T. Erl, R. Puttini, and Z. Mahmood, Cloud Computing: Concepts,Technology & Architecture. 1st ed. Englewood Cliffs, NJ, USA:Prentice-Hall, 2013.
 S. K. Garg, S. Versteeg, and R. Buyya, “A framework for ranking of cloud computing services,” Future Generation Comput. Syst., vol. 29, no. 4, pp. 1012–1023, Jun. 2012.
 G. Nan, Z. Mao, M. Li, Y. Zhang, S. Gjessing, H. Wang, and M.Guizani, “Distributed resource allocation in cloud-based wireless multimedia social networks,” IEEE Netw. Mag., vol. 28, no. 4, pp. 74–80, Jul. 2014.
 R. Yu, Y. Zhang, S. Gjessing, W. Xia, and K. Yang, “Toward cloudbasedvehicular networks with efficient resource management,”IEEE Netw. Mag., vol. 27, no. 5, pp. 48–55, Sep./Oct. 2013.
 H. Liu, A. Abraham, and A. E. Hassanien, "Scheduling jobs on computational grids using a fuzzy particle swarm optimization algorithm," Future Generation Computer Systems, vol. 26, no. 8, pp. 1336-1343, 2010/10/01/ 2010.
 Eberhart RC, Kennedy J. A new optimizer-using particle swarm theory. In: Proceedings of the Sixth International Symposium on Micro Machine and Human Science, 1995:39‐43.
E.Goldberg and J.H.Holland,”Genetic algorithms and machine learning”,Mach Learn.,vol.3,no.2,pp.95-99,1988.
 J. Liu, X. G. Luo, X. M. Zhang, and F. Zhang, "Job scheduling algorithm for cloud computing based on particle swarm optimization," in Advanced Materials Research, 2013, pp. 957-960.
 S. Javanmardi, M. Shojafar, D. Amendola, N. Cordeschi, H. Liu, and A. Abraham, "Hybrid job scheduling algorithm for cloud computing environment," in Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014, 2014, pp. 43-52.
 S. M. Abdulhamid, M. S. A. Latiff, and I. Idris, "Tasks scheduling technique using league championship algorithm for makespan minimization in IAAS cloud," arXiv preprint arXiv: 1510.03173, 2015.
 F. Ramezani, J. Lu, and F. K. Hussain, "Task-based system load balancing in cloud computing using particle swarm optimization," International journal of parallel programming, vol. 42, pp. 739-754, 2014.
S. Parthasarathy and C. J. Venkateswaran, "Scheduling jobs using oppositional-GSO algorithm in cloud computing environment," Wireless Networks, pp. 1-11.
 Z. Zhang and X. Zhang, "A load balancing mechanism based on ant colony and complex network theory in open cloud computing federation," in Industrial Mechatronics and Automation (ICIMA), 2010 2nd International Conference on, 2010, pp. 240-243.
 S. Sethi, A. Sahu, and S. K. Jena, "Efficient load balancing in cloud computing using fuzzy logic," IOSR Journal of Engineering, vol. 2, pp. 65-71, 2012.
 Krishna PV. Honey bee behavior inspired load balancing of tasks in cloud computing environments. Appl Soft Comput. 2013;13:2292‐2303.
 Calheiros RN, Ranjan R, Beloglazov A, De Rose CA, Buyya R. CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Softw Pract Exp. 2011;41:23‐50.