Cloud computing in cloud computing environment (Monarch Butterfly Algorithm))
- 1. Optimization of Task Scheduling in Cloud Computing Environment Presented by: Ronak Bhoi Guided By: Assistant Professor, Mr. Debashreet das Institute: Sambalpur University Institute Of Information Technology 1
- 2. What is Cloud Computing • Cloud Computing refers to an infrastructure where both the data storage and data processing happen outside of the computing device. • CLOUD COMPUTING = MACHINE COMPUTING + CLOUD COMPUTING 2
- 3. What Cloud Computing DOES… • cloud applications move the computing power and data storage away from the mobile devices and into powerful and centralized computing platforms located in clouds, which are then accessed over the wireless connection based on a thin native client. 3
- 4. WHY DO WE NEED Cloud Computing ? • Mobile devices faces different resource problems, like Storage, Battery life etc… • Cloud computing offers advantages to users by allowing them to use infrastructure, platforms and software by cloud providers at low cost . • Cloud computing provides mobile users with data storage and processing services in clouds. 4
- 5. ADVANTAGES • Extending battery lifetime • Improving data storage capacity and processing power • Improving reliability and availability • Dynamic provisioning • Scalability • Ease of Integration 5
- 7. Issues With Cloud Computing • Communication issues: • Low bandwidth: One of the biggest issues, because the radio resource for wireless networks is much more scarce than wired networks • Service availability: Mobile users may not be able to connect to the cloud to obtain a service due to traffic congestion, network failures, mobile signal strength problems • Heterogeneity: Handling wireless connectivity with highly heterogeneous networks to satisfy Cloud Computing requirements (always-on connectivity, on-demand scalability, energy efficiency) is a difficult problem 7
- 8. Problem Statement • To reduce the total time (Makespan) and Cost required for task scheduling in Cloud Computing using Optimization Techniques. 8
- 9. Task Scheduling In Cloud Computing • The goal of scheduling is to map tasks to appropriate resources that optimize one or more objectives • There are Various kinds of algorithm for task scheduling are implemented • Examples- Particle Swarm Algorithm, Ant colony Optimization, BAT algorithm, Monarch Butterfly Algorithm. 9
- 10. Monarch Butterfly Optimization • MBO is an new evolutionary computation intelligent technique. • It mimics the migration behavior of the monarch butterflies in nature when the seasons change. • The entire population is divided into two parts according to the fitness, called subpopulation1 and subpopulation2. 10
- 11. MBO Cont. • Butterflies are insects have five senses (Smell, sight, taste, touch and hearing) they used these senses for immigration from one place to another. • When Butterfly moves from one place to another, it generates a fragrance with intensity which is propagate over the distance. • The other butterflies can sense this fragrance and attracted to the butterfly according to the intensity of fragrance. 11
- 12. Schematic flowchart of MBO 12
- 13. Output MAKESPAN TIME COST NO.OF VM-10 RAM-512MB 13
- 14. Conclusion From the values of output, I have obtained that the makespan time and cost is minimum for the Monarch Butterfly Optimization over the values of Particle Swarm Optimization and Ant colony Optimization. 14
- 15. Future Work • Reduce the makespan time and the cost with the algorithms by implementing hybrid methords to get more optimized results. • Implement the algorithm for other optimization factors like, Flow time, Cost, Tardiness etc. 15
- 16. References 1. Enhanced Particle Swarm Optimization For Task Scheduling In Cloud Computing Environments by -A.I.Awad, N.A.El-Hefnawy, H.M.Abdel kader (2015) 2. Mobile cloud computing: Challenges and future research directions. by-Talal H. Noor, Sherali Zeadally, Abdullah Alfazi, Quan Z. Sheng (2018) 3. A review Of metahuristic Sheduling Techniques in Cloud computing. By-Mala Kalra , Sarabjit Singh .(2015) 4. Task scheduling for cloud computing using multi-objective hybrid bacteria foraging algorithm. By-Sobhanayak Srichandan , Turuk Ashok Kumar , Sahoo Bibhudatta 5. Task Scheduling Using PSO Algorithm in Cloud Computing Environments, By- Ali Al-maamari and Fatma A. Omara 16
- 17. THANK YOU : ) Email- Ronak.bhoi@suiit.ac.in 17