Load balancing in cloud
- 2. Cloud Computing • The practice of using a network of remote servers hosted on the Internet to store, manage, and process data, rather than a local server or a personal computer.
- 6. Challenges in Cloud Computing Security Efficient Load Balancing Performance Monitoring Consistent and Robust Service abstractions Resource Scheduling Scale and QoS management Requires a fast speed Internet connection
- 8. WHY? Resource Utilization Maximize Throughput Minimize Response Time Maintain system stability Cost effectiveness Scalability and flexibility Priority
- 9. Classification Load Balancing Algorithm Depending upon system state Static Dynamic Distributed Cooperative Non-cooperative Centralized Depending upon process initiator Sender Initiated Receiver Initiated Symmetric
- 10. Metrics Throughput Fault Tolerance Migration Time Response Time Scalability
- 11. Policies ● Information Policy ● Triggering Policy ● Transfer Policy ● Location Policy ● Selection Policy
- 12. Honeybee Foraging Behavior Nature-inspired algorithm for self-organization. Achieves global load balancing through local server actions. Performance of the system is enhanced with increased system diversity. Throughput is not increased with an increase in system size. Best suited for the conditions where the diverse population of service types is required.
- 14. Biased Random Sampling • Distributed and scalable. • Uses random sampling of the system domain to achieve self-organization. • Performance is improved with high and similar population of resources. • Performance is degraded with an increase in population diversity.
- 15. Active Clustering • Self-aggregation algorithm to optimize job assignments by connecting similar services using local re-wiring. • The performance of the system is enhanced with high resources thereby increasing the throughput. • Throughput degraded with an increase in system diversity.
- 16. Other Algorithms 1. Opportunistic Load Balancing: Attempt each node keep busy, therefore does not consider the present workload of each computer. 2. Compare and Balance: This algorithm is uses to reach an equilibrium condition and manage unbalanced systems load. 3. Round Robin: All the processes are divided between all processors in a round robin order. 4. Randomized: A process can be handled by a particular node n with a probability p.
- 17. Some Other Algorithms 5. Shortest Response Time First: Selects the job with the shortest (expected) processing time first. 6. Lock-free multiprocessing solution: Improves performance multicore environment by running multiple load-balancing processes in one load balancer. 7. Min-Min Algorithm. 8. Max-Min Algorithm.
- 18. Bibliography ● Mell, Peter and Grance, Tim, “The NIST definition of cloud computing”, National Institute of Standards and Technology, 2009,vol53, pages50, Mell2009. ● Haozheng Ren, Yihua Lan, and Chao Yin, “The Load Balancing Algorithm in Cloud Computing Environment”, IEEE, 2nd International Conference on Computer Science, China 2012. ● N. S. Raghava and Deepti Singh,” Comparative Study on Load Balancing Techniques in Cloud Computing” OPEN JOURNAL OF MOBILE COMPUTING AND CLOUD COMPUTING, In Press.
- 19. Thank You!