Abstract
Efficient load distribution plays an important role in grid and cloud applications. In a typical problem, a divisible load should be split into parts and allocated to several processors, with one processor responsible for the data transfer. Since processors have different speed and cost characteristics, selecting the processor order for the transmission and defining the chunk sizes affect the computation time and cost. We perform a systematic study of the model analysing the properties of Pareto optimal solutions. We demonstrate that the earlier research has a number of limitations. In particular, it is generally assumed that the load should be distributed so that all processors have equal completion times, while in fact this property is satisfied only for some deadlines; for many optimal schedules this property does not hold. Moreover, fixing the processor sequence in the non-decreasing order of the cost-characteristic may be appropriate only for Pareto-optimal solutions with relatively large deadlines; optimal schedules for tight deadlines may have a different order of processors. We conclude with an efficient algorithm for finding the time-cost trade-off.
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
Preview
Unable to display preview. Download preview PDF.
References
Abdullaha, M., Othman, M.: Cost-based multi-QoS job scheduling using divisible load theory in cloud computing. In: Proceedings of the 2013 International Conference on Computational Science (ICCS), pp. 928–935 (2013)
Beaumont, O., Legrand, A., Robert, Y.: Scheduling divisible workloads on heterogeneous platforms. Parallel Comput. 29, 1121–1152 (2003)
Berlińska, J., Drozdowski, M.: Scheduling divisible MapReduce computations, J. Parallel and Distrib. Comput. 71, 450–459 (2011)
Buyya, R., Abramson, D., Venugopal, S.: The grid economy. Proceedings of the IEEE 93, 698–714 (2005)
Charcranoon, S., Robertazzi, G.R., Luryu, S.: Parallel processor configuration design with processing/transmission costs. IEEE Trans. on Computers 49, 987–991 (2000)
Choi, K., Robertazzi, T.G.: Cost performance analysis in multi-level tree networks. In: Proceedings of the Ninth International Symposium on Parallel and Distributed Computing (ISPDC), pp. 41–48 (2010)
Chuprat, S., Baruah, S.: Real-time divisible load theory: incorporating computation costs. In: Proceedings of the 17th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, pp. 33–37 (2011)
Drozdowski, M.: Scheduling for Parallel Processing. Springer, London (2009)
Hu, M., Luo, J., Veeravalli, B.: Optimal provisioning for scheduling divisible loads with reserved cloud resources. In: Proceedings of the IEEE International Conference on Networks (ICON), pp. 204–209 (2012)
Jia, J., Veeravalli, B., Weissman, J.: Scheduling multisource divisible loads on arbitrary networks. IEEE Trans. on Parallel and Distrib. Systems 21, 520–530 (2010)
Kumar, S., Dutta, K., Mookerjee, V.: Maximizing business value by optimal assignment of jobs to resources in grid computing. European J. of Oper. Res. 194, 856–872 (2009)
Lin, W., Liang, C., Wang, J.Z., Buyya, R.: Bandwidth-aware divisible task scheduling for cloud computing. Software: Practice and Experience (accepted, available online, 2013)
Sohn, J., Robertazzi, T.G., Luryi, S.: Optimizing computing costs using divisible load analysis. IEEE Trans. Parallel and Distrib. Systems 9, 225–234 (1998)
Robertazzi, T.G.: Ten reasons to use divisible load theory. IEEE Computer 36, 63–68 (2003)
van Hoesel, S., Wagelmans, A., Moerman, B.: Using geometric techniques to improve dynamic programming algorithms for the economic lot-sizing problem and extensions. European J. Oper. Res. 75, 312–331 (1994)
Yu, J., Buyya, R., Ramamohanarao, K.: Workflow Scheduling Algorithms for Grid Computing. In: Xhafa, F., Abraham, A. (eds.) Meta. for Sched. in Distri. Comp. Envi. SCI, vol. 146, pp. 173–214. Springer, Heidelberg (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this paper
Cite this paper
Shakhlevich, N.V. (2013). Scheduling Divisible Loads to Optimize the Computation Time and Cost. In: Altmann, J., Vanmechelen, K., Rana, O.F. (eds) Economics of Grids, Clouds, Systems, and Services. GECON 2013. Lecture Notes in Computer Science, vol 8193. Springer, Cham. https://doi.org/10.1007/978-3-319-02414-1_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-02414-1_10
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02413-4
Online ISBN: 978-3-319-02414-1
eBook Packages: Computer ScienceComputer Science (R0)