Abstract
Cloud computing being a promising paradigm has become very prominent among a wide range of applications due to their timely service rendering capability. Attracted to the type of servicing and the way of servicing lots and lots of users, adapt to the cloud computing. This makes the time servicing of the cloud computing a tedious job. So in order to effectively handle the tasks the scheduling approach is entailed in the cloud computing. The paper proposes an efficient task scheduling for the heterogeneous cloud to render service at a minimized delay utilizing the genetic algorithm. The proposed method is validated through the, cloud simulator to understand the efficiency of the same in terms of delay and the quality of service.
References
Topcuoglu, Haluk, Salim Hariri, and Min-you Wu. "Performance-effective and low-complexity task scheduling for heterogeneous computing." IEEE transactions on parallel and distributed systems 13, no. 3 (2002): 260-274.
He, XiaoShan, XianHe Sun, and Gregor Von Laszewski. "QoS guided min-min heuristic for grid task scheduling." Journal of Computer Science and Technology 18, no. 4 (2003): 442-451.
Lakra, Atul Vikas, and Dharmendra Kumar Yadav. "Multi-objective tasks scheduling algorithm for cloud computing throughput optimization." Procedia Computer Science 48 (2015): 107-113.
Patel, Gaurang, Rutvik Mehta, and Upendra Bhoi. "Enhanced load balanced min-min algorithm for static meta task scheduling in cloud computing." Procedia Computer Science 57 (2015): 545-553.
Pham, Xuan-Qui, and Eui-Nam Huh. "Towards task scheduling in a cloud-fog computing system." In 2016 18th Asia-Pacific network operations and management symposium (APNOMS), pp. 1-4. IEEE, 2016.
Bittencourt, Luiz F., Javier Diaz-Montes, Rajkumar Buyya, Omer F. Rana, and Manish Parashar. "Mobility-aware application scheduling in fog computing." IEEE Cloud Computing 4, no. 2 (2017): 26-35.
Man, Nguyen Doan, and Eui-Nam Huh. "Cost and efficiency-based scheduling on a general framework combining between cloud computing and local thick clients." In 2013 International Conference on Computing, Management and Telecommunications (ComManTel), pp. 258-263. IEEE, 2013.
Krishnadoss, Pradeep, and Prem Jacob. "OCSA: task scheduling algorithm in cloud computing environment." Int J Intell Eng Syst 11, no. 3 (2018): 271-279.
Park, Chan-Ik, and Tae-Young Choe. "An optimal scheduling algorithm based on task duplication." In Proceedings. Eighth International Conference on Parallel and Distributed Systems. ICPADS 2001, pp. 9-14. IEEE, 2001.
Topcuoglu, Haluk, Salim Hariri, and Min-You Wu. "Task scheduling algorithms for heterogeneous processors." In Proceedings. Eighth Heterogeneous Computing Workshop (HCW'99), pp. 3-14. IEEE, 1999.
Koehler, Philip, Arun Anandasivam, and Dan MA. "Cloud services from a consumer perspective." AIS, 2010.
Casas, Pedro, and Raimund Schatz. "Quality of experience in cloud services: Survey and measurements." Computer Networks 68 (2014): 149-165.
Whitley, Darrell. "A genetic algorithm tutorial." Statistics and computing 4, no. 2 (1994): 65-85.
Davis, Lawrence. "Handbook of genetic algorithms." (1991).
Bäck, Thomas, David B. Fogel, and Zbigniew Michalewicz, eds. Evolutionary computation 1: Basic algorithms and operators. CRC press, 2018.
Panda, Sanjaya K., and Prasanta K. Jana. "An efficient task consolidation algorithm for cloud computing systems." In International Conference on Distributed Computing and Internet Technology, pp. 61-74. Springer, Cham, 2016.
Al-Maamari, Ali, and Fatma A. Omara. "Task scheduling using PSO algorithm in cloud computing environments." International Journal of Grid and Distributed Computing 8, no. 5 (2015): 245-256.