AN ANALYSIS OF IMPROVED DYNAMIC LOAD BALANCING ALGORITHM IN CLOUD COMPUTING ENVIRONMENT

International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

Abstract

One of the most crucial aspects of cloud computing in recent years has been regarded as load balancing. There are a lot more requests coming in quickly due to an increase in users worldwide. Global researchers have created a wide range of algorithms to process client requests at dispersed cloud servers. Accordingly, the cloud computing paradigm will automate server configuration for effective load balancing. Therefore, the load balancing method must be used to arrange the virtual machine selection process effectively. The availability of the virtual machine serves as the basis for the load balancing technique suggested in this work. Specifically, each virtual machine (VM) has its Availability Index (AI) value assessed over a predetermined duration; the AI value determines which work is assigned to that machine. Round Robin, Throttled, and Active Monitoring are three well-known load balancing algorithms that are compared with the suggested model in order to confirm its validity. With Cloud Analyst, the effectiveness of every algorithm was assessed. Comparing the suggested technique to alternative algorithms, simulation results demonstrate that it is more effective at load balancing between virtual machines.

References

[1] Chana, I., Singh, S.,"Quality of service and service level agreements for cloud environments: issues and challenges", In: Cloud Computing-Challenges, Limitations and R&D Solutions, pp. 51–72. Springer International Publishing, 2014.

[2] Buyya, Rajkumar, et al.,"Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility," Future Generation computer systems 25.6, pp. 599-616, 2009.
[3] Weerasiri, Denis, et al.,"A Taxonomy and Survey of Cloud Resource Orchestration Techniques." ACM Computing Surveys (CSUR) 50.2 (2017): 26. 

[4] García, A.G., Espert, I.B., García, V.H.,"SLA-driven dynamic cloud resource management", Futur. Gener. Comput. Syst. 31, pp. 1–11, 2014.

[5] Petcu, D.,"Consuming resources and services from multiple clouds", J. Grid Comput. 12(2), pp. 321–345, 2014.

[6] Singh, S., Chana, I.,"Formal Specification Language Based IaaS Cloud Workload Regression Analysis", arXiv preprint arXiv: 1402.3034. [Online] Available: http://arxiv.org/ftp/ arxiv/papers/1402/1402.3034.pdf (2014)

[7] Szabo, C., Sheng, Q.Z., Kroeger, T., Zhang, Y., Jian, Y.: Science in the cloud: Allocation and execution of data- intensive scientific workflows. J. Grid Comput. 12(2), pp. 245–264, 2014.

[8] García, A.G., Blanquer, I.,"Cloud services representation using SLA composition. J. Grid Comput. 13(1), pp. 35–51, 2015.

[9] Pascual, J.A., Lorido-Botrán, T., Miguel-Alonso, J., Lozano, J.A.,"Towards a greener cloud infrastructure management using optimized placement policies", J. Grid Comput. 13(3), pp. 375–389, 2015.

[10] Singh, S., Chana, I.,"QoS-aware autonomic resource management in cloud computing: A systematic review", ACM Comput. Surv. 48(3), 39, 2015.

[11] Singh, S., Chana, I., Buyya, R.,"Building and Offering Aneka- based Agriculture as a Cloud and Big Data Service", Big Data: Principles and Paradigms, pp. 1–25. Elsevier 2016.

[12] Nguyen, Nguyen Cong, et al.,"Resource management in cloud networking using economic analysis and pricing models: A survey." IEEE Communications Surveys & Tutorials (2017).

[13] Yousafzai, A., Gani, A., Noor, R. M., Sookhak, M., Talebian, H., Shiraz, M., Khan, M. K.,"Cloud resource allocation schemes: Review, taxonomy, and opportunities", Knowledge and Information Systems, 50(2), pp. 347-381, 2017.

[14] Kumar, C. Ashok, R. Vimala, KR Aravind Britto, S. Sathya Devi,"FDLA: Fractional dragonfly based load balancing algorithm in cluster cloud model." Cluster Computing 22, No. 1, pp. 1401-1414, 2019.

[15] Basu, Sayantani, G. Kannayaram, Somula Ramasubbareddy, C. Venkatasubbaiah, "Improved Genetic Algorithm for Monitoring of Virtual Machines in Cloud Environment." In Smart Intelligent Computing and Applications, pp. 319-326. Springer, Singapore, 2019.

[16] Bhandari, Anmol, Kiranbir Kaur,"An Enhanced Post- migration Algorithm for Dynamic Load Balancing in Cloud Computing Environment." In Proceedings of International Ethical Hacking Conference 2018, pp. 59-73. Springer, Singapore, 2019.

Keywords

Cloud Computing, Modified Throttled, Virtual Machine, Throttled Algorithm, Round-Robin Algorithm, Active Monitoring.