Review Presentation Scheduling in Cloud

1. Presentation By
Dr. Manjunath Kotari
Professor & Head-CSE
AIET, Moodbidre
Scheduling in Cloud Computing
01/20/191

2. Contents
Introduction
Traditional Cloud Scheduling
Job Scheduling Framework in Clouds
Dynamic Cloud Scheduling
Fault-Tolerant Scheduling in Cloud
Deadline-Constrained Dynamic Scheduling.
Inter-Cloud Meta-Scheduling
Conclusion
References
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3. Introduction
Cloud computing process the huge data.
Scheduling mechanism is essential.
Scheduling is at the heart of Distributed Computing.
PaaS model -> Workflow (job) Scheduling
IaaS model -> Virtual Machines (VM) Scheduling.
Scheduling decides allocation of VMs.
An effective scheduling can
Reduce operational costs
Reduce queue waiting time
Increase resource utilization
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4. Traditional Cloud Scheduling
FCFS
Simplest
Lower Headache
Fit for Small Size of data
No Starvation
Priority Queue Scheduling
Avoid starvation
Round Robin Scheduling
Time quantum is used
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5. Traditional Cloud Scheduling [cont..]
Shortest Job First Scheduling
Basis of shortest execution time
Multi Level Feedback Queue Scheduling
Use multiple queue with RR & FCFS.
Multi Level Queue Scheduling
Uses multiple queues with different scheduling.
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6. Job Scheduling Framework in Clouds
Challenges
Allocating massive job requests
Satisfying user QoS requirements.
Maintaining average response time
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7. Job Scheduling Framework
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8. Steps
User portal -manages job requests.
Job scheduler - routing decisions & selects VM instance.
Management module-
VM Monitor
Job monitor - keeps track of jobs
Job profiling - identify job types
History repository - stores the records of job .
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9. Dynamic Cloud Scheduling
Classification based on Historical data.
Creation of VMs
Matches tasks with suitable VMs dynamically
Minimize task waiting time and executing time.
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10. Cloud task scheduling framework
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11. Fault-Tolerant Scheduling in Cloud
Fault tolerance technique
Enhances Reliability and Availability
Introduce redundancy
Incurs extra overhead.
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12. Fault-tolerant scheduling architecture
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13. Steps
Global Scheduler
 Analyzes information
Makes decisions
Sends the primary/backup copies of the task to different VMs.
Local Scheduler
Rearranging the order of the local queue
Resource Manager
Decides how VMs should be added or migrated
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14. Deadline-Constrained Dynamic Scheduling
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15. Inter-Cloud Meta-Scheduling
Multiple autonomous clouds.
Functions under a single federated management entity.
The algorithm estimates the queue length of neighboring
processors
Reschedules the loads based on estimates.
The method aims to increase the possibilities to gain load
balancing.
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16. Inter-Cloud Meta-Scheduling
Facilitates scalable resource provisioning.
ICMS is based on a novel message exchange
mechanism.
Offers improved flexibility, robustness and
decentralization.
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17. Conclusions
Scheduling and execution improve service quality of the
clouds.
Creates VMs and decrease the failure rate of task
scheduling.
Increase in resource utilizations
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18. References
1. PeiYun Zhang, and MengChu Zhou, Dynamic Cloud Task Scheduling Based on
a Two-Stage Strategy, IEEE TRANSACTIONS ON AUTOMATION
SCIENCE AND ENGINEERING, VOL. 15, NO. 2, APRIL 2018.
2. YI WEI , LI PAN, SHIJUN LIU , LEI WU, AND XIANGXU MENG, DRL-
Scheduling: An Intelligent QoS-Aware Job Scheduling Framework for
Applications in Clouds, IEEE ACCESS, 2018.
3. PENGZE GUO, MING LIU1, JUN WU, ZHI XUE, AND XIANGJIAN HE,
Energy-Efficient Fault-Tolerant Scheduling Algorithm for Real-Time Tasks
in Cloud-Based 5G Networks, IEEE ACCESS ,2018.
4. Jyoti Sahni and Deo Prakash Vidyarthi, A Cost-Effective Deadline-
Constrained Dynamic Scheduling Algorithm for Scientific Workflows in a
Cloud Environment, IEEE TRANSACTIONS ON CLOUD COMPUTING,
VOL. 6, NO. 1, JANUARY-MARCH 2018.
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19. References [cont..]
5. Stelios Sotiriadis , Nik Bessis, Ashiq Anjum, and Rajkumar Buyya, An Inter-
Cloud Meta-Scheduling (ICMS) Simulation Framework: Architecture and
Evaluation, IEEE TRANSACTIONS ON SERVICES COMPUTING, VOL.
11, NO. 1, JANUARY/FEBRUARY 2018.
6. MIAN GUO, QUANSHENG GUAN, AND WENDE KE, Optimal Scheduling
of VMs in Queuing Cloud Computing Systems With a Heterogeneous
Workload, IEEE ACCESS 2018.
7. Ruiting Zhou , Zongpeng Li, and Chuan Wu,Scheduling Frameworks for Cloud
Container Services, IEEE/ACM TRANSACTIONS ON NETWORKING,
VOL. 26, NO. 1, FEBRUARY 2018
8. Arnav Wadhonkar , Deepti Theng ,A Survey on Different Scheduling
Algorithms in Cloud Computing, International Conference on Advances in
Electrical, Electronics, Information, Communication and Bio-Informatics
(AEEICB16).
01/20/1919