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Task Scheduling in Cloud Datacenter using genetic

algorithm

Presented by: Project Guide: Swathi R(1cg11is092) Mrs.Thara Dk Manasa V(1cg11is044) Asst. Professor Rekha M(1cg11is072) CIT, GubbiYashoda DN(1cg11is102)

Overview Introduction What is important in a Scheduling Algorithm? Need of scheduling Existing scheduling Algorithms Drawbacks of existing Algorithm Proposed system Genetic algorithm (GA)

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Introduction

What is Important in a Scheduling Algorithm?

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Need of Scheduling in cloud

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Existing system

Round robin algorithm

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Round Robin Scheduling Circular queue to store job. Task is based on slice of time. Context switch. Resources are utilized in balanced order.

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Drawbacks of Existing Algorithm

Largest job takes enough time for completion. The power consumption will be high as many

nodes will be kept turned-on for a long time.

There is an additional load on the scheduler to decide the size of quantum.

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Proposed System

• Genetic Algorithm.

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Genetic algorithm (GA) Search algorithms based on the mechanics of

natural selection and natural genetics

Based on the “survival of the fittest” concept (Darwinian theory)

Simulate the process of natural evolution

Central theme of research on genetic algorithm is “Robustness”

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Contd ..

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o Initial population

o Fitness function

o Selection

o Cross over

o Mutation

Data flow in genetic algorithm

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TASK ARRIVAL

NO YES

INITIAL POPULATION

SELECTION

CROSSOVER

MUTATION

VALUE > FITNESS

STOP THE PROCESS

Architecture

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Implementation

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Thank you. . . . ????