optimistic/unrealistic • view/expectations of/from • CLOUD COMPUTING- • “how CC makes technical sense” aspect • not rigorously treated • Overestimation of economic benefit-probably no • real data available to back that up-

  25. references Armbrust et al., “Above the clouds: a Berkeley view of cloud computing”, 2009 Powell John, “Cloud computing: what it is and what it means for education” Vaquero et al., “A break in the clouds: towards a cloud definition”, CCR online http://www.youtube.com/watch?v=IJCxqoh5ep4

  26. Thanks

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