Human resource transaction management system security optimize using multithreading with blowfish Algorithm
DOI:
https://doi.org/10.48165/gmj.2023.18.2.4Keywords:
HRMS, Blowfish algorithm, Data, Multithreading, managementAbstract
Today HRMS (Human resource management system) application around data transmitting from one place to another is challenging and doing this with real-time data is even more difficult to service time minimize and secure. In this paper using Blowfish algorithm with multithreading technology we will solve the waiting time using dis tributed data streaming platform. This approach will become ideal to daily life where each and every user get services in optimize way with secure direction.
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Dr. Madhurendra Kumar,“Cloud computing Network Problem and Storage solutions Using Ant colony optimization” International Journal of Scientific & Engineering Research Volume 7, Issue 12, December-2016, ISSN 2229-5518
Dorigo M. and Blum C., “Ant Colony Optimization Theory: A Survey,” in Theoretical Computer Science, vol. 344, no. 2, pp. 243-278, 2005.
Dorigo M., Birattari M., and Stutzel T., “Ant Colony Optimization,” IEEE Computational Intelligence Magazine, vol. 1, no. 4, pp. 28-39, 2006.
Fangzhe C., Ren J., and Viswanathan R., “Optimal Resource Allocation in Clouds,” in Proceedings of the 3rd International Conferenceon Cloud Computing, Florida, USA, pp. 418- 425, 2010.
Gao K., Wang Q., and Xi L., “Reduct Algorithm Based Execution Times Prediction in Knowledge Discovery Cloud Computing Environment,” the International Arab Journal of Information Technology, vol. 11, no. 3, pp. 268- 275, 2014.
Gao Y., Guan H., Qi Z., Hou Y., and Liu L., “A Multi Objective Ant Colony System Algorithm for Virtual Machine Placement in Cloud Computing,” Journal of Computer and System Sciences, vol. 79, no. 8, pp. 1230-1242, 2013.
R. Buyya and M. Murshed. GridSim: A Toolkit for the Modeling and Simulation of Distributed Resource Management and Scheduling for Grid Computing. Concurrency and omputation: Practice and Experience, 14(13-15), Wiley Press, Nov.-Dec., 2002.
Ghalem B., Tayeb F., and Zaoui W.,“Approaches to Improve the Resources Management in the Simulator Cloudism,” in Proceedings of the Conference on Interactionand Confidence Building Measures in Asia,Lecture Notes in Computer Science, Istanbul, Turkey, pp. 189-196, 2010.
Hsu C. and Chen T., “Adaptive Scheduling Based on Quality of Service in Heterogeneous Environments,” in Proceedings of the IEEEInternational Conference on Multimedia and Ubiquitous Engineering, California, USA, pp. 1-6, 2010.
Ijaz S., Munir E., Anwar W., and Nasir W.,“Efficient Scheduling Strategy for Task Graphs in Heterogeneous Computing Environment,” theInter national Arab Journal of Information Technology, vol 10, no. 5, pp. 486-492, 2013.
Kessaci Y., Melab N., and Talbi E., “A Pareto- Based GA for Scheduling HPC Applications on Distributed Cloud Infrastructures,” in Proceedings of the IEEE International Conference on High Performance Computing and Simulation, Istanbul, Turkey, pp. 456-462, 2011
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