Abstract
In this paper we handle the problem of scheduling tasks in hybrid clouds for small companies which can spend only a fixed budget in order to handle specific situations where the demand is high and cannot be predicted. We describe a model with important characteristics for the resource utilization and we design an algorithm for scheduling tasks which are sent continuously for execution, optimizing the schedule for tasks with high priority and short deadline. We propose an architecture that meets the challenges encountered by small business in their systems for tasks scheduling. We describe the main components, Configuration Agent and Task Scheduler, and we analyze different test scenarios, proving the efficiency of the proposed strategy.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Oprescu, A.-M., Kielmann, T.: Bag-of-tasks scheduling under budget constraints. In: 2010 IEEE Second International Conference on Cloud Computing Technology and Science (CloudCom), Indianapolis, IN, 30 November–3 December 2010, pp. 351–359. IEEE (2010). Print ISBN: 978-1-4244-9405-7
Oprescu, A.-M., Kielmann, T., Leahu, H.: Budget estimation and control for bag-of-tasks scheduling in clouds. Parallel Process. Lett. 21, 219–243 (2011). doi:10.1142/S0129626411000175
Oprescu, A.-M., Kielmann, T., Leahu, H.: Stochastic tail-phase optimization for bag-of-tasks execution in clouds. In: IEEE/ACM Fifth International Conference on Utility and Cloud Computing (2012)
Van den Bossche, R., Vanmechelen, K., Broeckhove, J.: Cost-optimal scheduling in hybrid IaaS clouds for deadline constrained workloads. In: 2010 IEEE 3rd International Conference on Cloud Computing, pp. 228–235. IEEE (2010). Print ISBN: 978-1-4244-8207-8
Van den Bossche, R., Vanmechelen, K., Broeckhove, J.: Online cost-efficient scheduling of deadline-constrained workloads on hybrid clouds. Future Gener. Comput. Syst. 29(4), 973–985 (2013)
Yanpei, L., Chunlin, L., Zhiyong, Y., Yuxuan, C., Lijun, X.: Research on cost-optimal algorithm of multi-QoS constraints for task scheduling in hybrid-cloud. J. Softw. Eng. 33–49 (2015)
Nicolae, A.A., Negru, C., Pop, F., Mocanu, M., Cristea, V.: Hybrid algorithm for workflow scheduling in cloud-based cyberinfrastructures. In: International Conference on Network-Based Information Systems (2014)
Pop, F., Cristea, V., Bessis, N., Sotiriadis, S.: Reputation guided genetic scheduling algorithm for independent tasks in inter-clouds environments. In: 27th International Conference on Advanced Information Networking and Applications Workshops (2013)
Van den Bossche, R., Vanmechelen, K., Broeckhove, J.: Cost-efficient scheduling heuristics for deadline constrained workloads on hybrid clouds. In: Third IEEE International Conference on Cloud Computing Technology and Science (2011)
Gutierrez-Garcia, J.O., Sim, K.M.: A family of heuristics for agent-based cloud bag-of-tasks scheduling. In: International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (2011)
Pinedo, M.L.: Scheduling Theory, Algorithms and Systems, 4th edn. Springer, Berlin (2012). ISBN 978-1-4614-1986-0
Acknowledgements
The research presented in this paper is supported by the project DataWay: Real-time Data Processing Platform for Smart Cities: Making sense of Big Data, PN-II-RU-TE-2014-4-2731 founded by UEFISCDI. We would like to thank the reviewers for their time and expertise, constructive comments and valuable insight.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Marcu, OC., Negru, C., Pop, F. (2016). Dynamic Scheduling in Real Time with Budget Constraints in Hybrid Clouds. In: Altmann, J., Silaghi, G., Rana, O. (eds) Economics of Grids, Clouds, Systems, and Services. GECON 2015. Lecture Notes in Computer Science(), vol 9512. Springer, Cham. https://doi.org/10.1007/978-3-319-43177-2_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-43177-2_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-43176-5
Online ISBN: 978-3-319-43177-2
eBook Packages: Computer ScienceComputer Science (R0)