cloud computing(bit mesra kolkata extn.)

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)

• 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

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

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

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

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

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

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

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

Implementation of Proposed Load Balancing Approach through Interface 34

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

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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