Cloud computing environments enable real time applications on virtualized resources that can be provisioned dynamically. It is one of the efficient platform service which permits to enable the various applications based on cloud infrastructure. Nowadays workflow systems become an easy and efficient task for the development of scientific applications. Efficient workflow scheduling algorithms are employed to improve the resource utilization by enhancing the cloud computing performance and to meet the users’ requirements. Many scheduling algorithms have been proposed but they are not optimal to incorporate benefits of cloud computing. In this paper a new framework are introduced as whale optimizer algorithm (WOA) which mimics the social behaviour of humpback whales and aims to maximize the work completion for meeting QoS constraints such as deadline and budget. This proposed method outperforms well when compared with other techniques and measured in terms of makespan, deadline and it is applicable for real time applications.
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Bardsiri AK, Hashemi SM (2012) A review of workflow scheduling in cloud computing environment. Int J Comput Sci Manag Res 1(3):348–351
Durillo JJ, Prodan R (2014) Multi-objective workflow scheduling in Amazon EC2. Clust Comput 17(2):169–189
Elghamrawy SM, Hassanien AE (2019) GWOA: a hybrid genetic whale optimization algorithm for combating attacks in cognitive radio network. J Ambient Intell Hum Comput 10:4345–4360. https://doi.org/10.1007/s12652-018-1112-9
Kaur N, Aulakh TS, Cheema RS (2011) Comparison of workflow scheduling algorithms in cloud computing. Int J Adv Comput Sci Appl 2(10):89
Komaki GM, Kayvanfar V (2015) Grey Wolf Optimizer algorithm for the two-stage assembly flow shop scheduling problem with release time. J Comput Sci 31(8):109–120
Mirjalili S, Lewis A (2016) The whale optimization algorithm. Adv Eng Softw 95:51–67
Mohammed A, El-Bahnasawy N, Sadi S, Wagdi M (2019) On the design of reactive approach with flexible checkpoint interval to tolerate faults in cloud computing systems. J Ambient Intell Hum Comput 10:4567–4577. https://doi.org/10.1007/s12652-018-1139-y
Naseri A, Jafari Navimipour N (2019) A new agent-based method for QoS-aware cloud service composition using particle swarm optimization algorithm. J Ambient Intell Hum Comput 10:1851–1864. https://doi.org/10.1007/s12652-018-0773-8
Rahman M, Hassan R, Ranjan R, Buyya R (2013) Adaptive workflow scheduling for dynamic grid and cloud computing environment. Concurr Comput Pract Exp 25(13):1816–1842
Shi Z, Dongarra JJ (2006) Scheduling workflow applications on processors with different capabilities. Future Gener Comput Syst 22(6):665–675
Singh R, Singh S (2013) Score based deadline constrained workflow scheduling algorithm for cloud systems. Int J Cloud Comput Serv Archit (IJCCSA) 3(6):89
Tawfeek M, El-Sisi A, Keshk A, Torkey F (2015) Cloud task scheduling based on ant colony optimization. Int Arab J Inf Technol 12(2):129–137
Watkins WA, Schevill WE (1979) Aerial observation of feeding behavior in four baleen whales: Eubalaena glacialis, Balaenoptera borealis, Megaptera novaeangliae, and Balaenoptera physalus. J Mammal 60(1):155–163
Ye F, Qi W, Xiao J (2011) Research of niching genetic algorithms for optimization in electromagnetics. Proced Eng 16:383–389
Zhan S, Huo H (2012) Improved PSO-based task scheduling algorithm in cloud computing. J Inf Comput Sci 9(13):3821–3829
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Thennarasu, S.R., Selvam, M. & Srihari, K. A new whale optimizer for workflow scheduling in cloud computing environment. J Ambient Intell Human Comput (2020) doi:10.1007/s12652-020-01678-9
- Wireless communication
- Service and semantic computing
- Autonomic computing
- Whale optimizer
- Bubble-net search mechanism