Call for Paper - January 2023 Edition
IJCA solicits original research papers for the January 2023 Edition. Last date of manuscript submission is December 20, 2022. Read More

Load Distribute Across the Cloud Server: Challenges and Algorithms

Print
PDF
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Durga Patel, Veena Mishra, R.K.Pateriya
10.5120/ijca2016912333

Durga Patel, Veena Mishra and R.K.Pateriya. Load Distribute Across the Cloud Server: Challenges and Algorithms. International Journal of Computer Applications 155(6):36-41, December 2016. BibTeX

@article{10.5120/ijca2016912333,
	author = {Durga Patel and Veena Mishra and R.K.Pateriya},
	title = {Load Distribute Across the Cloud Server: Challenges and Algorithms},
	journal = {International Journal of Computer Applications},
	issue_date = {December 2016},
	volume = {155},
	number = {6},
	month = {Dec},
	year = {2016},
	issn = {0975-8887},
	pages = {36-41},
	numpages = {6},
	url = {http://www.ijcaonline.org/archives/volume155/number6/26611-2016912333},
	doi = {10.5120/ijca2016912333},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Cloud computing has become as an approved computing model to challenge processing the large volume of data which utilizes clusters of commodity computers. . Load balancing helps to utilize 100% of the resource provided by cloud service provider in a cloud scenario. This is a procedure which actually implements the concepts of task scheduling algorithm, nowadays the load imbalance virtual machine accelerate several networks, storage and energy consumption related irregularities. Due to the extensive operation of cloud computing resources, it became one of the prime goals of the cloud provider to utilize the computing resources efficiently and optimize the physical resource utilization. Numerous algorithms were recommended to suggest potent procedure and algorithms for allocating the user's demand to accessible cloud nodes. These all methodologies wish to gain complete performance of the cloud services and make the user more satisfying, authentic, sensible and well-organized services. Load balancing is implemented by various algorithms, few of these algorithms are promoted because of better energy efficiency, resource utilization and they are fault tolerant too. This paper explored different existing load balancing approaches in a cloud environment along with their anomalies.

References

  1. Divya Chaudhary, "Analytical Study of Load Scheduling Algorithms in Cloud Computing ", proceeding of 2014 International Conference on Parallel, Distributed and Grid Computing, pp7-12, 2014.
  2. Garima Rastogi, "Analytical Literature Survey on Existing Load Balancing Schemes in Cloud Computing”, IEEE, pp1506-1510, 2015.
  3. Klaithem Al Nuaimi," A Survey of Load Balancing in Cloud Computing: Challenges and Algorithms ", NCCA, 2012, International Symposium on 2012, IEEE, pp137-142, 2012.
  4. Hamid Shoja, "A Comparative Survey On Load Balancing Algorithms In Cloud Computing ", ICCCNT, IEEE, pp1-5,2014.
  5. Yingchi Mao, “Adaptive Load Balancing Algorithm Based on Prediction Model in Cloud Computing”, proceeding of the second international conference on innovative computing cloud computing, pp165, 2015.
  6. G.Punetha Sharmila, "Survey Onfault Tolerant –Load Balancing Algorithmsin Cloud Computing ", Proceeding of 2nd International Conference On Electronics And Communication System (Icecs 2015), IEEE,pp1715-1720,2015.
  7. Hank Chen, Professor Frank Wang," User-Priority Guided Min-Min Scheduling Algorithm For Load Balancing in Cloud Computing ", IEEE, pp1-8,2013.
  8. Ekta Gupta, Vidya Deshpande," A Technique Based on Ant Colony Optimization for Load Balancing in Cloud Data Center ", 014 13th International Conference on Information Technology, IEEE, pp12-17,2014.
  9. G. Shobana," Nature Inspired Preemptive Task Scheduling for Load Balancing in Cloud Datacenter ", Proceedings of ICICES 2014, IEEE, pp1-6,2014.
  10. Shahrzad Aslanzadeh, Zenon Chaczko, "Load Balancing Optimization in Cloud Computing: Applying Endocrine-Particle Swarm Optimization", IEEE, pp165-169,2015.
  11. KaiPan, JiaqiChen, "Load Balancing in Cloud Computing Environment Based on An Improved Particle Swarm Optimization", IEEE, pp595-598,2015.
  12. Ariharan v," Neighbor-Aware Random Sampling (NARS) algorithm for load balancing in Cloud computing", IEEE, pp1-5,2015.

Keywords

Cloud computing, Load balancing, virtual machine.