Performance Evaluation of Load-Balancing Algorithms with Different Service Broker Policies for Cloud Computing
Source abstract
Abstract
Cloud computing has seen a major boom during the past few years. Many people have switched to cloud computing because traditional systems require complex resource distribution and cloud solutions are less expensive. Load balancing (LB) is one of the essential challenges in cloud computing used to balance the workload of cloud services. This research paper presents a performance evaluation of the existing load-balancing algorithms which are particle swarm optimization (PSO), round robin (RR), equally spread current execution (ESCE), and throttled load balancing. This study offers a detailed performance evaluation of various load-balancing algorithms by employing a cloud analyst platform. Efficiency concerning various service broker policy configurations for load-balancing algorithms’ virtual machine load balance was also calculated using metrics such as optimized response time (ORT), data center processing time (DCPT), virtual machine costs, data transfer costs, and total cost for different workloads and user bases. Many of the past papers that were mentioned in the literature worked on round robin and equally spread current execution, and throttled load-balancing algorithms were based on efficiency and response time in virtual machines without recognizing the relation between the task and the virtual machines, and the practical significance of the application. A comparison of specific load-balancing algorithms has been investigated. Different service broker policy (SBP) tests have been conducted to illustrate the load-balancing algorithm capabilities.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Cloud Computing and Resource Management · IoT and Edge/Fog Computing · Blockchain Technology Applications and Security
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Malaysian Institute of Information Technology, Universiti Kuala Lumpur, Kuala Lumpur 50250, Malaysia
Faculty of Computing, Riphah International University, Sector I-14, Hajj Complex, Islamabad 46000, Pakistan
School of Computer Science, University of Technology Sydney, 15 Broadway, Ultimo, NSW 2007, Australia
Persiaran Multimedia, Multimedia University, Cyberjaya 63100, Malaysia
Funding
Multimedia University, Persiaran Multimedia
References (53)
Show source-provided references
1. El Karadawy, A.I., Mawgoud, A.A., and Rady, H.M. (2020, January 8–9). An Empirical Analysis on Load Balancing and Service Broker Techniques using Cloud Analyst Simulator. Proceedings of the 2020 IEEE International Conference on Innovative Trends in Communication and Computer Engineering (ITCE), Aswan, Egypt.10.1109/ITCE48509.2020.9047753 ↗
2. Analysis of service broker and load balancing in cloud computing
3. Simulation of Dynamic Load Balancing Algorithms10.9756/BIJSESC.8061 ↗
4. Analysis of Load Balancing Algorithms using Cloud Analyst10.14257/ijgdc.2016.9.9.02 ↗
5. Performance evaluation of Load Balancing with Service Broker policies for various workloads in cloud computing
6. Satapathy, S.C., and Joshi, A. (2019). Information and Communication Technology for Intelligent Systems, Springer.10.1007/978-981-13-1742-2 ↗
7. A Variable Service Broker Routing Policy for data center selection in cloud analyst
8. Panda, B., Sharma, S., and Roy, N.R. (2018). Data Science and Analytics, Springer.10.1007/978-981-10-8527-7 ↗
9. Shakir, M.S., and Razzaque, E.A. (2017, January 19–21). Performance Comparison of Load Balancing Algorithms using Cloud Analyst in Cloud Computing. Proceedings of the 2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON), New York, NY, USA.10.1109/UEMCON.2017.8249108 ↗
10. Jain, A., and Kumar, R. (2016, January 25–26). A multi stage load balancing technique for cloud environment. Proceedings of the 2016 International Conference on Information Communication and Embedded Systems (ICICES), Chenai, India.10.1109/ICICES.2016.7518921 ↗
11. Cloud computing using load balancing and service broker policy for IT service: A taxonomy and survey10.1007/s12652-020-01747-z ↗
12. Cloud Analyst: An Insight of Service Broker Policy10.17148/IJARCCE.2015.4125 ↗
13. A new service broker algorithm optimizing the cost and response time for cloud computing10.1016/j.procs.2019.04.139 ↗
14. Efficient Service Broker Policy For Large-Scale Cloud Environments
15. Data Center Processing Time Evaluation of Service Broker Policies In A single Data Center
16. Mesbahi, M.R., Hashemi, M., and Rahmani, A.M. (2016, January 27–28). Performance evaluation and analysis of load balancing algorithms in cloud computing environments. Proceedings of the 2016 Second International Conference on Web Research (ICWR), Tehran, Iran.10.1109/ICWR.2016.7498459 ↗
17. A Review: Load balancing Algorithm Using Cloud Analyst Environment
18. Definition of Cloud Services Brokerage (CSB) (2021, June 29). Gartner Information Technology Glossary. In Gartner. Available online: https://www.gartner.com/en/information-technology/glossary/cloud-services-brokerage-csb.
19. CloudAnalyst: A Survey of Load Balancing Policies
20. (2020, December 28). Available online: https://shodhganga.inflibnet.ac.in/bitstream/10603/169324/15/15_chapter3.pdf.
21. Joshi, S., and Kumari, U. (2016, January 14–17). Load balancing in cloud computing: Challenges & issues. Proceedings of the 2016 2nd International Conference on Contemporary Computing and Informatics (IC3I), Greater Noida, India.10.1109/IC3I.2016.7917945 ↗
22. Kaneria, O., and Banyal, R.K. (2016, January 18–19). Analysis and improvement of load balancing in Cloud Computing. Proceedings of the 2016 International Conference on ICT in Business Industry & Government (ICTBIG), Indore, India.10.1109/ICTBIG.2016.7892711 ↗
23. A Comparative Survey on Various Load Balancing Techniques in Cloud Computing
24. Kumar, A., and Kalra, M. (2016, January 8–9). Load balancing in cloud data center using modified active monitoring load balancer. Proceedings of the 2016 International Conference on Advances in Computing, Communication, & Automation (ICACCA) (Spring), Dehradun, India.10.1109/ICACCA.2016.7578903 ↗
25. Panwar, R., and Mallick, B. (2015, January 8–10). Load balancing in cloud computing using dynamic load management algorithm. Proceedings of the 2015 International Conference on Green Computing and Internet of Things (ICGCIoT), Greater Noida, India.10.1109/ICGCIoT.2015.7380567 ↗
26. Farid, M., Latip, R., Hussin, M., and Abdul Hamid, N.A.W. (2020). A Survey on QoS Requirements Based on Particle Swarm Optimization Scheduling Techniques for Workflow Scheduling in Cloud Computing. Symmetry, 12.10.3390/sym12040551 ↗
27. Equally Spread Current Execution Load Algorithm—A Novel Approach for Improving Data Centre’s Performance in Cloud Computing
28. A Study on Cloud Simulation Tools
29. Comparison of Various Cloud Simulation tools available in Cloud Computing10.17148/IJARCCE.2015.4342 ↗
30. Dynamic provisioning of resources based on load balancing and service broker policy in cloud computing10.1007/s10586-019-02928-y ↗
31. Pant, M., Sharma, T.K., Verma, O.P., Singla, R., and Sikander, A. (2020). Soft Computing: Theories and Applications: Proceedings of SoCTA 2018, Springer.10.1007/978-981-15-0751-9 ↗
32. Singh, A., and Kumar, R. (2020, January 29–31). Performance Evaluation of Load Balancing Algorithms Using Cloud Analyst. Proceedings of the 2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence), Noida, India.10.1109/Confluence47617.2020.9058017 ↗
33. Sharma, H., Govindan, K., Poonia, R.C., Kumar, S., and Wael, M. (2020). Advances in Computing and Intelligent Systems: Proceedings of ICACM 2019, Springer.10.1007/978-981-15-0222-4 ↗
34. Adaptive user-oriented fuzzy-based service broker for cloud services
35. Differed service broker scheduling for data centres in cloud environment10.1016/j.comcom.2019.08.007 ↗
36. Arseniev, D.G., Overmeyer, L., Kälviäinen, H., and Katalinič, B. (2020). Cyber-Physical Systems and Control, Springer International Publishing.10.1007/978-3-030-34983-7 ↗
37. Challa, R.K., Dutta, M., and Kumar, R. (2019). Proceedings of 2nd International Conference on Communication, Computing and Networking: ICCCN 2018, NITTTR Chandigarh, India, Springer.
38. The New Service Brokering Policy for Cloud Computing Based on Optimization Techniques
39. A new efficient Virtual Machine load balancing Algorithm for a cloud computing environment
40. Analytical Study for Throttled and Proposed Throttled Algorithm of Load Balancing in Cloud Computing using Cloud Analyst
41. Mahalle, H.S., Tayde, S., and Kaveri, P.R. (2015, January 19–21). Implementing Service Broker Policies in Cloud Computing Enviroment. Proceedings of the 2015 International Conference on Communication Networks (ICCN), Gwalior, India.10.1109/ICCN.2015.37 ↗
42. Survey paper on cloud computing with load balancing policy
43. Khodar, A., Mager, V.E., Alkhayat, I., Al-Soudani, F.A., and Desyatirikova, E.N. (2020, January 27–30). Evaluation and Analysis of Service Broker Algorithms in Cloud-Analyst. Proceedings of the 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus), St. Petersburg, Russia.10.1109/EIConRus49466.2020.9039187 ↗
44. Cloud Computing Tools: Inside Views and Analysis10.1016/j.procs.2020.06.045 ↗
45. A Cost Efficient Service Broker Policy for Data Center Allocation in IaaS Cloud Model10.1007/s11277-020-07570-1 ↗
46. Performance analysis of nature inspired load balancing algorithm in cloud environment10.1007/s12652-019-01655-x ↗
47. (2021, June 11). The Best Open Source Cloud Computing Simulators. Available online: https://www.opensourceforu.com/2016/11/best-open-source-cloud-computing-simulators/.
48. Cloud Simulators—An Evaluation Study
49. Experimental comparison of simulation tools for efficient cloud and mobile cloud computing applications10.1186/s13635-016-0039-y ↗
50. A Comparative Analysis of Cloud Simulators10.5815/ijmecs.2016.04.08 ↗
51. Fakhfakh, F., Kacem, H.H., and Kacem, A.H. (2017, January 24–26). Simulation tools for cloud computing: A survey and comparative study. Proceedings of the 2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS), Wuhan, China.10.1109/ICIS.2017.7959997 ↗
52. A Comprehensive Study of Load Balancing Approaches in the Cloud Computing Environment and a Novel Fault Tolerance Approach10.1109/ACCESS.2020.3009184 ↗
53. Towards Resilient Method: An exhaustive survey of fault tolerance methods in the cloud computing environment10.1016/j.cosrev.2021.100398 ↗