simulation and performance analysis of a large scaled internet application (facebook) on cloud...

SIMULATION AND PERFORMANCE ANALYSIS OF

A LARGE SCALED INTERNET APPLICATION

(Facebook)ON CLOUD COMPUTING ENVIRONMENTS

CLOUD COMPPUTING

“…a style of computing in which dynamically scalable and often virtualized resourcesare provided as a service over the Internet.”

Deployment Models:

• Public

• Private

• Community

• Hybrid

Delivery Models:

• IaaS

• PaaS

• SaaS

ABOUT THE PROJECT

In this project we introduce a novel tool, CloudAnalyst, along with a new approach tosimulate a large-scaled applications on the Cloud with the purpose of studying thebehavior of such applications under various deployment configurations. Such a studywould benefit the application designers greatly in identifying the optimalconfiguration for their application. But more importantly such a study will generatevaluable insights in to designing Cloud infrastructure services in areas such ascoordination between Data Centers, load balancing algorithms andpossible valueadded services such as Service Brokers to coordinate between Data Centers tooptimize the application performance and cost to the owners.

CLOUD ANALYST

The CloudAnalyst is built on top of CloudSim tool kit, by extending CloudSimfunctionality with the introduction of concepts that model Internet and InternetApplication behaviors .

CloudSim toolkit covers most of the activities taking place within a Data Center in detail. This includes:

• Simulating Data Center hardware definition in terms of physical machines composed of processors, storage devices, memory and internal bandwidth

• Simulating virtual machine specification, creation and destruction

• The management of virtual machines, allocation of physical hardware resources for the operation of virtual machines based on different policies (e.g. time-shared and space-shared)

• Simulating the execution of user programs or requests (Cloudlet/Gridlet) on the virtual machines

SIMULATION OUTPUT/WHAT IS BEING MEASURED

• Response time of the simulated application

• The usage patterns of the application

• The time taken by data centers to service a user request

• The cost of operation

TECHNOLOGIES USED

• Java

• Java Swing

• CloudSim

TERMINOLOGY USED

• Region

• Internet

• Service Broker Request

• User Base

• Internet Cloudlet

• Data Center Controller

• VM Load Balancer

SERVICE BROKER ALGORITHM

• Service proximity based routing

• Performance based routing

• Dynamically Reconfigurable Routing

VM LOAD BALANCING ALGORITHM

• Round Robin

• Active Monitoring

• Throttled

SCENARIO 1.1.1Single data center located in Asia with service proximity algorithm forservice broker and round robin for VM load balancing

Avg (ms) Min (ms) Max (ms)

Overall Response Time 676.13 55.00 1862.84

Data Centre Processing Time 206.57 0.23 887.92

Overall Response Time Summary:

Response Time by Region:


Data Center Request Servicing Time:

Cost:

Data Center Avg (ms) Min (ms) Max (ms)

DC1 206.57 0.23 887.92

Total Virtual Machine Cost ($) 1.60

Total Data Transfer Cost ($) 1120.52

Grand Total ($) 1122.13

SCENARIO 1.1.2Single data center located in Asia with service proximity algorithm forservice broker and active monitoring for VM load balancing






SCENARIO 1.1.2Single data center located in Asia with service proximity algorithm forservice broker and active monitoring for VM load balancing


Cost:


DC1 206.57 0.23 889.74




SCENARIO 1.1.3Single data center located in Asia with service proximity algorithm forservice broker and throttled for VM load balancing






SCENARIO 1.1.3Single data center located in Asia with service proximity algorithm forservice broker and throttled for VM load balancing


Cost:


DC1 103.80 0.23 624.00




SCENARIO 1.2.1Single data center located in Asia with service optimum response timealgorithm for service broker and round robin for VM load balancing








Cost:


DC1 206.10 0.24 885.69




SCENARIO 1.2.2Single data center located in Asia with service optimum response timealgorithm for service broker and active monitoring for VM load balancing






SCENARIO 1.2.2Single data center located in Asia with optimum response time algorithm forservice broker and active monitoring for VM load balancing


Cost:


DC1 206.10 0.24 888.18




SCENARIO 1.2.3Single data center located in Asia with service optimum response timealgorithm for service broker and throttled for VM load balancing






SCENARIO 1.2.3Single data center located in Asia with optimum response time algorithm forservice broker and throttled for VM load balancing


Cost:


DC1 103.70 0.24 625.71




SCENARIO 2.1.1Each region has a data center with service proximity algorithm forservice broker and round robin for VM load balancing







Cost:




SCENARIO 2.1.2Each region has a data center with service proximity algorithm forservice broker and active monitoring for VM load balancing







Cost:




SCENARIO 2.1.3Each region has a data center with service proximity algorithm forservice broker and Throttledfor VM load balancing







Cost:




SCENARIO 2.2.1Each region has a data center with optimum response time algorithmfor service broker and round robin for VM load balancing







Cost:




SCENARIO 2.2.2Each region has a data center with optimum response time algorithmfor service broker and active monitoring for VM load balancing







Cost:




SCENARIO 2.2.3Each region has a data center with optimum response time algorithmfor service broker and throttled for VM load balancing







Cost:




SIMULATION RESULT SUMMARY :-

ANALYSIS OF OVERALL RESPONSE TIME

0

100

200

300

400

500

600

7005.2.1.1

5.2.1.2

5.2.1.3

5.2.2.1

5.2.2.2

5.2.2.3

5.3.1.1

5.3.1.2

5.3.1.3

5.3.2.1

5.3.2.2

5.3.2.3

SIMULATION RESULT SUMMARY :-

ANALYSIS OF DATA CENTRE PROCESSING TIME :

0

50

100

150

200

250

3005.2.1.1

5.2.1.2

5.2.1.3

5.2.2.1

5.2.2.2

5.2.2.3

5.3.1.1

5.3.1.2

5.3.1.3

5.3.2.1

5.3.2.2

THANK YOU