A Review of Scheduling and Resource Allocation Algorithms with a Load Balancing Approach in Cloud Computing

الموضوعات : Majlesi Journal of Telecommunication Devices

Yaser Ramzanpoor ¹ (Department of Computer Engineering, Qaemshahr Branch,Islamic Azad University, Qaemshahr, Iran)

تاريخ الإرسال : 16 الأربعاء , شعبان, 1444 تاريخ التأكيد : 30 السبت , شوال, 1444 تاريخ الإصدار : 12 الخميس , ذو القعدة, 1444

الکلمات المفتاحية: Resource allocation, Load balancing, Scheduling, cloud computing,

ملخص المقالة :

Cloud computing is a distributed environment for providing services over the Internet. Load balancing of computing resources has emerged as a crucial element in this industry as a result of the expanding use of cloud computing and the expectations of customers to receive more services and better outcomes. The workload and system behavior of cloud computing are quite dynamic. And this can cause the resources in the data center to be overloaded. Ultimately, a load imbalance in some data center resources could result in increased energy use, decreased performance, and resource waste. Response time, expense, throughput, performance, and resource usage are among the quality of service indicators that load balancing can enhance. In this article, we analyze and evaluate scheduling and resource allocation methods with a view to load balancing, review the most recent approaches, and give a classification of these algorithms. Also, several significant problems and difficulties with cloud load balancing will be discussed in an upcoming study to create new algorithms.

المصادر:

A. Botta, W. De Donato, V. Persico and A. Pescap, "Integration of Cloud computing and Internet of Things: A survey," Future Generation Computer Systems , vol. 56, pp. 684-700, 2016.

S. Distefano, G. Merlino and A. Puliafito, "A utility paradigm for IoT:The sensing cloud," Pervasive and Mobile Computing, vol. 20, pp. 127-144, Jul. 2015.

O. Diallo, J. J. P. C. Rodrigues, M. Sene and J. Niu, "Real-time query processing optimization for cloud-based wireless body area networks," Information Sciences, vol. 284, pp. 84-94, 2014.

T. DeStefano, R. Kneller and J. Timmis, "Cloud Computing and Firm Growth," 2020. [Online]. Available: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3618829. [Accessed 15 July 2021].

Y. Chen, X. Li and F. Chen, "Overview and analysis of cloud computing research and application," in International Conference on E-Business and E-Government (ICEE), Shanghai, China, 6–8 May 2011.

K. Rajwinder and P. Luthra, "Load balancing in cloud computing," in International Conference on Recent Trends in Information, Telecommunication and Computing(ITC), 2012.

R. R. Malladi, "An approach to load balancing in cloud computing," international journal of research in engineering and technology, vol. 4, no. 5, pp. 3769-3777, 2015.

Y. Jadeja and K. Modi, "Cloud Computing - Concepts, Architecture and Challenges," in International Conference on Computing, Electronics and Electrical Technologies[ICCEET], 2012.

S. Goyal and M. .. K. Verma, "Load balancing techniques in cloud computing environment: a review," international journal of advanced research in computer science and software engineering, vol. 6, no. 4, 2016.

P. Singh, P. Baaga and S. Gupta, "Assorted load-balancing algorithms in cloud computing: a survey," International Journal of Computer Applications, vol. 143, no. 7, 2016.

Y. W. Tin, T. L. Wei, S. L. Yu, S. L. Yih, L. C. Hung and S. H. Jhih, "Dynamic load balancing mechanism based on cloud storage," in IEEE International Conference on Computing, Communications and Applications, 2012.

I. Foster, Y. Zhao, I. Raicu and S. Lu, "Cloud Computing and Grid Computing 360-degree compared," in Grid Computing Environments Workshop, 2008.

R. Soumya and D. S. Ajanta, "Execution analysis of load balancing algorithms in cloud computing environment," International Journal on Cloud Computing: Services and Architecture, vol. 2, no. 5, pp. 1-13, 2012.

M. Noshy, A. Ibrahim and H. A. Ali, "Optimization of live virtual machine migration in cloud computing: a survey and future directions," Journal of Network and Computer Applications, pp. 1-10, 2018.

L. Gkatzikis and I. Koutsopoulos, "Migrate or not? Exploiting dynamic task migration in mobile cloud computing systems," IEEE Wireless Communications, vol. 20, no. 3, pp. 24-32, 2013.

P. Jamshidi, A. Ahmad and C. Pahl, "Cloud migration research: a systematic review," IEEE Transactions on Cloud Computing, vol. 1, no. 2, pp. 142-157, 2013.

E. Shamsinezhad, A. Shahbahrami, A. Hedayati, A. K. Zadeh and H. Banirostam, "Presentation methods for task migration in cloud computing by combination of Yu router and post-copy," International Journal of Computer Science Issues, vol. 10, no. 4, 2013.

S. K. Mishra, D. Puthal, B. Sahoo, S. K. Jena and M. S. Obaidat, "An adaptive task allocation technique for green cloud computing," Journal of Supercomputing, pp. 1-16, 2017.

A. H. Ibrahim, H. E. D. M. Faheem, Y. B. Mahdy and A. R. Hedar, "Resource allocation algorithm for GPUs in a private cloud," International Journal of Cloud Computing, vol. 5, no. 1, pp. 45-56, 2016.

M. Jebalia, L. A. Ben, M. Hamdi and S. Tabbane, "An overview on coalitional game-theoretic approaches for resource allocation in cloud computing architectures," International Journal of Cloud Computing, vol. 4, no. 1, p. 63–77, 2015.

F. Z. Ling, V. Bharadwaj and Y. Z. Albert, "An integrated task computation and data management scheduling strategy for workflow applications in cloud environments," Journal of Network and Computer Applications, vol. 50, pp. 39-48, 2015.

B. Aditya and R. K. Challa, "Efficient multistage bandwidth allocation technique for virtual machine migration in cloud computing," Journal of Intelligent & Fuzzy Systems, vol. 36, pp. 1-14, 2018.

L. C. Shang, Y. C. Yun and H. K. Suang, "CLB: A novel load balancing architecture and algorithm for cloud services," Computers and Electrical Engineering, vol. 58, p. 154–160, 2017.

A. S. Milani and N. J. Navimipour, "Load balancing mechanisms and techniques in the cloud environments: systematic literature review and future trends," International Journal of Cloud Computing, vol. 71, pp. 86-98, 2016.

M. M. Abdullahi, N. M. A. Asri and S. M. Abdulhamid, "Symbiotic organism search optimization based task scheduling in cloud computing environment," Future Generation Computer Systems, vol. 56, pp. 640-650, 2015.

Y. D. Eman and M. Y. Shyan, "A small world based overlay network for improving dynamic loadbalancing," Journal of Systems & Software, vol. 107, p. 187–203, 2015.

F. Ramezani, L. Jie and K. H. Farookh, "Task-based system load balancing in cloud computing using particle swarm optimization," International Journal of Parallel Programming, vol. 42, no. 5, p. 739–754, 2014.

M. Abdolhamid, M. Shafi’i and M. B. Bashir, "Scheduling techniques in on-demand grid as a service cloud: a review," Journal of Theoretical and Applied Information Technology, vol. 63, no. 1, pp. 10-19, 2014.

T. K. Ravi and K. R. Vuyyuru, "Performance analysis of load balancing techniques in cloud computing environment," in IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT’15), 2015.

S. Kumar and D. H. Rana, "Various dynamic load-balancing algorithms in cloud environment: a survey," International Journal of Computer Applications, vol. 129, no. 6, 2015.

B. Kruekaew and W. Kimpan, "Multi-Objective Task Scheduling Optimization for Load Balancing in Cloud Computing Environment Using Hybrid Artificial Bee Colony Algorithm With Reinforcement Learning," IEEE Access, vol. 10, pp. 17803-17818, 2022.

D. A. Shafiq, N. Z. Jhanjhi, A. Abdullah and M. A. Alzain, "A Load Balancing Algorithm for the Data Centres to Optimize Cloud Computing Applications," IEEE Access, vol. 9, pp. 41731-41744, 2021.

A. Semmoud, M. Hakem, B. Benmammar and J. Charr, "Load balancing in cloud computing environments based on adaptive starvation threshold," Concurrency and Computation: Practice and Experience, vol. 32, no. 11, pp. 1-14, 2020.

S. Anuradha and P. Kanmani, "fault tolerant load balancing with quadruple osmotic hybrid classifier and whale optimization for cloud computing," Scalable Computing: Practice and Experience, vol. 23, no. 4, p. 321–338, 2022.

M. Kumar and S. C. Sharma, "Dynamic load balancing algorithm for balancing the workload among virtual machine in cloud computing," in Computer Science 115, 2017.

M. Adhikari and T. Amgoth, "Heuristic-based load-balancing algorithm for IaaS cloud," Future Generation Computer Systems, vol. 81, pp. 156-165, 2018.

S. S. Rajput and V. S. Kushwah, "A genetic based improved load balanced min-min task scheduling algorithm for load balancing in cloud computing," in 8th international conference on Computational Intelligence and Communication Networks (CICN), 2016.

L. Tang, Z. Li, P. Ren, J. Pan, Z. Lu, J. Su and Z. Meng, "Online and offline based load balance algorithm in cloud computing," Knowledge-Based Systems, vol. 138, pp. 91-104, 2017.

M. Vanitha and P. Marikkannu, "Effective resource utilization in cloud environment through a dynamic well-organized load balancing algorithm for virtual machines," Computers and Electrical Engineering, vol. 57, p. 199–208, 2017.

S. K. Vasudevan, S. Anandaram, A. J. Menon and A. Aravinth, "A novel improved honey bee based load balancing technique in cloud computing environment," Asian Journal of Information Technology, vol. 15, no. 9, p. 1425–1430, 2016.

S. Sharma, A. K. Luhach and S. S. Abdhullah, "An optimal load balancing technique for cloud computing environment using bat algorithm," indian journal of science and technology, vol. 9, no. 28, 2016.

A. M. Tripathi and S. Singh, "PMAMA: priority-based modified active monitoring load balancing algorithm in cloud computing," Journal of Advanced Research in Dynamical and Control Systems, pp. 809-823, 2018.

A. N. Singh and S. Prakash, "WAMLB: weighted active monitoring load balancing in cloud computing," in Aggarwal, V., Bhatnagar, V., Mishra, D. (eds) Big Data Analytics. Advances in Intelligent Systems and Computing, vol 654. Springer, Singapore, pp 677–685, 2018.