Trust Based Resource Selection in Cloud Computing Using Hybrid Algorithm
Автор: V.Suresh Kumar, M. Aramudhan
Журнал: International Journal of Intelligent Systems and Applications(IJISA) @ijisa
Статья в выпуске: 8 vol.7, 2015 года.
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Cloud computing is experiencing rapid advancement in academia and industry. This technology offers distributed, virtualized and elastic resources as utilities for end users and can support full recognition of “computing as a utility” in the future. Scheduling distributes resources among parties which simultaneously and asynchronously seek it. Scheduling algorithms are meant for scheduling and they reduce resource starvation ensuring fairness among those using resources. Most Task-scheduling cloud computing procedures consider task resource requirements for CPU and memory, and not bandwidth. This study suggests optimizing scheduling with BAT-Harmony search hybrid algorithm.
Cloud Computing, Task Scheduling, BAT Algorithm, Harmony Search
Короткий адрес: https://sciup.org/15010743
IDR: 15010743
Список литературы Trust Based Resource Selection in Cloud Computing Using Hybrid Algorithm
- Bhatt, K., & Bundele, M. (2013). Review Paper on PSO in workflow scheduling and Cloud Model enhancing Search mechanism in Cloud Computing. IJIET-International Journal of innovations in engineering and technology, 2(3).
- Garg, S. K., & Buyya, R. (2011, December). CloudSim Estimation of a Simple Particle Swarm AlgorithmInternational Journal of Advanced Research in Computer Science and Software Engineering, 3(8), (pp. 1279-1287).
- Elzeki, O. M., Reshad, M. Z., & Elsoud, M. A. (2012). Improved Max-Min Algorithm in Cloud Computing. International Journal of Computer Applications, 50(12), 22-27.
- Agarwal, D., & Jain, S. (2014). Efficient Optimal Algorithm of Task Scheduling in Cloud Computing Environment. arXiv preprint arXiv:1404.2076.
- Chawla, Y., & Bhonsle, M. Dynamically optimized cost based task scheduling in Cloud Computing.
- Azawi Mohialdeen, I. (2013). Comparative study of scheduling al-gorithms in cloud computing environment. Journal of Computer Science, 9(2).
- Vijayalakshmi A. Lepakshi & Prashanth C S R (2013). A Study on Task Scheduling Algorithms in Cloud Computing. International Journal of Engineering and Innovative Technology (IJEIT), 2(11), 119-125.
- Jangra, A., & Saini, T. (2013). Scheduling optimization in cloud computing. Int. J. Adv. Res. Comput. Sci. Softw. Eng, 3, 62-65.
- Heger, D. A. (2010). Optimized Resource Allocation & Task Scheduling Challenges in Cloud Computing Environments. dheger@ dhtusa. com.
- Vijayalakshmi, M., & Muthusamy, K. An Efficient Study of Job Scheduling Algorithms with ACO in Cloud Computing Environment.
- Princy Bathla., Sahil Vashist., Rajwinder Singh., & Gagandeep Singh., (2014). A Sophisticated Review of the Job Scheduling methods on Cloud Network. International Journal of Latest Scientific Research and Technology (IJLSRT).
- Zhang, F., Cao, J., Li, K., Khan, S. U., & Hwang, K. (2014). Multi-objective scheduling of many tasks in cloud platforms. Future Generation Computer Systems, 37, 309-320.
- Liu, H., Xu, D., & Miao, H. (2011, December). Ant colony optimization based service flow scheduling with various QoS requirements in cloud computing. In Software and Network Engineering (SSNE), 2011 First ACIS International Symposium on (pp. 53-58). IEEE.
- Luo, L., Wu, W., Di, D., Zhang, F., Yan, Y., & Mao, Y. (2012, June). A resource scheduling algorithm of cloud computing based on energy efficient optimization methods. In Green Computing Conference (IGCC), 2012 International (pp. 1-6). IEEE.
- Song, X., Gao, L., & Wang, J. (2011, June). Job scheduling based on ant colony optimization in cloud computing. In Computer Science and Service System (CSSS), 2011 International Conference on (pp. 3309-3312). IEEE.
- Wang, N., Yang, Y., Meng, K., Chen, Y., & Ding, H. (2013, August). A task scheduling algorithm based on qos and complexity-aware optimization in cloud computing. In Information and Communications Technology 2013, National Doctoral Academic Forum on (pp. 1-8). IET.
- Pandey, S., Wu, L., Guru, S. M., & Buyya, R. (2010, April). A particle swarm optimization-based heuristic for scheduling workflow applications in cloud computing environments. In Advanced Information Networking and Applications (AINA), 2010 24th IEEE International Conference on (pp. 400-407). IEEE.
- Chen, C. Y., & Tseng, H. Y. (2012, March). An Exploration of the Optimization of Excutive Scheduling in the Cloud Computing. In Advanced Information Networking and Applications Workshops (WAINA), 2012 26th International Conference on (pp. 1316-1319). IEEE.
- Li, Q., & Guo, Y. (2010, September). Optimization of Resource Scheduling in Cloud Computing. In SYNASC (pp. 315-320).
- Han, Y., & Luo, X. (2013, December). An Effective Algorithm and Modeling for Information Resources Scheduling in Cloud Computing. In Advanced Cloud and Big Data (CBD), 2013 International Conference on (pp. 14-19). IEEE.
- Han, H., Deyui, Q., Zheng, W., & Bin, F. (2013, September). A Qos Guided task Scheduling Model in cloud computing environment. In Emerging Intelligent Data and Web Technologies (EIDWT), 2013 Fourth International Conference on (pp. 72-76). IEEE.
- Karthick, A. V., Ramaraj, E., & Subramanian, R. G. (2014, February). An Efficient Multi Queue Job Scheduling for Cloud Computing. In Computing and Communication Technologies (WCCCT), 2014 World Congress on (pp. 164-166). IEEE.
- Sun, W., Zhang, N., Wang, H., Yin, W., & Qiu, T. (2013, December). PACO: A Period ACO Based Scheduling Algorithm in Cloud Computing. In Cloud Computing and Big Data (CloudCom-Asia), 2013 International Conference on (pp. 482-486). IEEE.
- Man, N. D., & Huh, E. N. (2013, January). Cost and efficiency-based scheduling on a general framework combining between cloud computing and local thick clients. In Computing, Management and Telecommunications (ComManTel), 2013 International Conference on (pp. 258-263). IEEE.
- Hung, P. P., Bui, T. A., & Huh, E. N. (2013, December). A Thin-Thick Client Collaboration for Optimizing Task Scheduling in Mobile Cloud Computing. In IT Convergence and Security (ICITCS), 2013 International Conference on (pp. 1-4). IEEE.
- Liu, N., Dong, Z., & Rojas-Cessa, R. (2013, July). Task Scheduling and Server Provisioning for Energy-Efficient Cloud-Computing Data Centers. In Distributed Computing Systems Workshops (ICDCSW), 2013 IEEE 33rd International Conference on (pp. 226-231). IEEE.
- Fister Jr, I., Fister, D., & Yang, X. S. (2013). A hybrid bat algorithm. arXiv preprint arXiv:1303.6310.
- Wang, G., Guo, L., Duan, H., Liu, L., & Wang, H. (2012). A bat algorithm with mutation for UCAV path planning. The Scientific World Journal, 2012.
- Yang, X. S. (2009). Harmony search as a metaheuristic algorithm. In Music-inspired harmony search algorithm (pp. 1-14). Springer Berlin Heidelberg.
- Weyland, D. (2010). A rigorous analysis of the harmony search algorithm: How the research community can be misled by a “novel” methodology. International Journal of Applied Metaheuristic Computing (IJAMC), 1(2), 50-60.
- Wang, G., & Guo, L. (2013). A novel hybrid bat algorithm with harmony search for global numerical optimization. Journal of Applied Mathematics, 2013.
- Kumar, V. S., & Aramudhan, M. (2014). Trust based resource selection and list scheduling in cloud computing. International Journal of Advances in Engineering & Technology, 6(6).