Efficient Resource Provisioning in Cloud Environment in Terms of Profit using Hybrid Load Balancing Algorithm
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2016 by IJCTT Journal|
|Year of Publication : 2016|
|Authors : P.Karthika, K.C.Palanisamy|
|DOI : 10.14445/22312803/IJCTT-V36P106|
P.Karthika, K.C.Palanisamy "Efficient Resource Provisioning in Cloud Environment in Terms of Profit using Hybrid Load Balancing Algorithm". International Journal of Computer Trends and Technology (IJCTT) V36(1):32-37, June 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Resource provisioning plays a major role in the cloud computing environment due to increased number of cloud users. The user satisfaction level can be improves in the considerable manner by provisioning the resources to the users which can process them with more profit. In this research work, resource provisioning is done with the consideration of the objective called profit. The profit of cloud service providers and as well as users are improved in the considerable manner through the method named as double renting scheme. This double renting method collects the amount for dealing the user request in several way depends on type resource access. The public cloud resources charges for specific amount as like secret cloud resources charged for particular amount. The proposed hybrid load balancing method is used to increase the maximal profit values more significantly rather than the existing system. In this scenario, it shows that the hybrid algorithm insert an important improvements on average response time and profit values. This research provides QoS assured resource selection for the user submitted task in the considerable manner. The experimental tests conducted was proves that the proposed research scenario provides better result than the existing research scenario in terms of increased profit.
 Rochwerger, Benny, et al. "The reservoir model and architecture foropen federated cloud computing." IBM Journal of Research and Development 53.4 (2009): 4-1.
 Garg, Saurabh Kumar, RajkumarBuyya, and Howard Jay Siegel. "Time and cost trade-off management for scheduling parallel applications on utility grids." Future Generation Computer Systems 26.8 (2010): 1344-1355.
 Ghamkhari, Mahdi, and HamedMohsenian-Rad. "Energy and performance management of green data centers: A profit maximization approach."Smart Grid, IEEE Transactions on 4.2 (2013): 1017-1025.
 Khazaei, Hamzeh, JelenaMiši?, and Vojislav B. Miši? "Performance analysis of cloud computing centers using m/g/m/m+ r queuing systems"Parallel and Distributed Systems, IEEE Transactions on 23.5 (2012): 936-943.
 Mazzucco, Michele, and DmytroDyachuk. "Optimizing cloud providers revenues via energy efficient server allocation." Sustainable Computing: Informatics and Systems 2.1 (2012): 1- 12.
 Cao, Junwei, et al. "Optimal multiserver configuration for profit maximization in cloud computing." Parallel and Distributed Systems, IEEE Transactions on 24.6 (2013): 1087-1096.
 Mei, Jing, et al. "Energy-aware preemptive scheduling algorithm for sporadic tasks on DVS platform." Microprocessors and Microsystems37.1 (2013): 99-112.
 Xu, Hong, and Baochun Li. "Dynamic cloud pricing for revenue maximization." Cloud Computing, IEEE Transactions on 1.2 (2013): 158-171.
 Ghamkhari, Mahdi, and HamedMohsenian-Rad. "Profit maximization and power management of green data centers supporting multiple slas" Computing, Networking and Communications (ICNC), 2013 International Conference on. IEEE, 2013.
 Chiang, Yi-Ju, and Yen-ChiehOuyang "Profit optimization in SLA-aware cloud services with a finite capacity queuing model" Mathematical Problems in Engineering 2014 (2014).
SLA parameter, Profit, Resource provisioning, dynamic pricing, Hybrid load balancing.