Open Access
Issue
MATEC Web of Conferences
Volume 57, 2016
4th International Conference on Advancements in Engineering & Technology (ICAET-2016)
Article Number 02009
Number of page(s) 4
Section Information Systems & Computer Science Engineering
DOI https://doi.org/10.1051/matecconf/20165702009
Published online 11 May 2016
  1. J.A.J. Sujana, T. Revathi, G. Karthiga, R.V. Raj, Game multi objective scheduling algorithm for scientific workflows in cloud computing, IEEE, 1-6, (2015).
  2. K.A. Saranu, S.Jaganathan, Intensified scheduling algorithm for virtual machine tasks in cloud computing, Springer, 283-290, (2014).
  3. S. Selvarani, G.S. Sadhasivam, Improved cost-based algorithm for task scheduling in cloud computing,” IEEE, 1-5, (2010).
  4. S. Banerjee, M. Adhikari, S. Kar, U. Biswas, Development and analysis of a new cloudlet allocation strategy for QoS improvement in cloud, AJSE, Springer, 40, 1409-1425, (2015).
  5. U.A. Kashif, Z.A. Memon, A.R. Balouch, J.A. Chandio, Distributed trust protocol for IaaS cloud computing, IBCAST, IEEE, 275-279, (2015).
  6. K. Cheng, Y. Bai, R. Wang, Y. Ma, Optimizing soft real-time scheduling performance for virtual machines with XRT-Xen, IEEE, 169-178, (2015).
  7. D. Ding, X. Fan, S. Luo, User-oriented cloud resource scheduling with feedback integration, Springer, 1-22, (2015).
  8. Hu Wu, Zhuo Tang, Renfa Li, A priority constrained scheduling strategy of multiple workflows for cloud computing, IEEE, 1086-1089, (2012).
  9. A.V. Lakra, D.K. Yadav, Multi-objective tasks scheduling algorithm for cloud computing throughput optimization, ICICCC, 48, 107-113, (2015).
  10. C. Lin, S. Lu, Scheduling scientific workflows elastically for cloud computing, IEEE, 746-747, (2011).
  11. Himani, H.S. Sidhu, Cost- deadline based task scheduling in cloud computing, ICACCE, IEEE, 273-279, (2015).
  12. A. Verma, S. Kaushal, Cost- time efficient scheduling plan for executing workflows in the cloud, JGC, Springer , 13, 495-506, (2015).
  13. S. Sindhu, S. Mukherjee, Efficient task scheduling algorithms for cloud computing environment, Springer, 79-83, (2011).
  14. Z. Wang, S. Su, Dynamically hierarchical resource-allocation algorithm in cloud computing environment, Springer, 2748-2766, (2015).
  15. Jia Ru, Jacky Keung, An Empirical investigation on the simulation of priority and shortest-job-first scheduling for cloud based software systems, IEEE, 78-87, (2013).
  16. Q.T. Nguyen, N.Q. Hung, N.H. Tuong, V.H. Tran, N. Thoai, Virtual machine allocation in cloud computing for minimizing total execution time on each machine, IEEE, 241-245, (2013).
  17. A.K. Das, T. Adhikary, C.S. Hong, An intelligent approach for virtual machine and QoS provisioning in cloud computing, IEEE, 462-467, (2013).
  18. R. Achar, P.S. Thilagam, Shwetha D, Pooja H, Roshni, Andrea, Optimal scheduling of computational task in cloud using virtual machine tree, ICEAIT, IEEE, 143-146, (2012).
  19. W.J. Wang, Y.S. Chang, W.T. Lo, Y.K. Lee, Adaptive scheduling for parallel tasks with QoS satisfaction for hybrid cloud environments, Springer, 66, 783-811, (2013).
  20. Liang Ma,Y. Lu, F. Zhang, S. Sun, Dynamic task scheduling in cloud computing based on greedy strategy, Springer, 156-162, (2013).
  21. J.M. Tang, L. Luo, K.M. Wei, A heuristic resource scheduling algorithm for cloud computing based on polygons correlation calculation, ICEBE, IEEE, 365-370, (2015).
  22. S. Singh, I. Chana, QRSF: QoS aware resource scheduling framework in cloud computing, Springer, 71, 241-292, (2014).
  23. S. Singh, I. Chana, Resource provisioning and scheduling in clouds: QoS perspective, Springer, 1-35, (2016).

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