Abstract
Cloudcomputing has transformed the world of communication systems into a new modern way. A cloud system consists of a vast variety of resources like processors, memory and software that are distributed all around the world. Task scheduling has a critical part in the performance and service of the cloud system. Plenty of task scheduling algorithms exist whose aim is to intensify the overall quality of the system. This article investigates and categorizes these algorithms based on task scheduling metrics of the cloud environment.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Palanivel, K., Kuppuswami, S.: A cloud-oriented green computing architecture for e-learning applications. Int. J. Recent Innov. Trends Comput. Commun. 2(11), 3775–3783 (2014)
Ashouraei, M., et al.: A new SLA-aware load balancing method in the cloud using an improved parallel task scheduling algorithm. In: 2018 IEEE 6th International Conference on Future Internet of Things and Cloud (FiCloud). IEEE (2018)
Ettikyala, K., Vijayalata, Y., Mohan, M.C.: Efficient time shared task scheduler for cloud computing. In: 2017 International Conference on Information, Communication, Instrumentation and Control (ICICIC). IEEE (2017)
Chiang, M.-L., et al.: An improved task scheduling and load balancing algorithm under the heterogeneous cloud computing network. In: 2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST). IEEE (2017)
Shobana, G., Geetha, M., Suganthe, R.C.: Nature inspired preemptive task scheduling for load balancing in cloud datacenter. In: International Conference on Information Communication and Embedded Systems (ICICES 2014). IEEE (2014)
Xue, J., et al.: A study of task scheduling based on differential evolution algorithm in cloud computing. In: 2014 International Conference on Computational Intelligence and Communication Networks. IEEE (2014)
Zhang, P.Y., Zhou, M.C.: Dynamic cloud task scheduling based on a two-stage strategy. IEEE Trans. Autom. Sci. Eng. 15(2), 772–783 (2018)
Wang, T., et al.: Load balancing task scheduling based on genetic algorithm in cloud computing. In: 2014 IEEE 12th International Conference on Dependable, Autonomic and Secure Computing. IEEE (2014)
Mittal, S., Katal, A.: An optimized task scheduling algorithm in cloud computing. In: 2016 IEEE 6th International Conference on Advanced Computing (IACC). IEEE (2016)
Li, K., et al.: Cloud task scheduling based on load balancing ant colony optimization. In: 2011 Sixth Annual ChinaGrid Conference. IEEE (2011)
Alla, H.B., Alla, S.B., Ezzati, A.: A novel architecture for task scheduling based on dynamic queues and particle swarm optimization in cloud computing. In: 2016 2nd International Conference on Cloud Computing Technologies and Applications (CloudTech). IEEE (2016)
Rjoub, G., Bentahar, J.: Cloud task scheduling based on swarm ıntelligence and machine learning. In: 2017 IEEE 5th International Conference on Future Internet of Things and Cloud (FiCloud). IEEE (2017)
Srichandan, S., Kumar, T.A., Bibhudatta, S.: Task scheduling for cloud computing using multi-objective hybrid bacteria foraging algorithm. Future Comput. Inform. J. 3(2), 210–230 (2018)
Dubey, K., Kumar, M., Sharma, S.C.: Modified HEFT algorithm for task scheduling in cloud environment. Procedia Comput. Sci. 125, 725–732 (2018)
Mansouri, N., Zade, B.M.H., Javidi, M.M.: Hybrid task scheduling strategy for cloud computing by modified particle swarm optimization and fuzzy theory. Comput. Ind. Eng. 130, 597–633 (2019)
Wang, B., Li, J.: Load balancing task scheduling based on Multi-Population Genetic Algorithm in cloud computing. In: 2016 35th Chinese Control Conference (CCC). IEEE (2016)
Yin, S., Ke, P., Tao, L.: An improved genetic algorithm for task scheduling in cloud computing. In: 2018 13th IEEE Conference on Industrial Electronics and Applications (ICIEA). IEEE (2018)
Gupta, P., Tewari, P.: “Monkey search algorithm for task scheduling in cloud IaaS. In: 2017 Fourth International Conference on Image Information Processing (ICIIP). IEEE (2017)
Nayak, S.C., Tripathy, C.: Deadline based task scheduling using multi-criteria decision-making in cloud environment. Ain Shams Eng. J. 9(4), 3315–3324 (2018)
Jena, R.K.: Energy efficient task scheduling in cloud environment. Energy Procedia 141, 222–227 (2017)
Tripathi, S., Prajapati, S., Ansari, N.A.: Modified optimal algorithm: for load balancing in cloud computing. In: 2017 International Conference on Computing, Communication and Automation (ICCCA). IEEE (2017)
Ettikyala, K., Vijaya Latha, Y.: Rank based efficient task scheduler for cloud computing. In: 2016 International Conference on Data Mining and Advanced Computing (SAPIENCE). IEEE (2016)
Zuo, L., et al.: A multiqueue interlacing peak scheduling method based on tasks’ classification in cloud computing. IEEE Syst. J. 12(2), 1518–1530 (2016)
Nayak, S.C., et al.: An enhanced deadline constraint based task scheduling mechanism for cloud environment. J. King Saud Univ.-Comput. Inf. Sci. (2018)
Joseph, J., Babu, K.R.: Scheduling to minimize context switches for reduced power consumption and delay in the cloud. In: 2016 International Conference on Micro-Electronics and Telecommunication Engineering (ICMETE). IEEE (2016)
Luo, F., et al.: An ımproved particle swarm optimization algorithm based on adaptive weight for task scheduling in cloud computing. In: Proceedings of the 2nd International Conference on Computer Science and Application Engineering. ACM (2018)
Sridhar, S., Smys, S.: A hybrid multilevel authentication scheme for private cloud environment. In: 2016 10th International Conference on Intelligent Systems and Control (ISCO). IEEE (2016)
Karthiban, K., Smys, S.: Privacy preserving approaches in cloud computing. In: 2018 2nd International Conference on Inventive Systems and Control (ICISC). IEEE (2018)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Tom, L., Bindu, V.R. (2020). Task Scheduling Algorithms in Cloud Computing: A Survey. In: Smys, S., Bestak, R., Rocha, Á. (eds) Inventive Computation Technologies. ICICIT 2019. Lecture Notes in Networks and Systems, vol 98. Springer, Cham. https://doi.org/10.1007/978-3-030-33846-6_39
Download citation
DOI: https://doi.org/10.1007/978-3-030-33846-6_39
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-33845-9
Online ISBN: 978-3-030-33846-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)