cloud computing(bit mesra kolkata extn.)
TRANSCRIPT
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Bit mesra ranchi,kolkata extn.Under The Guidance of:
Ajanta De Sarkar Soumya Ray
Presented By: Group No-24
Udita Chakarborty (MCA/3508/10)Ashutosh Kumar (MCA/3539/10)Puja Kumari (MCA/3543/10)Shashi Ranjan (MCA/3545/10)
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• Internet based computing
• Enables convenient on-demand network access to a shared pool of configurable computing resources e.g., networks, servers, storage, applications, and
services
• Virtualized computing platform
• Business Model
Cloud Computing
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Cloud Computing(cont..)• Cloud Infrastructure:
Public CloudPrivate Cloud
• Major cloud providers: Amazon Google Microsoft
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Some key aspects of cloud computing• on-demand network
• Scalable use of computing resources
• Pay-per-use concept
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Cloud Architecture• Consists of two component:
Front-end(or user-end)
Back-end
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Cloud Architecture(Cont..)
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Service levelsPLATFORMAS A SERVICE-Build on it
SOFTWAREAS A SERVICE-Consume it
INFRASTRUCTUREAS A SERVICE-Migrate to it
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Service Level Argreements
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Service Level Argreements(Cont..)• Negotiation between service provider and service
consumers
• Service integrator offers an end-to-end SLA to its service consumers
end-to-end SLA depends on the SLAs that the service integrator has with its service provider
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Users and their Roles • Four types of business roles:
A Cloud Service Consumer (CSC)
A Cloud Service Provider (CSP)
A Cloud Service Integrator (CSI)
A Cloud Service Broker (CSB)
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Advantages• Easy to maintain
• Easy access
• Ideal for small business
• Location independence
• Provides flexibility12
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Advantages (Cont..)• Scalable
• Cost-effective
• Energy-efficient
• Reliable
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Drawbacks• Possible downtime
• Security issues
• Other issues: Load Balancing
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Why we need load balancing??• The steady growth of the Internet
low response times
network congestion and
disruption of services
• For achieving Green computing in cloudsLimited Energy Consumption
Reducing Carbon Emission15
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Load Balancing
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Some key aspects of load balancing• Network Load Balancing or Server Load Balancing
• Reassigning load to each individual node
• Provided by dedicated software or hardware
e.g. multilayer switch ,DNS server etc.
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Some key aspects of load balancing (Cont..)• Make resource utilization effective
• Improve the response time
• Dynamic in nature
• Load of resources considered can be: CPU load, amount of memory used, delay or Network load
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Goals of load balancing• Availability
• To improve the performance substantially
• To maintain the system stability
• To accommodate future modification in the system
• Build a fault tolerant system by Creating backups19
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Types of load balancing algorithms • Depending on who initiated the process:
sender Initiatedreceiver InitiatedSymmetric
• Depending on the current state of the system:staticdynamic
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Usefulness of study of simulation • Creating and experimenting model of a physical system
• To test scenarios that might be particularly difficult or expensive
• Provide graphical applications
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Need of Simulators• Difficult to access exact cloud computing environment
• Easily mimicking cloud testbeds with different VMs
• To easily include modifications for complex scenario
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Types of SimulatorsGreenCloud
» Why?» Scenarios» Performance Measurement
iCanCloud» Why?» Scenarios» Performance Measurement
CloudSim » Why?» Scenarios» Performance Measurement
Comparison 23
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Scenarios
Scenario a: sole execution of sample application program
Scenario b: execution of sample application program with lightly loaded application
Scenario c: execution of sample program with heavily loaded application
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Why Green Cloud?1. A simulation environment
2. No provisioning for observing clouds for their energy efficiency
3. Offers a thorough investigation of workload distributions
4. Minimise energy consumption
5. Packet-level simulations of communications in the data center infrastructure
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Performance Evaluation Graph
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Why iCanCloud?• Used to simulate and model systems
•Optimizes the trade-off between cost and performance
• Lets the users to take an easy decision for paying corresponding budget of machines
• Provides flexibility, scalability, performance and usability
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Why iCanCloud?(Cont..)
• Customizable VMs can be used to quickly simulate uni-core/multi-core systems
• Provides a user-friendly GUI
• Conducts large experiment
• provides a flexible global hypervisor for integrating any cloud brokering policy
• reproduces the instance types provided by a given cloud infrastructure 28
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Performance Evaluation Graph
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Why CloudSim?• An extensible simulation toolkit that enables modelling
and simulation of Cloud computing systems and application provisioning environments.
• Can test the performance of a newly developed application service in a controlled and easy to set-up environment.
• Requires very less effort and time to implement Cloud-based application provisioning test environment
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Cont..
• Used for modelling and simulation of large scale computing
environments
• Facilitates simulation of federated cloud environment
• Supports simulation of network connections among the simulated
system elements
• Support for modelling and simulation of energy-aware
computational resources are also available
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Performance Evaluation Graph
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Comparison of Features
Parameters GreenCloud iCanCloud CloudSim
Platform NS2 OMNET,MPI _
Language C++/OTcl C++ Java
Availability Open Source Open Source Open Source
Graphical Support Limited(through Nam)
Full Limited(through CloudAnalyst)
Support for Power Consumption
Yes Yes WiP33
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Implementation of Proposed Load Balancing Approach through Interface 34
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Dynamic Information System
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Novel Load Balancing Approach • Cloud Provider (Windows) and Resource Provider (Linux)• “Top” command executed on Resource Provider• Getting the “Dynamic Resource Information ” into xml file• Connection established between Cloud Provider and Resource Provider through socket connection
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Novel Load Balancing Approach (Cont..)• Transferring xml file from Resource Provider to Cloud Provider• Cloud Provider checks xml file• Resource Table is maintained by the Cloud Provider
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Welcome Page
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Activities Page
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Simulators Page
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Performance Evaluation Graph of CloudSim
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Performance Evaluation Graph of GreenCloud
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Performance Evaluation Graph of iCanCloud
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Resource Information of R1
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Resource Information of R2
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Resource Information of R3
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Resource Table
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Conclusion• Concludes features, architectures and performance evaluation graph of different existing cloud simulators• Predict the outcome of each simulator under different scenarios• Compares the different simulators
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Conclusion(Cont..)• Future Work:
Improvement from the cloud consumer sides Service level agreements between cloud provider and cloud consumer
• Limitations:Message passing overheadA part of the Approach
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Reference1. Aarti Khetan, Vie Bhushan and Subhash Chand Gupta “A novel Survey on Load Balancing in Cloud Computing” International Journal of Engineering Research & Technology (IJERT) Vol. 2 Issue 2,February- 2013.
2. Anthony T.Velte, Toby J.Velte, Robert Elsenpeter, “Cloud Computing:A Practical Approach”, TATA McGRAW-HILL Edition 2010.
3. Dzmitry Kliazovich ,Pascal Bouvry and Samee Ullah Khan “GreenCloud: a packet-level simulator of energy-aware cloud computing 63 data centers” Springer Science+Business Media, LLC 2010 J Supercomput DOI 10.1007/s11227-010-0504-1.50
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Reference(Cont..)4. Kliazovich, D., Bouvry, P., Khan, S.U.: “iCanCloud: A Flexible and Scalable Cloud Infrastructure Simulator.” J Grid Computing (2012) 10:185–209 DOI 10.1007/s10723-012-9208-5.
5. Mell, P.; and Grance, T. (2009, 7 10). The NIST Definition of Cloud Computing, from NIST Information Technology Laboratory, http://www.nist.gov/itl/cloud/upload/cloud-def-v15.pdf,retrieved onApril 2011.
6. Syed A. Ahson, Mohamma “Cloud Computing and Software Services”.
7. www.google.co.in/imghp?hl=en&tab=wi
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YOU…..THANK
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