cloud computing project presentation

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EFFICIENT LIVE VM MIGRATION IN A CLOUD Pabba Praneeth B100864CS Y Sreenivasa Reddy B100825CS N Yaswanth B100976CS P Rakesh B100565CS Guided by : Mr. Saidalavi Kalady

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Cloud Computing Federated Cloud

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Page 1: Cloud Computing Project Presentation

EFFICIENT LIVE VM MIGRATION IN A CLOUD

Pabba Praneeth B100864CS

Y Sreenivasa Reddy B100825CS

N Yaswanth B100976CS

P Rakesh B100565CS

Guided by : Mr. Saidalavi Kalady

Page 2: Cloud Computing Project Presentation

Problem Statement

To simulate a federated cloud environment with dynamic load balancing by VM migration and simulation of real time cloud market scenario.

Page 3: Cloud Computing Project Presentation

Federated Cloud A Federated cloud is an interconnected group of diverse

interacting clouds with regulated configuration and features.

Clouds coordinate with each other to offer effective and seamless QoS levels in different geographic locations.

Sharply increased demand and demand at unreachable geographic frontiers could be effectively managed with coordination.

Page 4: Cloud Computing Project Presentation

VM Migration

Live VM Migration is the process of migrating a VM instance as one unit from one physical host to another host while continuously running it.

Advantages: Load balancing Fault management Energy cost savings in cloud Managing regionally distributed demand

Page 5: Cloud Computing Project Presentation

CloudSim CloudSim is a generalized and extensible Cloud Computing model

simulator

Primary uses:

For benchmark experiments in a repeatable, dependable and scalable environment

Tuning system bottlenecks before deploying in real time clouds

Various resource provisioning and application models tested with ease

Experiment failures only crash simulation causing no real world damages

Page 6: Cloud Computing Project Presentation

CloudSim – Features and limitations

Features:

Simulation of large cloud computing environments on a single physical node

Supports modelling of real world entities such as datacenters, brokers etc.

Cloud federation, SLA management and other core competencies can be modelled and simulated effectively

Real world topology and network delays in cloud induced using BRITE topology

Limitation:

Deploying real applications is NOT possible in CloudSim as it only a simulator and doesn’t execute real applications on cloud.

Page 7: Cloud Computing Project Presentation

CloudSim Architecture

Page 8: Cloud Computing Project Presentation

Proposed Design

Cloud 1 Cloud 2 Cloud 3

Cloud Coordinator

Resource Provider Agent

Resource Provider Agent

Resource Provider Agent

Resource Broker Agent

End User

Cloud Coordinator

Cloud Coordinator

Page 9: Cloud Computing Project Presentation

Analogous Terms and Definitions

In CloudSim In Real Time Definition

DataCenter Cloud Virtualization of resources

DataCenterBroker Resource Broker Agent Agent between user and the federated cloud

Cloudlet Application Service to be deployed

Task assigned to a cloud which has to be completed by a VM

FederatedDataCenter A cloud in federation <NA>

Host Physical host or server in cloud

Application or Data Server in cloud

EndUser (added) End user wishing to deploy VMs in a cloud

<NA>

Page 10: Cloud Computing Project Presentation

Design Implementation

Cloud 1 Cloud 2 Cloud 3

Cloud Coordinator

Resource Provider Agent

Resource Provider Agent

Resource Provider Agent

Resource Broker Agent

End User

Cloud Coordinator

Cloud Coordinator

EndUser

DataCenterBroker

CloudCoordinator

FederatedDataCente

r

Page 11: Cloud Computing Project Presentation

Implementation

Page 12: Cloud Computing Project Presentation

Implementation: Extended Class Diagram

Extended Class Diagram – Red classes added and blue classes modified in source code

Page 13: Cloud Computing Project Presentation

Addition of End User component End User component is added to the simulation specification layer in

CloudSim architecture.

Application requests (Cloudlets) and VM configuration form the basic requirement on end user side.

They are sent from EndUser to DataCenterBroker who packages all such requests and deploys them on best fit clouds.

FURTHER SCOPE: Billing to respective users based on usage and SLA management could be implemented by enhancing EndUser component.

Cloud Scenari

o

User Requirements

Application Configuratio

n

End User

User or DataCenterBroker

Page 14: Cloud Computing Project Presentation

Extension of VmAllocationPolicy VmAllocationPolicy is an abstract class which is responsible for

allocating VMs to different physical hosts in a cloud based on VM and Host configurations.

VmAllocationPolicy being abstract cannot be directly implemented and is extended by default VmAllocationPolicySimple of CloudSim.

VmAllocationPolicySimple allocates VM to host with least Pes (Processing entities) in use.

Our project extends VmAllocationPolicy to allocate VMs based on RAV (Resource Availability Vector) of a host.

Page 15: Cloud Computing Project Presentation

Resource Availability Vector Resource fraction vector is a vector with magnitude equal to ratio of

available resource to the total available resource on a host.

Every resource fraction vector is aligned in a dedicated direction.

Resource Availability Vector is the linear combination of all Resource fraction vectors of the host.𝑅𝐴𝑉=( ℎ ) +( ) +𝐵𝑎𝑛𝑑𝑤𝑖𝑑𝑡 𝐹𝑟𝑎𝑐𝑡𝑖𝑜𝑛 𝑖� 𝑅𝐴𝑀 𝐹𝑟𝑎𝑐𝑡𝑖𝑜𝑛 𝑗̂�

( ) 𝑃𝑟𝑜𝑐𝑒𝑠𝑠𝐹𝑟𝑎𝑐𝑡𝑖𝑜𝑛 𝑘̂� Here, Resource fraction vectors belong to bandwidth, RAM and Processing

power respectively.

All resources are taken at equal weightage in linear combination.

The host with maximum RAV magnitude gets the VM assigned.

Page 16: Cloud Computing Project Presentation

Why RAV???

The idea of availability vectors is used throughout the project.

RAV represents the utilization and availability of all resources without neglecting any resource used by a host.

Hence, scheduling decisions involving RAV tend to provide optimal performance metrics.

In case any resource needs greater importance, its weight in linear combination could be increased.

Page 17: Cloud Computing Project Presentation

Extension of CloudCoordinator

CloudCoordinator is the root component for a cloud in federation.

It maintains information about other clouds in the federation and forms a medium of communication for information and data interchange between clouds.

updateDataCenter() function polls all the resources of the cloud regularly to check if any host is overloaded or lightly loaded and is a target for VM migration.

migrate() function implements migration policy of VM from one cloud to another.

Page 18: Cloud Computing Project Presentation

migrate() in CloudCoordinator

migrate() already obtains overloaded Host from the sensors of the cloud it triggers.

In order to fix the target host for migration, it uses utilization vector similar to RAV as follows:𝑈𝑡𝑖𝑙𝑖𝑧𝑎𝑡𝑖𝑜𝑛=( ℎ ) + ( ) 𝐵𝑎𝑛𝑑𝑤𝑖𝑑𝑡 𝑛𝑜𝑟𝑚𝑎𝑙𝑖𝑠𝑒𝑑 𝑖� 𝑅𝐴𝑀 𝑛𝑜𝑟𝑚𝑎𝑙𝑖𝑠𝑒𝑑 𝑗̂�+ ( ) + ( ) 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑛𝑜𝑟𝑚𝑎𝑙𝑖𝑠𝑒𝑑 𝑘̂� 𝐼𝑛 𝑆𝑎𝑚𝑒 𝐷𝑎𝑡𝑎𝑐𝑒𝑛𝑡𝑒𝑟 𝑙�

Here, an extra flag In Same DataCenter is added to check if host under consideration in within the same cloud.

Flag is assigned 0 if host is within same cloud and 1 otherwise.

This decision is taken based on overweighing migration overhead costs and exchange costs for migration of VM between different clouds in federation.

Decision policy is similar to “ Child is better off with mother rather than a caretaker.”

Page 19: Cloud Computing Project Presentation

Final step of migrate()

Once target host is set in migrate() , we need to find the VM from overloaded to target host for migration.

The most heavyweight VM is found and migrated to restore balance in load as follows:

𝑉𝑀 𝑉𝑒𝑐𝑡𝑜𝑟=( ℎ) +( ) +( 𝐵𝑎𝑛𝑑𝑤𝑖𝑑𝑡 𝑖� 𝑅𝐴𝑀 𝑗̂� 𝑃𝑟𝑜𝑐𝑒𝑠𝑠𝑖𝑛𝑔) 𝑃𝑜𝑤𝑒𝑟 𝑘̂�

The final step of migrate() is performed by invoking send() or sendNow() function of SimEntity core class of CloudSim.

Page 20: Cloud Computing Project Presentation

Creation of Sensors

A sensor is a entity that responds to a certain input from a physical or intellectual environment.

Sensors are used in clouds to detect abnormal resource usages in clouds and respond accordingly.

Sensor is implemented as an interface in CloudSim.

Our work extends Sensor to create 3 sensors : BWSensor, RAMSensor and ProcessSensor to monitor bandwidth, RAM and Processing power respectively.

Page 21: Cloud Computing Project Presentation

Working and use of Sensors

Sensors have lower and upper thresholds as set values.

monitor() function of a sensor monitors utilization of all physical components if usage moves beyond range specified by thresholds.

In case of an abnormality, sensor reports it appropriate return value: +1 overutilization and -1 for underutilization.

monitor() of all sensors is invoked by updateDataCenter() of each cloud regularly.

Page 22: Cloud Computing Project Presentation

Working model of Implementation

Cloud 1 Cloud 2

Page 23: Cloud Computing Project Presentation

Thank You