An Advance Algorithm for Task Management On Activity Based Costing in Cloud Computing By : Ashutosh Ingole Sumit Chavan Rajesh Singh Sinhgad Institute.

An Advance Algorithm for An Advance Algorithm for Task Management On Task Management On

Activity Based Costing in Activity Based Costing in Cloud ComputingCloud Computing

By : Ashutosh Ingole Sumit ChavanRajesh Singh

Sinhgad Institute of Technology ,LONAVALA 19th Apr 2012

Contents

IntroductionCloud Computing ArchitectureProblem Statement

Problems

Overall Scenario

Flow of Algorithm

Cost calculation and SchedulingFeedback Mechanism

Advantages

Conclusion and References

19th Apr 2012Sinhgad Institute of Technology ,LONAVALA

IntroductionIntroduction

Sinhgad Institute of Technology ,LONAVALA 19th Apr 2012

What is Cloud Computing?What is Cloud Computing?• Shared computing resourcesShared computing resources• As opposed to local servers and devicesAs opposed to local servers and devices• Made up of Grid InfrastructureMade up of Grid Infrastructure• ScalableScalable• VirtualizationVirtualization• Web applicationsWeb applications• Specialized raw computing servicesSpecialized raw computing services

Technical Key PointsTechnical Key Points• User interaction interface:User interaction interface: How users of cloud interface with the cloudHow users of cloud interface with the cloud• Services catalog:Services catalog: Services a user can requestServices a user can request• System management: System management: Manages the resources availableManages the resources available• Provisioning tool: Provisioning tool: Carves out the systems from the cloud to deliver on the Carves out the systems from the cloud to deliver on the

requested servicerequested service• Monitoring and metering:Monitoring and metering: Tracks the usage of the cloud (optional)Tracks the usage of the cloud (optional)• Servers:Servers: Virtual or physical servers managed by System managementVirtual or physical servers managed by System management

Cloud Computing Architecture Cloud Computing Architecture

19th Apr 2012 Sinhgad Institute of Technology ,LONAVALA

Problem StatementProblem Statement

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To reduce the total time required for task scheduling in To reduce the total time required for task scheduling in

Cloud Computing using Activity Based Costing AlgorithmCloud Computing using Activity Based Costing Algorithm

19th Apr 2012

KeywordsKeywords

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• Cloud ComputingCloud Computing

• Task ManagementTask Management

• Activity Based CostingActivity Based Costing

• Advance AlgorithmAdvance Algorithm

19th Apr 2012

Overall ScenarioOverall Scenario

$4

$1

$2

Dynamic Priority

Allocator

Queue 1

Queue 2

Queue 3

Cost Calculation

Decide Priority

According To Cost

Virtual Machines

Scheduling Server

19th Apr 2012Sinhgad Institute of Technology ,LONAVALA

Flow of AlgorithmFlow of Algorithm

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Dependencies and DAGDependencies and DAG

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• Get the Activity dependencies form Task divider module.Get the Activity dependencies form Task divider module.• Calculate the DAG from the given information.Calculate the DAG from the given information.• According to the DAG fill up the Task queue.According to the DAG fill up the Task queue.• An Activity only starts after all its immediate predecessors finish.An Activity only starts after all its immediate predecessors finish.• Activities with no immediate predecessor are entry-activities, and Activities with no immediate predecessor are entry-activities, and

activities without immediate successors are exit-activities.activities without immediate successors are exit-activities.

T1

T3

T2

T4

T1 T3 T2 T4

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Cost calculation of Cost calculation of TaskTask

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Parameters consideredParameters considered

• Resource costResource cost• Arrival TimeArrival Time• Predicted Execution TimePredicted Execution Time• Dependency (DAG)Dependency (DAG)

19th Apr 2012

Continued… (Formulae)Continued… (Formulae)

Sinhgad Institute of Technology ,LONAVALA 19th Apr 2012

1)Resource Cost Evaluation

2)Estimated Execution Time

Where,Tij: estimated execution time for ith activity of jth taskTj: estimated execution time for complete jth taskKj: total number of activities in jth task

Continued… (Formulae)Continued… (Formulae)

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Total cost of Activity =Total cost of Activity =

19th Apr 2012

∑ (∑ Resource cost for a single activity) * execution time

Total cost of Task =Total cost of Task = ∑ (Activity Cost)

Concept of Waiting QueueConcept of Waiting Queue

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• In case of dependent activities, if a certain activity say A11 needs server1 and its dependent activity say A12 needs to be on server2, then without complete execution of A11, we cant forward A12 from ready queue to server2.

• In such a case, we also cant keep a2 in ready queue for a long time and hence we use waiting queue to store these kind of dependent activities

Waiting QueueWaiting Queue

Ready QueueReady Queue

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A22 A34 A52 A62 ….

A51 A61 ….A12 A31 A32 A33

Feedback and UpdateFeedback and Update

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• When we get feedback from server that a particular activity is When we get feedback from server that a particular activity is completed then we can schedule its dependent activity from completed then we can schedule its dependent activity from waiting queue to its destination server.waiting queue to its destination server.

• After that each resource table and universal resource table gets After that each resource table and universal resource table gets updated.updated.

19th Apr 2012

Waiting QueueWaiting QueueA22 A34 A52 A62 ….

Failure CasesFailure Cases

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• Simulation parameters• Average bounded slowdown and average per-processor slowdown• Average waiting time & average weighted waiting time• Network Error• Computational Error• Power Failure• Queue Overflow

19th Apr 2012

ConclusionConclusion

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An ABC-system of low complexity, such as a system with a small number An ABC-system of low complexity, such as a system with a small number of cost drivers, is not only easier to handle but also easier to understand. of cost drivers, is not only easier to handle but also easier to understand.

It seems to be an interesting next step to analyze how ABC decision rules It seems to be an interesting next step to analyze how ABC decision rules perform when several approximations apply.perform when several approximations apply.

Thus ABC reduces the scheduling cost and reduces delays.Thus ABC reduces the scheduling cost and reduces delays.

19th Apr 2012

ReferencesReferences

Sinhgad Institute of Technology ,LONAVALA 19th Apr 2012

Sandeep Tayal, University School of Information Technology, Guru Gobind Singh, Indraprastha University, Delhi- 10006, India “Tasks Scheduling optimization for the Cloud Computing System2011, IJAEST,2011 Archana Ganapathi, Yanpei Chen, Armando Fox, Randy Katz, David Patterson Computer Science Division, University of California at Berkeley,” Statistics-Driven Workload Modeling for the Cloud”, IEEE 2011 QI CAO, ZHI-BO WEI, WEN-MAO GONG International School of Software Wuhan University Wuhan, China, “An Optimized Algorithm for Task Scheduling Based On Activity Based Costing in Cloud Computing”, IEEE 2009 Jinhua Hu, Jianhua Gu, Guofei Sun, Tianhai Zhao, NPU HPC Center Xi‟an, China “A Scheduling Strategy on Load Balancing of Virtual Machine Resources in Cloud Computing Environment”, IEEE 2010 Jiahui Jin, Junzhou Luo, Aibo Song, Fang Dong and Runqun Xiong School of Computer Science and Engineering, Southeast University Nanjing, P.R. China “BAR: An Efficient Data Locality Driven Task Scheduling Algorithm for Cloud Computing” , IEEE 2011 GAN Guo-ning, HUANG Ting-Iei, GAO Shuai School of Computer science and engineering Guilin University of Electronic Technology Guilin, China “Genetic Simulated Annealing Algorithm for Task Scheduling based on Cloud Computing Environment”, IEEE 2010

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Any Questions…???

19th Apr 2012Sinhgad Institute of Technology ,LONAVALA

Thank You…!!!

19th Apr 2012Sinhgad Institute of Technology ,LONAVALA