dynamic load balancing over linux cloud

Dynamic Load Balancing

On Linux Private Cloud

Introduction .1

Load Balancing.2

Dynamic Load Balancing.3

Proposed Algorithm.4

Performance & Results Analysis.5

What done So Far.6

Overview

What’s Remaining 7

Programming Languages & References.8

Computing challenges to Businesses Modern IT providers will have to face the following challenges:

Hardware is Costly to ownCapacity Planning is complexBusiness agility is low

• Hardware is expensive

• Hardware requiresmaintenance

• Hardware needs to be replaced

• Hardware Becomes obsolete

• How many Servers required?

• How much CPU power?

• How much RAM ?

• How much Storage ?

• Loss of competitive edge

• Slow response tochanged IT

• Unchanged Traditional ITinfrastructure

• Resources cannot be modifieddynamically

What is the solution to

these challenges?

But What is Cloud

Computing?

Solution:- Cloud The only solution addressing all the business challenges

On demand, self- service, reliable, anywhere, any time and cost effective

You only pay for what you use

Respond instantly to changing IT

No need to buy, maintain & replace hardware

Eliminate all wastage by automatic capacity planning

Elastic Resources

Essential Characteristics of Cloud

Broad Networkaccess

On demand self service

Rapid elasticity

Measured service

Resource Planning

COMPUTINGCLOUD

Billing is metered and delivered as a

utility service

Capability to scale to cope with

fluctuating demands

Request driven pool of computing

resource.

Virtualized resources as a service to

businesses

Centralized Computing technology over the

Internet

Essential Characteristics

On demand, self- service, reliable, anywhere, any time and cost effective

This cloud model is composed of six essential characteristics, three service models and four deployment models

Did you know?

Cloud computing & Cloud Model Concept

This cloud model is composed of six essential characteristics, three service models and four deployment models

Source:- ESDS

“Cloud computing is a style of computing in which scalable and elastic IT-enabled capabilities are delivered as a service using Internet technologies”

- Gartner

The Cloud Model

Scaling in CloudVirtual machines within the cloud can expand and contract. This is called scaling.

UserUser User

Load Balancer

Virtual ServerVirtual Server Virtual Server

Virtual Server&

Policy Engine

Load Balancing

Important Factors consider while Developing Algo

• Collecting and managing System status information

• Estimation of load

• Comparision of load

• Performance of System

• Nature of work to be transferred

• Selection of hosts

1. Static Load Balancing.

• Priori Knowledge about the global status of distributed.

• Job resource requirements communication time are assumed

• Mapping of jobs to resources is not allowed to change after the load balancing has begun.2.Dynamic Load Balancing

• Based on the current sate of system.

• Tasks are allowed to move dynamically from an overloaded node to receive faster service

• Mapping of jobs to resources at any point of time.

Local Scheduling

1 2

3 Distributed Scheduling Policy

Load Distributing

Strategy

Determines how the CPU resources at a

single node is allocated among its resident processes

Distributes the system workload among the nodes through process

migration

4

• Process of reallocating VMs

• On another Host over the Network

• To improve both resource utilization and job response time

• Avoiding a situation where some nodes are heavily loaded while others are idle or doing little work

What is Load Balancing Type of Load Balancing

Optimize Performance

Reduce IT Capital

Expense

Reduce IT operational

expense

Increase Flexibility &

Uptime

Reduce Carbon

Footprint

Reduce Administration

overhead

Benefits from Load Balancing In Linux Cloud

This benefits pull more Business to live on cloud rather than on desktop

Five Phases of Dynamic Load Balancing

TaskMigration

Task Selection

Work Transfer Vector Calculation

Profitability Determination

Load Evaluation

VM that has CPU utilization is closer to the amount equal to Work Transfer Vector Calculation

This is done by transferring a VM from Heavily loaded to Lightly loaded band such that both system achieve a Moderately loaded band

Migration of virtual machine from one host to another if there exists one VM in Heavily loaded and one in Lightly band

All Host send load information to policy EnginePolicy Engine divide CPU utilization of host into 1.Lightly Loaded 2.Moderately Loaded3.Heavily Loaded Band

QEMU-KVM’s live migration feature is usedVirsh command is part of libvirt API

1

2

3

4

5

Policy Engine

Heart of load balancing algorithm.

Decides Every thing when to migrate

virtual

machines between hosts and runs as

normal virtual machine.

It can move itself to a different host like

any other virtual machine

Depending on load

1

2

367%

41%

Dynamic Load Balancing Algorithms & Flow chart

Bands of

CPU

Utilization

threshold = (α1+α2+α3+...+αn)/n mean = (αmin+αmax) / 2 diff = |threshold - mean|

if diff > 10 moderately loaded band = threshold ± diff

else moderately loaded band = threshold ± 10

where, αi= CPU usage of ith Host over a defined time in percentage and i =

1 to n

Calculation of moderate band:

•All VMs achieve or come into Moderately Load Band•WTVC = Threshold – CPU utilization of LLB host

Work Transfer Vector Calculation

•If there exists one VM in HLB and one LLB

Profitability Determination

1

4

2

3

KVM,QEMU Libvirt,NFS,NTP,SSH,CentOS7

Live Migration

Linux Cluster Up & Running

Modified CSLB AlgoPython,

Bash

1.Adaptive Distributed Load Balancing Algo.

2.Central Scheduler Load Balancing Algo (CSLB)

3.Modified CSLB

Implemetation Of Algo

Dynamic Load Balancing Algo

What’s Done So Far Project is decompose into following Phases

What’s Remaining User Interface to intract with the Software

4

Graphical User Interface

PERFORMANCE AND RESULTS ANALYSIS

OS:- Centos7,

CPU:- Intel i5-2400 3.1 GHz * 3,

Memory:- 3 GB

Dynamic Load Balancing Algorithm

Host 1 CPU Usage 42.4 %



S146.50

S29.60

S33.00

K148.50

K28.70

K323.80

A193.50

A224.80

A32.90





S146.50

S29.60

S33.00

K148.50

K28.70

K323.80

A193.50

A224.80

A32.90

MLB LLB HLB

MLB=Thres±10MLB

31.21 51.21

Threshold=41.21Mean=40.62Difference=0.58





S146.50

S29.60

S33.00

K148.50

K28.70

K323.80

A193.50

A224.80

A32.90

MLB LLB HLB


MLB=Thres±10MLB

31.21 51.21W.T.V.C = 22.14





S149.40

S210.10

S31.00

K149.00

K27.00

K324.50

A194.50

A223.40

A31.90





S149.40

S210.10

S31.00

K149.00

K27.00

K324.50

A194.50

A223.40

A31.90

MLB HLB LLB


MLB=Thres±10MLB

31.01 51.10





S149.40

S210.10

S31.00

K149.00

K27.00

K324.50

A194.50

A223.40

A31.90

MLBHLB

LLB


MLB=Thres±10MLB

31.01 51.10W.T.V.C = 12.10





S151.40

S210.40

S31.00

K146.10

K21.80

K325.10

A195.10

A251.90

A32.10





S151.40

S210.40

S31.00

K146.10

K21.80

K325.10

A195.10

A251.90

A32.10

MLBHLB

LLB


MLB=Thres±10MLB

31.16 50.16





S151.40

S210.40

S31.00

K146.10

K22.10

K325.10

A194.10

A251.90

A31.80

MLBHLB LLB


MLB=Thres±10MLB

31.16 50.16W.T.V.C = 12.85





S152.20

S210.60

S31.00

K141.80

K21.00

K324.70

A195.60

A261.90

A31.70





S152.20

S210.60

S31.00

K141.80

K21.00

K324.70

A195.60

A261.90

A31.70

MLB MLB MLB


MLB=Thres±10MLB

28.57 48.57

KVM Kernel Based Virtual Machine Red Hat, Inc. 2014.1

Ali M. Alakeel, A Guide to Dynamic Load Balancing in Distributed Computer 2

Terry C. Wilcox Jr, Dynamic Load Balancing Of Virtual Machines Hosted On Xen, Department

of Computer.3

Jyotiprakash Sahoo, Subasish Mohapatra, Radha Lath,Virtualization: A Survey On Concepts,

Taxonomy And Associated Security Issues, Second International Conference on Computer

and Network Technology, 2010.

4

Youran Lan, Ting Yu, A Dynamic Central Scheduler Load Balancing Mechanism, Computers

and Communications, pp 734-740, May 1995.5

Yi Zhao, Wenlong Huang, Adaptive Distributed Load Balancing Algorithm based on Live

Migration of Virtual Machines in Cloud, Fifth International Joint Conference INC.6

References :-

7

8

http://www.python.org/

http://www.riverbankcomputing.com/

dynamic load balancing over linux cloud

Documents

esds cloud computing

dynamic load balancing

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