[1] H. Jiao, J. Zhang, J. Li, J. Shi, and J. Li, “Immune optimization of task scheduling on multidimensional QoS constraints,” Cluster Comput., vol. 18, no. 2, pp. 909–918, 2015.
[2] S. K. Panda, I. Gupta, and P. K. Jana, “Task scheduling algorithms for multi-cloud systems: allocation-aware approach,” Inf. Syst. Front., pp. 1–19, 2017.
[3] L. Ma, Y. Lu, F. Zhang, and S. Sun, “Dynamic Task Scheduling in Cloud Computing Based on Greedy Strategy,” Proc. Int. Conf. Trust. Comput. Serv., pp. 156–162, 2012.
[4] L. Tang, J.-S. Pan, Y. Hu, P. Ren, and Y. T. and H. Zhao, “A Novel Load Balance Algorithm for Cloud Computing,” © Springer Int. Publ. Switz. 2016, vol. 329, pp. 325–333, 2016.
[5] K. Dubey, M. Kumar, and S. C. Sharma, “Modified HEFT Algorithm for Task Scheduling in Cloud Environment,” Procedia Comput. Sci., vol. 125, pp. 725–732, 2018.
[6] R. Moreno-Vozmediano, R. S. Montero, E. Huedo, and I. M. Llorente, “Orchestrating the Deployment of High Availability Services on Multi-zone and Multi-cloud Scenarios,” J. Grid Comput., pp. 1–15, 2017.
[7] M. Ghetas and C. H. Yong, “Resource Management Framework for Multi-tier Service Using Case-Based Reasoning and Optimization Algorithm,” Arab. J. Sci. Eng., 2017.
[8] L. Chen, M. Qiu, J. Song, Z. Xiong, and H. Hassan, “E2FS: an elastic storage system for cloud computing,” J. Supercomput., pp. 1–16, 2016.
[9] R. Khorsand, F. Safi-Esfahani, N. Nematbakhsh, and M. Mohsenzade, “Taxonomy of Workflow Partitioning Problems and Methods in Distributed Environments,” J. Syst. Softw., 2017.
[10] K. R. R. Babu and P. Samuel, “Enhanced Bee Colony Algorithm for Efficient Load Balancing and Scheduling in Cloud,” © Springer Int. Publ. Switz. 2016, vol. 237, pp. 67–78, 2016.
[11] H. Gamal El Din Hassan Ali, I. A. Saroit, and A. M. Kotb, “Grouped tasks scheduling algorithm based on QoS in cloud computing network,” Egypt. Informatics J., vol. 18, no. 1, pp. 11–19, 2017.
[12] A. V. Lakra and D. Kumar Yadav, “Multi-objective tasks scheduling algorithm for cloud computing throughput optimization,” Procedia Comput. Sci., vol. 48, no. C, pp. 107–113, 2015.
[13] M. S. Aslanpour, M. Ghobaei-Arani, and A. N. Toosi, “Auto-scaling Web Applications in Clouds: A Cost-Aware Approach,” J. Netw. Comput. Appl., p. , 2017.
[14] L. D. Dhinesh Babu and P. Venkata Krishna, “Honey bee behavior inspired load balancing of tasks in cloud computing environments,” Appl. Soft Comput. J., vol. 13, no. 5, pp. 2292–2303, 2013.
[15] U. Bhoi and P. Ramanuj, “Enhanced Max-min Task Scheduling Algorithm in Cloud Computing,” Int. J. Appl. or Innov. …, vol. 2, no. 4, pp. 259–264, 2013.
[16] M. Beltr´an, “BECloud: A new approach to analyse elasticity enablers of cloud services,” Futur. Gener. Comput. Syst., vol. 64, pp. 39–49, 2016.
[17] S. K. Garg, S. Versteeg, and R. Buyya, “A framework for ranking of cloud computing services,” Futur. Gener. Comput. Syst., vol. 29, no. 4, pp. 1012–1023, 2013.
[18] M. Ghobaei-Arani, S. Jabbehdari, and M. A. Pourmina, “An autonomic approach for resource provisioning of cloud services,” Cluster Comput., vol. 19, no. 3, pp. 1017–1036, 2016.
[19] M. Ghobaei-Arani, S. Jabbehdari, and M. A. Pourmina, “An autonomic resource provisioning approach for service-based cloud applications: A hybrid approach,” Futur. Gener. Comput. Syst., 2016.
[20] B. Xu, C. Zhao, E. Hu, and B. Hu, “Job scheduling algorithm based on Berger model in cloud environment,” Adv. Eng. Softw., vol. 42, no. 7, pp. 419–425, 2011.
[21] H. Li, S. Ge, and L. Zhang, “A QoS-based scheduling algorithm for instance-intensive workflows in cloud environment,” 26th Chinese Control Decis. Conf. CCDC 2014, pp. 4094–4099, 2014.
[22] J. Zhao, W. Zeng, M. Liu, and G. Li, “Multi-objective Optimization Model of Virtual Resources Scheduling Under Cloud Computing and It’s Solution,” Cloud Serv. Comput., pp. 185–190, 2011.
[23] F. Ramezani, J. Lu, J. Taheri, and F. K. Hussain, “Evolutionary algorithm-based multi-objective task scheduling optimization model in cloud environments,” World Wide Web, vol. 18, no. 6, pp. 1737–1757, 2015.
[24] S. H. H. Madni, M. S. A. Latiff, Y. Coulibaly, and S. M. Abdulhamid, “Recent advancements in resource allocation techniques for cloud computing environment: a systematic review,” Cluster Comput., vol. 20, no. 3, pp. 2489–2533, 2017.
[25] N. R. Herbst, S. Kounev, and R. Reussner, “Elasticity in Cloud Computing : What It Is , and What It Is Not,” Present. as part 10th Int. Conf. Auton. Comput., pp. 23–27, 2013.
[26] F. Cottet, J. Delacroix, Z. Mammeri, and C. Kaiser, Scheduling in real-time systems. 2002.
[27] L. Wu, S. Kumar Garg, S. Versteeg, and R. Buyya, “SLA-based Resource Provisioning for Hosted Software as a Service Applications in Cloud Computing Environments,” IEEE Trans. Serv. Comput., vol. 7, no. 3, pp. 465–485, 2014.
[28] C. Rodrigo N. Calheiros, Rajiv Ranjan, Anton Beloglazov, esar A. F. De Rose, and and R. Buyya, “CloudSim: a toolkit formodeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms,” Softw. - Pract. Exp., vol. 41, no. 1, pp. 23–50, 2011.
[29] R. Khorsand, F. Safi-Esfahani, N. Nematbakhsh, and M. Mohsenzade, “ATSDS: adaptive two-stage deadline-constrained workflow scheduling considering run-time circumstances in cloud computing environments,” J. Supercomput., vol. 73, no. 6, pp. 2430–2455, 2016.
[30] S. Banerjee, M. Adhikari, S. Kar, and U. Biswas, “Development and Analysis of a New Cloudlet Allocation Strategy for QoS Improvement in Cloud,” Arab. J. Sci. Eng., vol. 40, no. 5, pp. 1409–1425, 2015.
[31] G. Wang and H. C. Yu, “Task Scheduling Algorithm Based on Improved Min-Min Algorithm in Cloud Computing Environment,” Appl. Mech. Mater., vol. 303–306, pp. 2429–2432, 2013.
[32] M. Dakshayini and H. S. Guruprasad, “An Optimal Model for Priority based Service Scheduling Policy for Cloud Computing Environment,” Int. J. Comput. Appl., vol. 32, no. 9, pp. 975–8887, 2011.
[33] A. Narwal and S. Dhingra, “Task Scheduling Algorithm Using Multi-Objective Functions for Cloud Computing Environment,” 2nd Int. Conf. Sustain. Comput. Tech. Eng., vol. 27–28, no. Vm, 2017.