dth: 0px; "> [1] Handbook of Cloud Computing [online].
Available:http://www.springerlink.com/index/10.1007/978-1-4419-6524-0.
[2] J. Tsai, J. Fang, J. Chou ,“Optimized task scheduling and resource
allocation on cloud computing Environment using improved differential
evolution algorithm”, Computers &Operations Research 40, PP. 3045–
3055,2013.
[3] A. Soror, U. F. Minhas, A. Aboulnaga, K. Salem, P. Kokosielis, and S.
Kamath, "Deploying Database Appliances in the Cloud.," IEEE Data Eng.
Bull., vol. 32, No. 1, PP. 13-20, 2009.
[4] Y. Yang, et al., " An Algorithm in SwinDeW-C for Scheduling
Transaction- Intensive Cost-Constrained Cloud Workflows," Proc. of 4th
IEEE International Conference on e-Science, Indianapolis, USA, PP. 374-
375, December 2008.
[5] Y.Chawla, M.Bhonsle, “A Study on Scheduling Methods in Cloud
Computing”, International Journal of Emerging Trends & Technology in
Computer Science, Vol. 1, Issue 3, PP. 12-17, September – October 2012.
[6] Amazon EC2. Available:http://aws.amazon.com/ec2/.
[7] Google Cloud. Available:https://cloud.google.com/compute/pricing.
[8] Al-maamari, Ali, and Fatma A. Omara."Task SchedulingUsing PSO
Algorithm in Cloud ComputingEnvironments."International Journal of
Grid andDistributed Computing 8.5 (2015): 245-256.
-stroke-width: 0px; "> [9] Ali Al-maamari, Fatma A. Omara.” Task Scheduling using Hybrid
Algorithm in Cloud Computing Environments” IOSR Journal of Computer
Engineering (May – Jun. 2015), PP 96-106.
[10] Suraj Pandey, Linlin Wu, Siddeswara Guru, and Rajkumar Buyya. "A
Particle Swarm Optimization (PSO)-based Heuristic for Scheduling
Workflow Applications in Cloud Computing Environments." Proceedings
of the 24th IEEE International Conference on Advanced Information
Networking and Applications (AINA ), Perth, Australia. April 20-23, 2010.
[11] Ke Liu, Hai Jin, Jinjun Chen, Xiao Liu, Dong Yuan, Yun Yang , " A
Compromised-Time-Cost Scheduling Algorithm in SwinDeW-C for
Instance-Intensive Cost-Constrained Workflows on a Cloud Computing
Platform," International Journal of High Performance Computing
Applications - IJHPCA , vol. 24, no. 4, pp. 445-456, 2010
[12] J.Huang. "The Workflow Task Scheduling Algorithm Based on the GA
Model in the Cloud Computing Environment." Journal of Software, vol. 9,
No 4, PP. 873-880, April 2014.
[13] Lei Zhang, et al. "A Task Scheduling Algorithm Based on PSO for Grid
Computing." International Journal of Computational Intelligence Research,
vol. 4, No.1, PP. 37–43, 2008.
[14] M.Al-Roomi, S.Al-Ebrahim, S.Buqrais and I.Ahmad,“Cloud Computing
Pricing Models: A Survey”,Vol.6, No.5 (2013), pp.93-106, International
Journal of Grid and Distributed Computing.
[15] J. D. Ullman. Np-complete scheduling problems. J. Comput.Syst. Sci.,
10(3), 1975.
[16] Visalakshi, P. and S. Sivanandam, Dynamic task scheduling with load
balancing using hybrid particle swarm optimization. Int. J. Open Problems
Compt. Math, 2009. 2(3): p. 475-488.
[17] Selvarani, S. and G.S. Sadhasivam. Improved cost-based algorithm for task
scheduling in cloud computing. in Computational intelligence and
computing research (iccic), 2010 ieee international conference on. 2010.
[18] Uma, S., et al., A hybrid PSO with dynamic inertia weight and GA
approach for discovering classification rule in data mining. International
Journal of Computer Applications, 2012. 40(17).
[19] Girgis, M. R., Mahmoud, T. M., Abdullatif, B. A., & Rabie, A. M. Solving
the Wireless Mesh Network Design Problem using Genetic Algorithm and
Tabu Search Optimization Methods.
[20] Elhossiny Ibrahim, Nirmeen A. El-Bahnasawy, Fatma A. Omara, “Job
Scheduling based on Harmonization Between The requested and Available
Processing Power in The Cloud Computing Environment”, IJCA, Volume
125 – No.13, September 2015.
[21] Rajkumar Buyya, Rajiv Ranjan and Rodrigo N. Calheiros, “Modeling and
Simulation of Scalable Cloud ComputingEnvironments and the CloudSim
Toolkit: Challenges and Opportunities” in the 7th High Performance